Google recently held its annual developer conference Google I/O 2023. Google is a large real estate owner with arguably more data than any other tech company in the world. This advantage cannot be overstated when it comes to training large language models (LLMs). In addition to having a strategic advantage for future development of LLMs with data, Google can offer advertisers instant ROI.
The primary announcements from the event were:
Google drops the waitlist for Bard and announces new features.
Google launches new Large Language Model, PaLM2
Unveils its new AI-powered Search.
Google Cloud announces new A3 supercomputer VMs built to power LLMs.
Google drops the waitlist for Bard and announces new features
Among the more exciting announcements at Google I/O, the company dropped the waitlist for Bard and the chatbot is now available in 180 countries and territories. Bard supports English, Japanese, & Korean languages, and will soon support more than 40 languages. Google is also rolling out features such as better source citations, the ability to export content generated in Gmail and Google Docs, support for more visuals and an upcoming Google Lens integration to analyze pictures and write captions.
Background on Google’s Bard:
Earlier this year, Google’s stock (Alphabet) tumbled 7% when chatbot Bard was unable to complete a search with 100% accuracy. During the demonstration, Bard returned incorrect information about which telescope was the first to take pictures of a planet outside the Earth’s solar system. This was a minor mistake given how far large language models and generative AI has come, rather it was the timing that was a bit flawed as OpenAI’s ChatGPT, the chatbot powering competitor Microsoft Bing, had been dominating headlines since its November 30th launch.
Microsoft, being an opportunist, took it a step further and announced Bing would now be powered by a faster and more accurate version of GPT-3.5 one day after Bard’s failed demonstration: “We’re excited to announce the new Bing is running on a new, next-generation OpenAI large language model that is more powerful than ChatGPT and customized specifically for search. It takes key learnings and advancements from ChatGPT and GPT-3.5 – and it is even faster, more accurate and more capable.”
Both companies have been preparing for this moment for many years. Microsoft invested $1 billion into OpenAI a few years ago with a new $10 billion round announced last month. Meanwhile, Google acquired DeepMind in 2014. Google also previously developed conversational neural language models such as LaMDA, which is used by Google’s Bard for its conversational AI technology.
Despite the mishap with Bard, it would be a human-generated mistake to think Alphabet does not command a place of leadership right now in generative AI. Alphabet was one of the first tech companies to focus and invest on AI and natural language processing (NLP). We pointed out to our premium research members in July of 2022 that ChatGPT is based on transformer architecture that Google initially introduced in 2017 when we said:
“Transformers are becoming one of the most popular neural-network models by applying self-attention to detect how data elements in a series influence and depend on one another.
Sequential text, images and video data are used for self-supervised learning and pattern recognition, which results in more data being used to create better models. Prior to transformer models, labeled datasets had to be used to train neural networks.
Transformer models eliminate this need by finding patterns between elements mathematically, which substantially opens up what datasets can be used and how quickly.
Google first introduced transformer models in 2017 and transformers are used in Google and Bing Search. Transformers also led to BERT models, which stands for Bidirectional Encoder Representations from Transformers, and is commonly used for text sequences. Transformers are also used in GPT-3 (it’s the T in GPT) which improved from 1.5 billion parameters to 175 billion parameters. GPT-3 has the ability to report on queries it has not been specifically trained on.”
Earlier this month, Google’s CEO, Sundar Pichai, gently reminded the AI community of how cutting edge Google’s research is when he stated, “Transformer research project and our field-defining paper in 2017, as well as our important advances in diffusion models, are now the basis of many of the generative AI applications you're starting to see today.”
BERT was designed to help Google better understand search intent, as despite billions of searches every day, about 15% of those searches are for brand new terms. This prompted Google engineers to develop a model that could self-learn.
The result is that searches results are more accurate by taking into consideration the nuances of language.
Google launches new Large Language Model, PaLM2
Google launched a new Large Language Model, PaLM2, that will power the updated Bard AI chat tool and more than 25 other new products & features including productivity software (Gmail, Google Docs), Healthcare and Security.
PaLM 2 has the following capabilities:
Multilingual: The LLM is trained on more than 100 languages, which increases language proficiency
Reasoning: The LLM’s dataset has improved logic, common sense reasoning and mathematics
Coding: The LLM can generate code including programing languages such as Python, JavaScript and specialized languages such as Prolog, Fortran and Verilog.
Google Unveils its new AI-powered Search
The company has unveiled its new generative AI-powered search that will be subject to a waitlist. Google cites the example of the following search “what's better for a family with kids under 3 and a dog, bryce canyon or arches.” Previously, you had to break the question down into smaller ones, sort through the vast information available, and then put things together yourself. Now with generative AI, search will be able to better understand the question.
Generative AI will also provide a better experience for online shopping by instantly getting relevant information like reviews, images, and ratings. The new shopping experience is based on Google’s Shopping Graph, which has more than 35 billion product listings.
The company announced the ‘About this image’ feature, allowing users to identify fake images. It mentioned in its press release, “When the image and similar images were first indexed by Google, Where it may have first appeared, and Where else it’s been seen online (like on news, social, or fact checking sites)”.
Google launches new Large Language Model, PaLM2
The company launched the new Large Language Model, PaLM2, that will power the updated Bard AI chat tool and more than 25 other new products & features announced during the Google I/O 2023.
Its predecessor PaLM, launched in April 2022, was a 540 billion based parameter, and the company did not provide this detail for PaLM2. PaLM stands for Pathways Language Model. “What we found in our work is that it’s not really the sort of size of model — that the larger is not always better,” DeepMind VP Zoubin Ghahramani said in a press briefing ahead of the announcement. “That’s why we’ve provided a family of models of different sizes. We think that actually parameter count is not really a useful way of thinking about the capabilities of models and capabilities are really to be judged by people using the models and finding out whether they’re useful in the tests that they try to achieve with these models.”
PaLM2 is faster and more efficient than previous models. Some of the improvements highlighted by the company are that PaLM2 is trained for improved multilingual text, spanning over 100 languages, reasoning, and coding, including popular languages like Python & JavaScript. For example, due to the multilingual capabilities of PaLM2, it has helped Bard to expand to new languages. PaLM2 is available in four sizes: Gecko, the smallest, followed by Otter, Bison, and Unicorn. Other use cases include improved Workspace features while working in Gmail, Google Docs, and Google Sheets. PaLM2 can also be used for enterprise use cases like Med-PaLM2 in medical research and Sec-PaLM in cybersecurity.
The company also said that it’s working on a more powerful model called Gemini and it will also be available in various sizes so that it can be easily deployed to various products.
Google Cloud announces new A3 supercomputer VMs built to power LLMs
Google Cloud announced the A3 GPU supercomputer that can be used to train and run Artificial Intelligence and Machine Learning models. While the A3 GPU supercomputer is on a private preview waitlist, the previously announced G2 VMs are now in general availability. The G2 VMs are powered by the new Nvidia L4 Tensor Core GPUs. The company said that it is the first cloud provider to offer these new GPUs for serving generative AI workloads.
The A3 GPU VMs are made of eight Nvidia H100 Hopper architecture GPUs, 3.6 TB/s bisectional bandwidth between A3’s 8 GPUs via the Nvidia NVSwitch and NVLink 4.0, 4th Gen Intel Xeon Scalable processors, and 2TB of host memory.
The A3 supercomputer can deliver up to 26 exaFlops of AI performance, thereby improving the time and cost of training large machine learning models. The A3 workloads will be run on Google’s Jupiter data center networking fabric which the company states“scales to tens of thousands of highly interconnected GPUs and allows for full-bandwidth reconfigurable optical links that can adjust the topology on demand.”
Conclusion:
I would not be surprised if we exit 2023 with a reimagined way to use Search Engines. The iteration cycle here is likely to move quickly compared to AVs or the Metaverse, as there are real-world applications where AI can be applied without safety issues (AVs) or friction in terms of user adoption (Metaverse/VR headsets). Instead, the scale has already been built with Search being a viral, daily activity used by nearly every human on earth. AI advancements will simply improve what is already in place.
Cutting-edge chatbots can be quickly deployed on the search engines that already exist, and this is a substantial difference from other overhyped, early-stage technologies. Their accuracy may still need time, but they're probably not too far off from being deemed “reliable enough.”
Investors should expect that AI will become a winner(s)-take-all market. In time, the difference in how search and other applications operate in terms of user experience plus ROI for advertisers will help carve a larger lead.
Premium Members should check the forum for updates on our timing for an entry into the stock.
This article was originally published on Forbes on May 10, 2023,07:45am EDTForbes Forbes on May 10, 2023,07:45am EDT
The mega-cap stocks that are known as FAAMG reported earnings recently. These names are driving the market higher, especially Microsoft and Apple. In fact, the percentage of Microsoft and Apple’s combined weighting in the S&P 500 has never been higher.
The S&P 500 weighting is according to market cap, which is price times float. The longer buying happens in these two names, accompanied with selling in other areas of the index, the percentage weighting becomes stretched to unhealthy extremes. This is not characteristic of a burgeoning bull market; instead, it is the type of behavior we usually see at market tops.
Also worth noting, since the February top, we are seeing a strong rotation into Big Tech while aggressive selling is taking place in other areas of the market. Take a look at the market cap weighted NASDAQ-100, which has over40% weighting into the FAAMG stocks, compared to the equal weighted NASDAQ-100.
Source: I/O FUND
While the NASDAQ-100 has made a series of higher highs, led mostly by the FAAMG names, the equal weighted index has made a series of lower highs. We are seeing similar price action in small caps as well as most economically sensitive sectors. This is typically not the sign of a healthy market.
FAAMG Stocks Trading at Precarious Valuations
As you’ll see below, there’s little room in FAAMG valuations compared to their 5-year historic averages. Apple and Microsoft both trade above their 5-year median on the top line and bottom line whereas the others are getting quite close given the low growth rates and macro uncertainty. The only exception is Amazon.
Microsoft is leading on valuation at 10 compared to the FAAMGs that are at 7 or below. Most are within range of their five-year average valuation except Amazon at 2.0 today compared to an average valuation of 3.6.
Source: YCHARTS
Amazon has a P/E ratio of 247.79, compared to 32.96 for Microsoft, 29.22 for Meta, 28.13 for Apple, and 23.32 for Alphabet. The FAAMGs are trading within range of their historical valuation except for Amazon with a five-year average P/E ratio of 93.48.
Source: YCHARTS
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FAAMG Earnings Overview:
There were some puts and takes in the most recent earnings reports. Despite price telling us we could be nearing a top, there are some fundamental signs that FAAMG stocks may be overstretched in the near term.
Below, you’ll find that consensus points toward a bottom for FAAMG stocks yet it will require consensus materializing in the coming quarters in order for the stock price action to hold. In other words, the market has front run the rebound in growth and now we must wait and see if this rebound unfolds.
Alphabet: Search is Resilient
Alphabet’s revenue grew by 2.6% YoY or 6% in constant currency, for a total of $69.8 billion, primarily helped by the resilience in Search and the momentum in Cloud business. Although this is marginal growth, below you can see that Alphabet is expected to accelerate in revenue growth over the next few quarters from 2.6% to an expected 9.4% in Q1 of next year.
Source: SEEKING ALPHA
Operating margins were soft at 25% of revenue compared to 30% last year. Net income declined (8.4%) YoY to $15.1 billion. This resulted in EPS of $1.17 compared to $1.23 for the same period last year.
Source: YCHARTS
The drop in profits was mainly due to $2.6 billion in charges related to the reduction in the company’s workforce and office space, and was offset by $988 million in depreciation from servers and network equipment.
Google Cloud revenue grew by 28% YoY to $7.45 billion and reported its first profitable quarter bringing in $191 million operating income.
Microsoft: Top Line and Bottom Line Beat
Microsoft’s revenue grew 7.1% YoY and 10% in constant currency to $52.9 billion. Management’s revenue guidance for next quarter is $54.85 billion to $55.85 billion, representing YoY growth of 6.7% at the mid-point. Similar to Google, a noticeable acceleration is expected in the second half of the year.
Source: SEEKING ALPHA
Azure grew by 27% and 31% YoY in constant currency and came in at the higher end of management guidance of 30% to 31%.This is down from 38% growth in constant currency last quarter. Next quarter will also mark a deceleration with management guiding to 26.5% in constant currency. This includes 1% from AI services.
Source: I/O FUND
Operating income grew by 9.8% YoY to $22.35 billion. The net profit margin was 34.6% compared to 33.9% in the same period last year which resulted in EPS of $2.45 compared to $2.22 in the same period last year.
Source: YCHARTS
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Meta: Back to Positive Growth
The company’s revenue grew by 2.6% YoY and 6% on constant currency to $28.6 billion. This is a positive as Meta’s revenue has declined YoY in the last three quarters.
Management’s revenue guidance for the next quarter is between $29.5 billion to $32 billion, representing a YoY growth of 6.7% at the mid-point. Analysts expect revenue to grow 7% YoY to $30.84 billion.
Source: SEEKING ALPHA
The operating income declined by (15%) YoY to $7.2 billion as total expenses rose 10% YoY. The operating margin was 25% compared to 31% in the same period last year. The net income declined by (24%) YoY to $5.7 billion, resulting in EPS of $2.20 compared to $2.72 in the same period last year.
Source: YCHARTS
The company recorded $1.14 billion in restructuring charges related to layoffs, facilities consolidation, and data center. Excluding these charges, the operating margin would be 4% higher and EPS would be $0.44 higher.
Amazon: AWS is Slowing
The company’s revenue grew by 9.4% and 11% YoY in constant currency to $127.4 billion. Analyst consensus is for growth of 8.2% next quarter.
Source: SEEKING ALPHA
The operating margin was 3.8% compared to 3.2% in the same period last year. Net Income was $3.2 billion or $0.31 per share compared to a net loss of ($3.8) billion or ($0.38) per share in the same period last year.
The net income included a pre-tax valuation loss of ($0.5) billion from the investment in Rivian Automobile compared to a pre-tax valuation loss of ($7.6) billion in the same period last year.
Source: YCHARTS
AWS revenue grew by 16% YoY to $21.4 billion. This is lower than the 20% growth in the December quarter and a remarkable slowdown from the 37% in the same period last year.
Management discussed in the earnings call that April AWS revenue growth further decelerated to 11%. This is due to the ongoing tough macro environment, causing customers to optimize their cloud spending in the recent quarter.
The company’s CEO, Andy Jassy, also highlighted cautiousness in the enterprise customers. “In AWS, what we’re seeing is enterprises continue to be cautious in their spending in this uncertain time. Customers are looking for ways to save money however they can right now. They tell us that most of it is cost optimizing versus cost cutting, which is an interesting distinction because they say they’re cost optimizing to reallocate those resources on new customer experiences.”cost optimizing versus cost cutting, which is an interesting distinction because they say they’re cost optimizing to reallocate those resources on new customer experiences.”
Notably, despite the market rewarding Microsoft’s report, cost optimization is not isolated to one hyperscaler and investors can expect to see more evidence of optimizations in future reports.
Apple: More Buybacks to Appease the Street
Apple’s revenue declined by (2.5%) YoY to $94.84 billion. Management commented that they expect YoY performance to be similar to the March quarter. Analysts expect revenue to decline (1.7%) YoY to $81.53 billion in the next quarter following these comments.
Source: SEEKING ALPHA
iPhone sales grew by 1.5% YoY to $51.3 billion. Mac revenue declined by (31%) YoY to $7.2 billion. iPad revenue declined by (13%) YoY to $6.7 billion. Wearables, home and accessories revenue was flat, and the services segment revenue grew by 5.5% YoY to $20.9 billion.
The operating margin was 29.9% compared to 30.8% in the same period last year. The operating expenses of $13.66 billion were lower than management guidance of $13.7 billion to $13.9 billion, which the market saw as a positive.
Net income declined by (3.4%) YoY to $24.2 billion with a net profit margin of 25.5% compared to 25.7% in the same period last year. EPS came in at $1.52 and remained unchanged from the same period last year.
Source: YCHARTS
Apple returned $23 billion to the shareholders through dividends and equivalents of $3.7 billion and $19.1 billion in share repurchases. The board also authorized an additional $90 billion share repurchase and increased the quarterly dividend by 4% to $0.24 per share.
Analyst Comments:
Deutsche Bank analyst Benjamin Black raised the firm's price target on Alphabet to $125 from $120 and kept a Buy rating on the shares. He noted, “The company reported solid Q1 results with the biggest takeaway being the stabilizing growth trends at Search and YouTube, which beat Street expectations.”stabilizing growth trends at Search and YouTube, which beat Street expectations.”
Wedbush Securities analyst Dan Ives said in a research note. "It's clear that in Redmond's enterprise backyard the company is gaining more market share on the cloud front with many enterprises making this transformational shift on the shoulders of Microsoft,"gaining more market share on the cloud front with many enterprises making this transformational shift on the shoulders of Microsoft," He further said, "Cloud growth and the overall outlook for the June quarter was solid and much better than feared given recent noise in the market and will be music to the ears of investors this morning digesting results."Cloud growth and the overall outlook for the June quarter was solid and much better than feared given recent noise in the market and will be music to the ears of investors this morning digesting results."
BMO analyst Keith Bachman upgraded Microsoft (MSFT) shares to outperform. He stated that he now has "higher conviction" that any headwinds to Azure are likely to moderate by the end of the year, while opportunities in artificial intelligence can help the longer-term. "While the stock is not inexpensive, we think the durable growth opportunities warrant a premium valuation."
RBC Capital analyst Brad Erickson raised the firm's price target on Meta Platforms to $285 from $225 and kept an Outperform rating on the shares. Brad said, “The company's Q1 results were better-than-feared and the simple three-fold bull case – dominating engagement vs. competition, restoring lost signal post-IDFA, and cutting costs – is increasingly coming into view.” RBC believes that further upside is still achievable for Meta on engagement share gains and the ongoing conversion improvement eventually leading to incremental spend.
Citi analyst Ronald Josey raised the firm's price target on Meta Platforms to $315 from $260 and kept a Buy rating on the shares. “With engagement rising, newer advertising products attracting incremental spend, and a more streamlined organization, Meta's momentum in Q1 can continue.”“With engagement rising, newer advertising products attracting incremental spend, and a more streamlined organization, Meta's momentum in Q1 can continue.” the analyst tells investors in a research note.
Conclusion:
We have Buy levels we are targeting for FAAMG stocks, which we share with our premium research members each week as the stocks progress. We believe our target buy levels will set us up for gains in FAAMG stocks when the next bull cycle begins. We provide in depth macro and individual stock analysis so that readers can better understand why we buy/sell. In this market, we frequently take gains.
Right now, we do not believe FAAMG stocks are in a buy zone. Instead, some are trading higher than their 5-year median on valuations despite a weaker macro backdrop and fundamental weakness. The market is front-running the anticipated revenue rebound. Most of this rebound is based off low comps, and there could be soft growth in the future for some of these names.
You can learn more here including information on our next webinar, this Thursday at 4:30 pm Eastern, where we review our positions live.
Equity Analyst Royston Roche contributed to this article.
Please note, that Perion is a Hold right now and we will inform our Premium Newsletter Members if we initiate a position. The I/O Fund is unique in that we do not issue blanket buy recommendations, rather we offer an actively managed portfolio. We do not own the stock right now but we hope to enter the stock when the technicals line up. Our process is tied to a real portfolio with audited results. Our service aims to show individual investors the reality of stock investing, which is to do extensive due diligence, and then to be patient on price. In addition, tech investors must be especially keen on macro events as the tech sector is particularly sensitive to high interest rates. This is very different from other services that push out content with no adherence to actual performance and/or entries, exits.
Summary:
Last March, we covered Google’s anti-trust lawsuit here for premium newsletter members. This is an important analysis to revisit for Perion Network.Google’s anti-trust lawsuit here for premium newsletter members. This is an important analysis to revisit for Perion Network.
Perion Network is a digital advertising company headquartered in Holon, Israel. The company offers digital solutions in three primary channels of digital advertising: ad search, social media, and display/video/CTV advertising.
Perion helps brands and publishers to identify and reach customers through the company’s proprietary Intelligent HUB (iHub), which processes billions of signals, and powers the cookieless solution SORT. By mixing contextual data with user insights, Perion is able to forego cookies by using this data with AI-based clustering techniques. SORT stands for Smart Optimization of Responsive Traits, which translates to categorizing customers into 1 of 30 Smart Groups through shared traits.
The primary sources of data are contextual – so what a customer is reading at the moment, why they’re reading it, how long they’re reading it and/or what search words brought them to the content. This is combined with signals such as time of day, weather, browser, device, etc.
Ultimately, what Perion’s technology does is calculates the similarities between groups, and then to target the group that performs the highest in terms of converting. The model is deemed effective when one group has a significantly higher click-through-rate (CTR).
Second, SORT then optimizes the bids so that it’s a cost-effective solution. SORT analyzes the bid of each publisher and selects the price that is likely to win. If the price is too high, SORT finds another publisher with a similar audience as the SmartGroup. The entire process happens in real-time.
Doron Gerstel, CEO of the company, said in the Q2 2022 earnings call, “iHub sits in the center of the supply and the demand side of the market. This is an innovative model that no one else in the industry has, aggregate data signals from all channels and from both sides of the open web to create the model that eliminates waste and rewards clients. The data goes into Perion’s privacy first cookieless solution known as SORT.”
This is important because cookies are expected to be phased out from Chrome in 2024. Cookies have already been phased out by Mozilla Firefox and Apple Safari.
In addition to this, Perion has partnered with Microsoft Bing. CodeFuel is the Perion product that powers intent-based monetization. When you go to search for something on a search engine, Perion’s CodeFuel can power the search results in an optimal way for conversion. This has led to a strategic partnership between Microsoft and Perion that was renewed in 2020 for four years.
Per a previous earnings call, “If the new Bing search with ChatGPT sparks even modest share gains, Microsoft can do very well in the business. As their CFO, Amy Hood said yesterday, every percentage point of share it gains in search equals roughly $2 billion in additional advertising revenue, and as a strategic partner of Microsoft Bing, I’m sure we will be benefiting from this increase.”I’m sure we will be benefiting from this increase.”
Notably, there is a risk that Microsoft does not renew its partnership next year. However, this risk is muted a bit since Perion was named “Global Supply Partner of the Year” by Microsoft in 2022.
What’s interesting about Perion is that the company is fundamentally one of the strongest ad-tech companies on the public markets due to a strong bottom line and a top line that was more resilient than its peers. Any windfall here could very interesting for a company that already proven operational efficiency with a 16% to 20% operating margin while maintaining 30%+ growth in the tough year of 2022. Notably, the top line is decelerating to the 10% to 15% range but a catalyst here that could lead to a reversal could be quite interesting
Perion Networks: Google Anti-Trust Beneficiary Plus AI Tailwinds
We published a piece in March on the potential outcomes from Google’s anti-trust trial slated to begin in the fall of this year. If Google is found to have engaged in anti-competitive behavior, we identified Perion Networks (PERI, $1.5b mkt cap) as a potential beneficiary.
Currently, Perion holds a unique position in the advertising technology sector that has enabled it to outperform its peers. Perion recently reported Q123 earnings. At a time when its peers are dealing with advertising budgets that are in flux, Perion revised upward its 2023 sales target. The earnings report provided a good opportunity to get an update on the business and the main business drivers.
Perion is positioned to benefit from several key investment themes.
Maximizing search monetization and integration with AI
Helping companies compete against Amazon and Walmart
Increased browser privacy awareness
Outsourcing of video advertising functions
Maximize advertising budgets
What does Perion do?
Perion is a digital advertising company that provides technology to brands, agencies and publishers to identify, reach and monetize their most valuable customers – across numerous digital channels, including retail media. Clients include world-class brands such as Mercedes-Benz, IBM, Disney, Walmart, Albertson’s and Verizon.
Perion has two main businesses, Display and Search advertising. They make up 55% and 45% of total revenue, respectively. Within these divisions, there are 3 main activities
Search ad monetization, a direct-response platform that works with a range of different publishers
Cross-channel high impact advertising through the open web, including video and CTV
Social advertising through Perion’s performance monitoring platform and content monetization system
There are 5 key business drivers
1. Search Advertising and AI
Capturing consumers at their moment of highest intent has been well-established as the highest ROI (Return on Investment) advertising channel. Advertisers are increasingly allocating funds to search advertising. According to eMarketer reports, U.S. search advertising market reached $101 billion in 2022, and is estimated to reach over $108 billion in 2023, which represents 39% of U.S. digital ad spending.
Search is a fundamental digital behavior that will continue to grow. Perion continuously innovates to provide more value to its publishers. Perion deploys advanced AI, neural networks, and machine learning to optimize yield for its publishers and transform search into revenue. As this shift continues, Perion is well positioned thanks to its longstanding relationship with Microsoft Bing. In 2022, Perion was named Microsoft Advertising’s Global Supply Partner of the Year.
Search monetization is one of Perion’s core and most profitable areas. The business is driven by 1) increasing the number of publishers 2) the aggregate number of monetized searches transferred, mainly through its partnership with Microsoft Bing and 3) integration of ChatGPT with Microsoft Bing
In Q123, these 3 factors contributed to a 29% increase in the number of publishers. As a result, average daily traffic increased by nearly 50% year-over-year and are now close to 30 million monetized searches per day on an average basis. The ability of Perion to monetize search traffic through their Microsoft Bing Partnership and its effectiveness is best reflected in the growth of Perion’s publisher network. This is particularly important given the growing shift to Direct Response, as search represents the highest intent customers.
This is how Perion described the ChatGPT impact and opportunity. Notably, Microsoft Bing has 3% market share and for every additional 1%, Microsoft will make an additional $2 billion. This may not be enough to move Microsoft stock, but can have an impact on Perion.
“We believe that the massive media attention to ChatGPT has driven a material portion of this (Q1 growth) and that will continue to see growth that exceeds our normative project. Microsoft Bing has a real competitive advantage now and that cascade[s] immediately to our business.”
“Now to other part of your question, I think that this is – it’s beyond what we able to imagine, what the ChatGPT is going to make. It’s quite a transformation. Quite a transformation and I would say that the search interaction as we’ve seen an experience in let’s say the last 20 years is not going to be the same. And we will have a chance to look at it two years from now, it would be completely different interaction, user experience, engagement between consumer and search engine. No doubt about it.”
2. Perion’s retail media solutions
Perion provides digital advertising for major retailers who have launched their own digital presence to compete with Amazon and Walmart. Perion works with companies such as Albertson’s, CVS and Target. Perion has built an AI-driven platform that enables these retailers to maximize the value of their inventory with ad units that identify consumer signals and responds with timely and personalized promotion and content. Perion can personalize at scale and can do it in an omni-channel fashion across all screens.
This allows retailers to shift away from transaction campaigns (i.e. circulars) to “always on” which generates higher returns. For Albertson’s, Perion delivered 14 times return on ad spend.
As the chart below shows. Perion develops targeted advertising at various touchpoints for different companies to target the consumer throughout the day. As the diverse client list below shows, this ranges from RiteAid to P&G to GSK.
3. SORT and Privacy
Perion’s proprietary SORT (Smart Optimization of Responsive Traits) technology will benefit from ever increasing privacy demands. SORT is a cookie less and totally anonymous solution that protects consumer privacy. Further, SORT does not collect or store any user data, the way other cookie-less solutions do. This is attracting brands who wants to be associated with the privacy-first capability while generating strong ROI.
Cookies are an essential part of the targeting infrastructure of the digital advertising market, they are under increasing pressure for the manner in which they are perceived to violate user privacy. In fact, the U.S. Congress is looking into cookies and considering further restrictions. SORT provides a competitive solution that should enable Perion to capture additional revenue as brands and advertisers move away from traditional methods such as cookies and other platforms. Google has postponed its elimination of cookies until the end of 2024 presumably because they need to do further testing to develop a satisfactory replacement solution.
In addition, consumers are made aware that a brand campaign is running through SORT, and hence the ads are safe to click, thanks to a proprietary “Privacy Shield” graphic logo that is incorporated into every ad unit running through SORT. SORT is a solution that provides consumers with visible confidence they won’t be followed around the web as their behavior is being tracked.
Currently, Perion’s clients range from Mercedes Benz to the United Nation. SORT will grow as it attracts more brands who want to be known for espousing privacy first principles.
4. Video Platform
Via their Vidazoo division, Perion’s end-to-end platform is meeting a large and growing need for publishers who are looking for fast results and lack the internal resources to build the complex time maintenance internal system. Perion is able to offer different aspects of the Vidazoo suite depending on their client’s needs.
Through Vidazoo’s proprietary video platform, Perion offers a wide range of products, through which publishers can deliver an enhanced user experience, increase video content consumption, and identify new monetization opportunities.
A simple example is how Dr. Pepper, using Perion’s Vidazoo, was able to run an ad while a sport event was playing. There was no interruption to the viewer.
5. iHUB
Perion’s proprietary Intelligent Hub (iHUB) connects the supply and demand sides of the ad marketplace. It processes billions of signals from across its network and properties. This provides five levels of value: operational savings in the form of – shared resources; reduced traffic acquisition costs and media buying optimization; increased customer value; market agility.
For Perion, iHUB helps increase its media margin (Revenue less traffic acquisition costs or TAC) by lowering TAC costs. While for Advertisers, iHUB helps them reach their ROAS (Return on Ad Spend) goals.
iHUB allows Perion’s business units to quickly balance demand and supply, providing optimum utilization of their owned & operated supply, as well as what is available on the open web. This optimization is enhanced by their ability to offer publishers and advertisers multiple ad products to support their marketing efforts which enables Perion to increase its market share with current and new clients. This helps reduce Perion’s TAC.
At the end of the day, companies seek to maximize their advertising budgets. Perion is able to help companies satisfy their ROAS though iHUB. This technology is Perion’s key competitive advantage. This is how Perion described it.
“We’re able to capture and analyze data signal from all channels and from both sides of the open web into our central hub. We’re using advanced AI to develop a bidding system that maximize our unit revenue, while reducing our video costs. By doing this, we uniquely combine efficient bind with the ability to meet our customer ROAS, Return on Ad Spend expectations. At the same time, when advertiser under extreme growth pressure, this is a true competitive advantage for us.”
“Without having all the pieces of the business connected, we would be managing a very costly, inefficient, fragmented business. On a given day, we capture into iHUB data lake billions of data requests from various media channels. One example of effectively leveraging this amount of data is creating an AI driven bidding strategy that optimizes the match between supply and demand to maximize our profit.
At the same time, it assures the highest performance to our customers. Our iHUB open architecture is a foundation that enable us to make acquisitions, which are instantly optimized because they plug in into the center of our ecosystem. As FX grows more complex and multi-dimensional, the value of our iHUB will only become way more meaningful.”
Q123 Earnings
Perion recently exceeded Q1 earnings expectations and revised their FY23 sales target of between $725-745 million which is 15% year-over-year growth at the midpoint.
One risk for Perion is that the revenue growth rate decelerated from the 30% range in prior quarters to 15.8% in the most recent quarter. Right now, analysts are showing further deceleration. We will want to see Perion resist this deceleration through one of the catalysts noted above – whether it’s product-market fit with niche advertisers, Microsoft-Bing partnership with Bing increasing in market share due to Chat-GPT and/or Google’s anti-trust lawsuit having a favorable outcome.
With increasing EBITDA and Profitability (EBITDA Margins). The GAAP operating margin was up year-over-year at 16.8% this quarter compared to 13.17% in the year ago quarter. However, this was down from the September quarter and December quarter, both in the 19% to 20% range. This is something to watch, to make sure it continues to trend up – if not on a sequential basis than at least on a year-over-year basis.
Q1 media margin increased year over year (Sales less TAC)
The balance sheet is very strong for a small cap stock with $384 in cash and no debt.
Conclusion:
Through different market environments from 2020 to 2022, Perion has continued to execute from a business and financial perspective. It demonstrates that through changing consumer and advertiser needs, Perion has been able to adapt and meet those needs.
During a time when advertising budgets are under pressure, Perion’s key competitive advantage is its technology provides a meaningful ROI on ad dollars spent by its customers.
Perion’s partnership with Microsoft Bing, while still in its early stages provides an exciting growth opportunity in its Search business. Meanwhile, Retail Media and SORT are businesses that will continue to grow. Later in the year, depending on the Google court case, Perion may also benefit.
Deep dives, trade alerts, a forum and weekly webinars on the I/O Fund portfolio are offered on our premium service, you can find out more information here.Deep dives, trade alerts, a forum and weekly webinars on the I/O Fund portfolio are offered on our premium service, you can find out more information here.more information here.
We’d like to set our sights on a few ad-tech names that may benefit from the Google antitrust lawsuit. It may feel like the words “Google” and “lawsuit” are commonplace, but the trial in September carries enormous weight and is unlike the lawsuits of the past. Not only do we want to identify what ad-tech names could benefit should Google’s monopoly be broken up and the juggernaut come out weaker, but we also want to be prepared if the tech giant is able to hold off regulators.
Considering that Google is sitting on the world’s very best consumer data, which is not an exaggeration in the least bit, its ability to lead on artificial intelligence and large language models should not be underestimated. For our purposes, the company is far from sitting on its laurels and there’s a predictable path where the company competes in a duopoly with Microsoft.
Therein lies the issue. Google undisputedly has the world’s best consumer data, but did this grow to become part and parcel with operating a monopoly? The Department of Justice has asserted anti-trust violations against Google with the trial beginning in September 2023. The trial is expected to last ten to 12 weeks, although a lawyer for the DOJ told CNBC it could be as brief as five weeks.
Why it matters:
With Google and other ad-tech companies trading this low, one of two outcomes will happen. The antitrust outcome will be mild, and Google will be empowered to continue to dominate. Or, the outcome will require the ad properties to be broken up, leading to a weaker stance for Google. This could benefit smaller ad-tech players.
The Goal — Looking back:
A few years back, I analyzed the potential outcome of a government decision when the Pentagon was evaluating cloud providers. Clearly, this decision is far outside of anyone’s control and requires some speculation. At the time, I speculated Azure would be a winner. For a year or so, Microsoft did secure the Pentagon contract over the more-favored Amazon. This decision was ultimately reversed, and the contract was split between four tech companies.
The exact outcome of the Pentagon contract was not particularly important because the analysis led to my conclusion that Microsoft’s hybrid computing was a material advantage and this would be the path Nadella would most likely use to take market share from AWS’s heavily-slanted public cloud strategy.
I’m hoping for something similar, which is to acknowledge something very important is going on with ad-tech, which is Google’s antitrust case. This is not a headline to simply dismiss. It’s the first time the DOJ has brought a case of this kind against a technology company since Microsoft. If there are even minor cracks in Google’s monopoly, there could stand to be a stock or two that starts a new trajectory.
On similar note, Cambridge Analytica is what sparked my coverage on Facebook. Similar to Google’s antitrust case, it became apparent to me that Facebook was peaking in terms of its ability to monetize through third party data. I covered this extensively, for example here and here.
Brief Overview of Antitrust Case:
According to Lanier Law Firm, which is the litigation team for the State of Texas in the state coalition case, a primary argument against Google is that the company went above and beyond to become the default search engine on iOS devices by paying Apple $12 billion per year.
The lawsuit includes other deals that Google struck with Apple’s Safari browser, the Mozilla browser and Android device manufacturers where Google either paid up or imposed restrictions on Android device makers to strongarm having their suite of apps pre-installed on the home screen.
The company has already lost an antitrust case in Europe in 2018 with a $4.4 billion Euro fine for forcing Android manufacturers to pre-install Google’s bundle of apps on the device, including Chrome, Maps and the Play Store.
Google’s market share of Search is at 91% and the argument is being made this was accomplished through anti-competitive practices, especially since Google owns Android and had leverage over the many device makers that used this operating system.
In addition to being pre-installed and the default browser/search engine, Google also attempts to keep people on its search engine by using a website’s data on its page. For example, if you look up “Best Dog Breed” Google scrapes Wikipedia and puts the results onto the search page instead of sending you to Wikipedia. This is seen as anti-competitive as it takes a website’s data to profit from it, rather than directing the traffic to the rightful copyright owner, which is the function of a search engine.
Part of Microsoft’s antitrust case was based on Microsoft using its dominance on Windows to force a Microsoft Explorer to be the default browser. At the time, the decision was that default settings are anticompetitive.
The secondary argument filed by a 10-state group led by Texas, is that Google leverages its properties to be the buyer and the seller via its ad exchange. Per Lanier Law Firm, the Texas case states Google and Facebook “unreasonably restrained trade and harmed competition through an unlawful agreement to allocate auction wins and to fix prices in violation of Section 1 of the Sherman Act, 15 U.S.C. § 1”
This is where it gets very messy, and so I’ve dedicated a specific section below to break down these details. The purpose of understanding the minutiae is not to only determine if we should buy Google and when, but also what companies could stand to benefit if Google’s products are shutdown or broken up.
My long-ago analysis on Facebook pointed toward a conflict of interest in the company owning a third-party ad network called Audience Network while also being publisher. At the very least, the conflict of interest created a risk since Facebook was essentially siphoning oil from real estate the company didn’t own (iOS users). This was a serious, material risk for investors that played out over time (note: it certainly wasn’t immediate, it took four years from the first time I covered the topic).
If you’re a Meta investor, you’ll want to watch the CPMs on the company and make sure the erosion below is not permanent. Despite Apple only impacting third-party data, it’s unclear how much of that third-party data was informing its first party data. The unusually high CPMs that Meta charged points towards enhanced targeting – that in my opinion – was likely due to mixing both first-party data with third-party data. This means there will be an eventual erosion, over time, of the CPMs Facebook can charge even on its own applications.
Pictured above: Although subtle, there is an erosion to Facebook’s otherwise high CPMs. You can see that Nov 2022 made a lower high over Black Friday compared to the two previous years. Many factors could be at play, such as lower ad budgets, but it’s something investors should keep a close eye on.
Google currently does the same thing that Facebook used to do, which is to run an ad exchange that is undeniably a conflict of interest. The difference is that rather than renting real estate, like Facebook did with iOS, Google is a real estate tycoon. There isn’t a tech company that can kick Google off their turf because Google owns all of the turf – primarily Chrome, Android, Google Search, and YouTube.cBy conflict of interest, I’m referring to AdX, DoubleClick and DV360, collectively known as the Google Network.
Below, you can see Google Network is a $32 billion annual revenue stream. Not exactly peanuts.
To further the lawsuit, a 30-state coalition has issued a third claim that Google uses its monopoly to rip off smaller companies, such as Yelp, DoorDash, and Kayak. You can see evidence of this when Google Search returns flight searches powered by Google at the top, with a large embedded format, rather than producing a fair search result that includes competitors. Yelp has been in a battle with Google over this for over a decade. After Google Reviews were launched, Google pushed Yelp down the page in terms of search results.
The two search engine allegations are fairly straight forward. Most of us who use Google Search can reasonably understand those arguments.
The Messy, Blackbox that is AdExchange (AdX):
DoubleClick was acquired in 2007 for $3.1 billion. As author Tony Yiu points out on Toward Data Science, this was twice the amount paid for YouTube a year earlier. Google Network is a by-product of many acquisitions including AdMob for $750 million and AdMeld for $400 million, among others, yet DoubleClick truly set the supply side dominance in motion as the company owned 60% of the desktop publisher market at the time of acquisition.
DoubleClick allows Google to set a cookie on a website so that online publishers can better target visitors with ads. The DoubleClick cookie provides the time and date a user saw an advertisement, as well as a unique ID that identifies a user by their browser. Publishers are then able to auction inventory to advertisers.
DoubleClick was a major move by Google to expand beyond search advertising. This was the first time Google entered the market on display ads. As stated, DoubleClick owned 60% of the publisher market when it was acquired, which means Google would eventually profit from monetizing millions of websites.
This led to a concentration of power for Google, because with this advantage, it was able to grow quickly as a predominant ad server for publishers. Naturally, Google wanted to maximize this advantage, and so the company made the appropriate acquisitions to operate on the demand side (advertiser side) in addition to the publisher side.
Through a series of acquisitions, Google built DV360, which allows advertisers to use their own data to target customers across publisher inventory. Google always has strong ties to data, in this case powering DV360 with Google Analytics 360. In addition to this, Google’s AdX allows advertisers to create campaigns across Google-owned properties in addition to millions of websites from third-party publishers on the DoubleClick publisher side, as mentioned above.
An easy analogy here would be to compare it to a real estate transaction, since ads are transactional between a buyer and seller. In this case, Google was representing both the buyer and the seller, and in some cases brokered its own real estate to the buyers. You can imagine due to Google’s scale of doing millions of transactions a day, things might get unethical real quick.
Here’s how a Google executive put it:
“[I]s there a deeper issue with us owning the platform, the exchange, and a huge network?” the executive allegedly asked. “The analogy would be if Goldman or Citibank owned the NYSE.”
With that in mind, let’s continue because the depth of Google’s black box is quite deep.
The product AdSense further pools the data provided by publishers. When millions of websites join AdSense to pool data, Google can record more information on a person’s browsing history. It provides a complete view of the consumer for more enhanced targeting. Another area that Google allegedly monopolizes the market is that the company mixes its first party data with this third party data, but only in instances where Google will benefit.
The AdMob acquisition in 2009 provided a similar strategy as DoubleClick but on mobile. It deepened Google’s reach on the supply side for the mobile market. This, of course, was especially advantageous considering Google bought Android in 2005.
You can imagine, that the depth of Google’s data on desktop users and mobile users is deep (and likely quite dark). Meaning, Google knows more about you than you know about yourself. Now, take that depth of data and add the serious conflict of interest that can occur when Google bids against competitors.
Where Google (Allegedly) Went Wrong with AdX
Despite the allegations below that Google was unethical, I want to point out that antitrust could be harder to prove for AdX. This is because many corporations combine first-party publisher data with a third-party ad exchange, such as Amazon, Facebook, Disney and Comcast. Microsoft is building its ad exchange, as well right now, after acquiring Xandr from AT&T. However, Xandr/Microsoft’s strategy is to support the “free and open web” by adopting the Unified ID.
Point being, if the product AdX is found to be anticompetitive, it could have far-reaching implications for other companies. This wasn’t the case with Microsoft, as the company was rather isolated on its throne in the late 90s. With that said, Google is the worst offender in terms of the sheer advantages it has compared to other corporations with large media properties.
Here are some of the more unethical things Google is being accused of:
According to the lawsuit, there was a 65% drop in revenue if publishers chose to not use Google on the demand side. Advertisers are also stating this was a conflict of interest as Google restricted inventory in this case. This would be like a real estate agent refusing to show a house if they did not have both the buyer and the seller to double-end the transaction.
Google also allegedly circumvented waterfall auctions to prioritize their own bids on AdX. Waterfalls were prevalent throughout the ecosystem because they allow exchanges to be ranked by bids. Based on historical bids, if the ad exchange in the number one position doesn’t buy the inventory, it goes to the next ad exchange in the waterfall (the number two position).
Where Google may have manipulated the bidding is by allowing their exchange to meet only floor prices to win the bid, even when another exchange would have bidded higher in a waterfall-like auction. This would be like a real estate agent only presenting their Buyer’s offer to a Seller even if they knew they could get higher offers from another agent.
Due to DoubleClick and AdX waterfalls having the issues described above, programmatic header bidding was introduced to offer true, real-time bidding to increase publisher yield. It essentially increased competition by holding an open auction rather than a closed, blackbox auction that pushes inventory back and forth in an attempt to sell the inventory.
Per Digiday written in 2015: “One notable side effect of header bidding adoption is that it puts pressure on Google’s DoubleClick for Publishers ad server, which, through its dynamic allocation feature, lets AdX — but no other exchange — see and bid on every impression.”
That sentence and general understandingand general understanding of what AdX did to manipulate the waterfall process nicely sums up where Google could face trouble in a courtroom. According to the lawsuit, publishers saw 30% to 40% more revenue through header bidding by simply removing Google’s ability to manipulate the waterfall auction. I bolded “general understanding” because Google is so powerful that the ad ecosystem knew full and well that it was using its monopoly in anticompetitive ways but there was nothing any publisher or advertiser could do about it.
Google has tens of thousands of engineers and is a very advanced company, which is why the allegations are quite complex. The lawsuit points out that Google then later manipulated header bidding by allowing AdX to bid last. As long as AdX beat the previous bids, then it would win the bid. Going back to the real estate agent scenario, this would be like having multiple offers on a house, and the listing agent going to their exclusive buyers to reveal what the prices are to help the buyers win the bidding war.
Google is also accused of using more acquisitions for ad technology that would later be leveraged to subsidize bids. This means Google paid the difference on an advertiser’s bid in order to be the winning bid. In this case, Google simply increased its margin or cut in order to make up for the amount that was subsidized.
Google’s DSP called DV360 was also allegedly engineered to decrease bids from competing ad exchanges, including those who were using header bidding for a more fair auction process. This was done by setting the highest competing bid at the floor price while AdX was able to bid higher.
Google is accused of suppressing header bidding through covert mechanisms by reducing header bids by up to 90%. Meanwhile, Google’s own DV360 bid was not decreased. This was done even when Publishers attempted to set a lower floor for competing ad exchanges, meaning, Publishers were without recourse even if they agreed to a lower bid.
Possible Outcomes
The outcome that many competing supply-side platforms (SSPs) and demand-side platforms (DSPs) are hoping for is the adoption of the Unified Ad ID 2.0 (UID2). There are many investors in The Trade Desk on our site, so this term is likely very familiar to our IOF Members.
The Unified Ad ID is essentially a replacement for cookies that uses email-based identifiers. There are a few hurdles here, such as users would have to opt-in and it brings up privacy issues to have ad exchanges passing a more persistent signal, such as anonymized IDs based on emails. What UID does solve for is any anticompetitive practices as there are many companies in the ecosystem that have signed on to support the open web initiative.
There are more companies than just The Trade Desk that would benefit if this happens – companies like Magnite, PubMatic, Microsoft/Xandr, to name a few.
To be clear, I’m not sure UID2 is realistic because of the privacy hurdles. The ad ecosystem may be “all-in”, but consumers are not likely to opt-in to having a persistent signal.
Another possible outcome is that Google Network is not broken up because what the company did was perhaps unethical but not anticompetitive since many corporations do something similar – which is mix first-party data with third-party data, and otherwise wield their large, corporate publisher dominance.
Instead, there could be regulations that force more transparency in the pricing structure. Or, perhaps Google has to choose a side in the transaction (publisher or advertiser) but cannot serve both.
It’s also possible that Google is not allowed to compete as a Search Engine across other verticals, such as flights, reviews, or dining reservations and must direct the traffic to web pages.
Companies that Challenge the Walled Garden
The ad ecosystem is quite large, although there are only a handful of public companies for us to discuss. Below is a view of the 2023 ecosystem per Publisher Management company Playwire. Most of these companies stand to benefit in some manner should Google be broken up or otherwise made weaker.
As stated, Google Network generated $32.8 billion in 2022. The DOJ is asking for divestiture ‘at minimum’ to divest the Google Ad Manager, including its publisher ad server (DFP) and the ad exchange (AdX).
In addition, the search engine is in the crosshairs for anti-competitive behavior, such as requiring mobile OEMs to make Google the default search engine. When Microsoft did this by requiring Microsoft Explorer to be the default browser across PCs, the behavior was found to be anti-competitive.
We believe the following companies stand to benefit:
Perion Network is partnered with Microsoft Bing. For this reason, the company is considered a beneficiary of Chat-GPT. If Google Search is forced to play fair, it’s likely Bing would see an incremental increase in its market share. In addition to this, Perion does not rely on cookies. As cookies are phased out, ETA around Jan 2024 (assuming no further delays), Perion will stand out in this regard, as well. Perion uses search intent insights to create audiences or “SmartGroups” for targeting purposes. Perion can help any search function, so imagine the search you might perform on Pinterest or Expedia. This is unique because search intent is often a superior signal compared to other forms of behavioral targeting.
The Trade Desk sits on the demand side and is in direct competition with Google’s DSP. If Google has been strongarming publishers into using its exchange for ads, per the allegations noted above, then breaking this up would be an immediate tailwind to The Trade Desk. Essentially, Google is penalizing publishers in various ways if they use another DSP.
If it becomes a more equitable ecosystem, to where publishers are rewarded equally no matter which DSP they use, then The Trade Desk will be able to fairly compete with Google on their publisher inventory. This assumes that Google will be able to keep the supply side ad machine it acquired from DoubleClick for Publishers. Clearly, The Trade Desk has done well in a walled garden environment despite all odds. It’s reasonable to assume The Trade Desk will do better if those walled gardens become weaker.
Notably, as stated above, The Trade Desk has two hurdles – the second one being the elimination of cookies and IDs. This is a separate issue entirely and does not relate to the antitrust case, it just happens to be timed to where the antitrust case is in 2023 and cookies will be phased out in 2024.
The goal is for Unified ID to be accepted as part of the open web, but there are privacy hurdles here that don’t relate to anticompetitive practices. In 2021, 96% of iOS users opted-out of tracking. The same can happen to UID 2.0. In other words, Google could be broken up but this may not do much for allowing the demand-side to access third-party IDs for attribution and measurement.
Magnite and PubMatic compete with Google on the supply side. Publishers have an outsized advantage when they use Google on the publisher side as the company mixes its first party data with third party data to drive the industry’s best targeting. Similar to Meta’s Audience Network covered here, it’s nearly impossible to compete as a SSP when a publisher of Google’s magnitude combines its data and brokers for a pool of publishers.
If this is broken up, then those who specialize on the publisher side — while also not directly competing with publishers — stand to benefit. Because Google is the largest publisher in the world while also competing with smaller publishers for ad inventory, it seems a likely outcome will be the breakup of the SSP side, at the very least.
The hurdle the SSP side must clear is that many corporations do this – with that said, Google is by far the largest offender due to its commanding properties of Android, Chrome, Search and YouTube. It’s also not clear if the other corporations (Comcast, Disney, etc.) have leveraged their position to penalize publishers who use other SSPs.
Ad-Tech Fundamentals
Below, we go into brief overviews of each company’s financials. The goal of combing over these companies during a lull in earnings is to accomplish a few things. First, to acknowledge that this antitrust lawsuit should not be overlooked. The ramifications could be quite advantageous to a few small cap companies. Secondly, to cautiously watch the charts ahead of the trial. We don’t want to front run but we also don’t want to be complacent. Third, is to understand Google a bit more. In the avalanche of Chat-GPT coverage, we want to be realistic about a potential position in Google, and look at the brass tacks of this important lawsuit.
Ultimately, I believe the outcome of the antitrust lawsuit is more important than the hype of the chatbots in the near term – that goes for both Google Search and Bing. AI chatbots are great for early adopters but search engines serve the masses. In addition to this, considering Google Network is worth $32 billion, and we have some small caps that could stand to benefit, we want to be prepared if there is a favorable outcome for the smaller players.
Perion Network
Perion Network is a digital advertising company headquartered in Holon, Israel. The company offers digital solutions in three primary channels of digital advertising: ad search, social media, and display/video/CTV advertising.
Perion helps brands and publishers to identify and reach customers through the company’s proprietary Intelligent HUB (iHub), which processes billions of signals, and powers the cookieless solution SORT. By mixing contextual data with user insights, Perion is able to forego cookies by using this data with AI-based clustering techniques. SORT stands for Smart Optimization of Responsive Traits, which translates to categorizing customers into 1 of 30 Smart Groups through shared traits.
The primary sources of data are contextual – so what a customer is reading at the moment, why they’re reading it, how long they’re reading it and/or what search words brought them to the content. This is combined with signals such as time of day, weather, browser, device, etc. Ultimately, what Perion’s technology does is calculates the similarities between groups, and then to target the group that performs the highest in terms of converting. The model is deemed effective when one group has a significantly higher click-through-rate (CTR).
Second, SORT then optimizes the bids so that it’s a cost-effective solution. SORT analyzes the bid of each publisher and selects the price that is likely to win. If the price is too high, SORT finds another publisher with a similar audience as the SmartGroup. The entire process happens in real-time.
Doron Gerstel, CEO of the company, said in the Q2 2022 earnings call, “iHub sits in the center of the supply and the demand side of the market. This is an innovative model that no one else in the industry has, aggregate data signals from all channels and from both sides of the open web to create the model that eliminates waste and rewards clients. The data goes into Perion’s privacy first cookieless solution known as SORT.”
This is important because cookies are expected to be phased out from Chrome in 2024. Cookies have already been phased out by Mozilla Firefox and Apple Safari.
In addition to this, Perion has partnered with Microsoft Bing. CodeFuel is the Perion product that powers intent-based monetization. When you go to search for something on a search engine, Perion’s CodeFuel can power the search results in an optimal way for conversion. This has led to a strategic partnership between Microsoft and Perion that was renewed in 2020 for four years.
Per the recent earnings call, “If the new Bing search with ChatGPT sparks even modest share gains, Microsoft can do very well in the business. As their CFO, Amy Hood said yesterday, every percentage point of share it gains in search equals roughly $2 billion in additional advertising revenue, and as a strategic partner of Microsoft Bing, I’m sure we will be benefiting from this increase.”I’m sure we will be benefiting from this increase.”
Notably, there is a risk that Microsoft does not renew its partnership next year. However, this risk is muted a bit since Perion was named “Global Supply Partner of the Year” by Microsoft in 2022.
What’s interesting about Perion is that the company is fundamentally one of the strongest ad-tech companies on the public markets due to a strong bottom line and a top line that was more resilient than its peers. Any windfall here could very interesting for a company that already proven operational efficiency with a 20% operating margin while maintaining 30%+ growth in the tough year of 2022. Notably, the top line is decelerating but a catalyst that could lead to a reversal here could be quite interesting
The company’s revenue in the recent quarter grew by 33% YoY to $209.7 million. Display advertising revenue grew 24% YoY to $123.8 million and search advertising revenue grew 49% YoY to $85.9 million. The company had an operating margin of 20% compared to 13% in the same period last year.
The company is GAAP profitable, and margins are improving. The net profit margin improved to 18% from 11% in the same period last year. The adjusted EBITDA margin was 23% compared to 18% in the same period last year.
Source: Company IR
The company has free cash flow of $37.90 million representing a free cash flow margin of 18%. Perion had cash and bank deposits of $429.6 million and no debt at the end of December 2022.
Revenue growth is expected to slow, as seen below. The company’s revenue grew above 30% in all four quarters in 2022, and it grew 34% YoY to $640.3 million for the full year of 2022. This is expected to level off quite a bit, presumably due to industry-wide headwinds.
Source: Seeking Alpha
Magnite
Magnite is another ad-tech company that is a potential beneficiary. Magnite is a sell-side platform (SSP) that offers exposure to a higher mix of CTV ads from an independent SSP than what is currently on the market.
We previously discussed Magnite is both an ad server and a Supply Side Platform. Strategically, this allows Magnite to compete with FreeWheel and Google and helps them maintain their position “as the largest independent programmatic CTV marketplace.” The SSP allows for programmatic and private market place bidding while the ad server stores the creatives and serves the ads. The SSP facilitates the selling/bidding (auction) while the ad server actually manages, stores and serves the ads. SpringServe is ad server that Magnite acquired for $31 million. The acquisition came from SpotX’s option to buy.
In their recent earnings call, the management highlighted that Disney has renewed their agreement to use Magnite as Disney’s global programmatic SSP partner. “As you may recall, our relationship with them started with Hulu. We have since grown the relationship to include the full portfolio of Disney properties.”
The company’s Q4 2022 revenue ex-TAC grew by 10% YoY to $156.6 million. The operating margin was (16%) compared to +2% in the same period last year.
Net losses are increasing to ($36.4) million with a net margin of (21%). This compares to $453,000 in net profit for a flat net margin in the year-ago quarter.
The company reported GAAP EPS of ($0.27) compared to GAAP EPS estimates of $0.02. The adjusted EPS also missed at $0.24 versus $0.32 expected.
Our recent analysis discussed that the company missed on the bottom line due to the new CTV ad platform that was launched in February. The newly launched Magnite Streaming is a single supply-side platform that merges the technology from Magnite CTV and SpotX platform. Magnite Streaming led to a $35 million accelerated amortization.
Cash flow was the strongest line item in Magnite’s report. Free cash flow margin was 28% compared to 34% in the year-ago quarter. The company has $326.3 million in cash on the balance sheet with $726.4 million in debt for net debt of $400.1 million.
Below are the analyst’s ex-TAC revenue estimates. Magnite’s revenue is also decelerating.
Source: Seeking Alpha
PubMatic
PubMatic is another sell-side platform that is a potential beneficiary. The company works with over 1,600 publishers. In the recent earnings call, the management highlighted new partnerships with Roku, TiVo, and Kroger.
Rajeev Goel, CEO and co-founder, pointed out that the company has increased its market share from 2-3% at time of IPO in Dec 2020, “We ended 2022 with an estimated market share of 4% to 4.5%, significantly up from when we went public just over two years ago. We are well on our way to our stated goal from the time of our IPO of 20% market share, and we intend to use the downturn to further accelerate our gains.”
The CEO pointed out that Google’s antitrust case could help them achieve the (lofty) 20% goal: “Advertisers and publishers continue to seek alternatives to the walled gardens. This tailwind, along with structural changes, including ongoing antitrust activities, will only expand our total addressable market as an independent technology provider.”
The company’s revenue in the recent quarter declined by (1.7)% YoY to $74.3 million. The operating margin was 22% compared to 37% in the same period last year. The drop in revenue led to lower margins when we compare it to the year-ago quarter. However, the Q4 operating margin was the highest for the year 2022. Net margin was 17% compared to 37% in the same period last year.
The free cash flow in the recent quarter was $7.02 million, with a free cash flow margin of 9% compared to a free cash flow of $18.72 with a free cash flow margin of 25% in the year-ago quarter. The company has cash and marketable securities of $174.4 million with no debt. The analysts expect revenue to decline in the next two quarters. In the earnings call, management was cautious about the macro environment.
Source: Seeking Alpha
The Trade Desk
The Trade Desk is an independent demand side ad platform. We discussed the Universal ID in August 2019. “Strong drivers for The Trade Desk include omnichannel capabilities, which is the ability to buy ads across many channels, such as mobile, video, audio, display, social and native. The universal ad ID is another important differentiation as it offers an anonymized ID that helps track users, target audiences and provide attribution.”
The Trade Desk has benefitted from its omnichannel approach that also focuses on CTV. Jeff Green, CEO and founder of the company, said in the recent earnings call. “CTV continued to be our strongest growth driver as more content owners from around the world are moving beyond ad-free subscription models and offering ad-supported options for viewers.”
Jeff Green mentioned in fourth quarter last year, about 15% of the Trade Desk’s third-party data had UID2 associated with it and expects it to be in the 75% range in the first half of this year. “In fact, I would say again that it becomes about 10x more valuable than with cookies, simply because UID2 solves the needle in the haystack problem that came with cookies, because advertisers can now match their customer data with accuracy across the open Internet more effectively than ever before.”
Jeff Green also sounded confident in the earnings call that the outcome of the DoJ will benefit the company. “I know there is some at Google who tried to suggest that we have been through this three or four times before. I do believe that this is fundamentally different. And part of that is just because of how detailed I think the case is outlined.”
The Trade Desk has illustrated a strong bottom line despite a tough 2022. The company’s Q4 revenue grew by 24% YoY to $491 million. The operating margin was 20% compared to (6%) in the same period last year. The net margin was 15% compared to 2% in the same period last year. The adjusted EBITDA margin was 50% compared to 48% in the same period last year.
The company has free cash flow of $123 million with a free cash flow margin of 25% compared to $151 million compared to a free cash flow margin of 38% in the year-ago quarter. The company had cash and short-term investments of $1.4 billion with no debt.
Below are analyst revenue estimates for the next few quarters. Analysts expect the revenue of the company to grow faster when compared to the other ad-tech companies we covered, and the company also has a premium valuation.
Source: Seeking Alpha
The Trade Desk has a forward P/S ratio of 15.14 compared to 2.53 for PubMatic, 2.47 for Magnite, and 2.22 for Perion Network.
Given the sheer impact a weaker Google could have on the ad-tech ecosystem, we wanted to do a deep dive and get in front of this. Most of the names listed are familiar to our Members, yet these names may be seeing the biggest catalyst in their respective company’s history. This will depend on outcome of the antitrust lawsuit and the severity of the DOJ’s actions.
Perhaps the opposite will happen. Perhaps Google’s deep pocketbooks will provide top tier lawyers who can defend the case accordingly. As investors, it’s not our job to take sides but to find where ad dollars may be flowing next.
Ultimately, I believe this is the number one catalyst across ad-tech this year and we want our readers to benefit no matter the outcome. As the market can often do, there may be some price movements ahead of the trial, and if so, we will be watching for entries closely.
It may feel like the words “Google” and “lawsuit” are commonplace, but the trial in September carries enormous weight and is unlike the lawsuits of the past. Not only do we want to keep an eye on ad-tech names that could benefit should Google’s monopoly be broken up and the juggernaut come out weaker, but we also want to be prepared if the tech giant is able to hold off regulators.
Considering that Google is sitting on the world’s very best consumer data, which is not an exaggeration in the least bit, its ability to lead on artificial intelligence and large language models should not be underestimated. For our purposes, the company is far from sitting on its laurels and there’s a predictable path where the company competes in a duopoly with Microsoft.
Therein lies the issue. Google undisputedly has the world’s best consumer data, but did this grow to become part and parcel with operating a monopoly? The Department of Justice has asserted anti-trust violations against Google with the trial beginning in September 2023. The trial is expected to last ten to 12 weeks, although a lawyer for the DOJ told CNBC it could be as brief as five weeks.
Why it matters:
With Google and other ad-tech companies trading this low, one of two outcomes will happen. The antitrust outcome will be mild, and Google will be empowered to continue to dominate. Or, the outcome will require the ad properties to be broken up, leading to a weaker stance for Google. This could benefit smaller ad-tech players.
The Goal — Looking back:
A few years back, I analyzed the potential outcome of a government decision when the Pentagon was evaluating cloud providers. Clearly, this decision is far outside of anyone’s control and requires some speculation. At the time, I speculated Azure would be a winner. For a year or so, Microsoft did secure the Pentagon contract over the more-favored Amazon. This decision was ultimately reversed, and the contract was split between four tech companies.
The exact outcome of the Pentagon contract was not particularly important because the analysis led to my conclusion that Microsoft’s hybrid computing was a material advantage and this would be the path Nadella would most likely use to take market share from AWS’s heavily-slanted public cloud strategy.
I’m hoping for something similar, which is to acknowledge something very important is going on with ad-tech, which is Google’s antitrust case. This is not a headline to simply dismiss. It’s the first time the DOJ has brought a case of this kind against a technology company since Microsoft. If there are even minor cracks in Google’s monopoly, there could stand to be a stock or two that starts a new trajectory.
On similar note, Cambridge Analytica is what sparked my coverage on Facebook. Similar to Google’s antitrust case, it became apparent to me that Facebook was peaking in terms of its ability to monetize through third party data. I covered this extensively, for example here and here.
Brief Overview of Antitrust Case:
According to Lanier Law Firm, which is the litigation team for the State of Texas in the state coalition case, a primary argument against Google is that the company went above and beyond to become the default search engine on iOS devices by paying Apple $12 billion per year.
The lawsuit includes other deals that Google struck with Apple’s Safari browser, the Mozilla browser and Android device manufacturers where Google either paid up or imposed restrictions on Android device makers to strongarm having their suite of apps pre-installed on the home screen.
The company has already lost an antitrust case in Europe in 2018 with a $4.4 billion Euro fine for forcing Android manufacturers to pre-install Google’s bundle of apps on the device, including Chrome, Maps and the Play Store.
Google’s market share of Search is at 91% and the argument is being made this was accomplished through anti-competitive practices, especially since Google owns Android and had leverage over the many device makers that used this operating system.
In addition to being pre-installed and the default browser/search engine, Google also attempts to keep people on its search engine by using a website’s data on its page. For example, if you look up “Best Dog Breed” Google scrapes Wikipedia and puts the results onto the search page instead of sending you to Wikipedia. This is seen as anti-competitive as it takes a website’s data to profit from it, rather than directing the traffic to the rightful copyright owner, which is the function of a search engine.
Part of Microsoft’s antitrust case was based on Microsoft using its dominance on Windows to force a Microsoft Explorer to be the default browser. At the time, the decision was that default settings are anticompetitive.
The secondary argument filed by a 10-state group led by Texas, is that Google leverages its properties to be the buyer and the seller via its ad exchange. Per Lanier Law Firm, the Texas case states Google and Facebook “unreasonably restrained trade and harmed competition through an unlawful agreement to allocate auction wins and to fix prices in violation of Section 1 of the Sherman Act, 15 U.S.C. § 1”
This is where it gets very messy, and so I’ve dedicated a specific section below to break down these details. The purpose of understanding the minutiae is not to only determine if we should buy Google and when, but also what companies could stand to benefit if Google’s products are shutdown or broken up.
My long-ago analysis on Facebook pointed toward a conflict of interest in the company owning a third-party ad network called Audience Network while also being publisher. At the very least, the conflict of interest created a risk since Facebook was essentially siphoning oil from real estate the company didn’t own (iOS users). This was a serious, material risk for investors that played out over time (note: it certainly wasn’t immediate, it took four years from the first time I covered the topic).
If you’re a Meta investor, you’ll want to watch the CPMs on the company and make sure the erosion below is not permanent. Despite Apple only impacting third-party data, it’s unclear how much of that third-party data was informing its first party data. The unusually high CPMs that Meta charged points towards enhanced targeting – that in my opinion – was likely due to mixing both first-party data with third-party data. This means there will be an eventual erosion, over time, of the CPMs Facebook can charge even on its own applications.
Pictured above: Although subtle, there is an erosion to Facebook’s otherwise high CPMs. You can see that Nov 2022 made a lower high over Black Friday compared to the two previous years. Many factors could be at play, such as lower ad budgets, but it’s something investors should keep a close eye on.
Google currently does the same thing that Facebook used to do, which is to run an ad exchange that is undeniably a conflict of interest. The difference is that rather than renting real estate, like Facebook did with iOS, Google is a real estate tycoon. There isn’t a tech company that can kick Google off their turf because Google owns all of the turf – primarily Chrome, Android, Google Search, and YouTube.cBy conflict of interest, I’m referring to AdX, DoubleClick and DV360, collectively known as the Google Network.
Below, you can see Google Network is a $32 billion annual revenue stream. Not exactly peanuts.
To further the lawsuit, a 30-state coalition has issued a third claim that Google uses its monopoly to rip off smaller companies, such as Yelp, DoorDash, and Kayak. You can see evidence of this when Google Search returns flight searches powered by Google at the top, with a large embedded format, rather than producing a fair search result that includes competitors. Yelp has been in a battle with Google over this for over a decade. After Google Reviews were launched, Google pushed Yelp down the page in terms of search results.
The two search engine allegations are fairly straight forward. Most of us who use Google Search can reasonably understand those arguments.
The Messy, Blackbox that is AdExchange (AdX):
DoubleClick was acquired in 2007 for $3.1 billion. As author Tony Yiu points out on Toward Data Science, this was twice the amount paid for YouTube a year earlier. Google Network is a by-product of many acquisitions including AdMob for $750 million and AdMeld for $400 million, among others, yet DoubleClick truly set the supply side dominance in motion as the company owned 60% of the desktop publisher market at the time of acquisition.
DoubleClick allows Google to set a cookie on a website so that online publishers can better target visitors with ads. The DoubleClick cookie provides the time and date a user saw an advertisement, as well as a unique ID that identifies a user by their browser. Publishers are then able to auction inventory to advertisers.
DoubleClick was a major move by Google to expand beyond search advertising. This was the first time Google entered the market on display ads. As stated, DoubleClick owned 60% of the publisher market when it was acquired, which means Google would eventually profit from monetizing millions of websites.
This led to a concentration of power for Google, because with this advantage, it was able to grow quickly as a predominant ad server for publishers. Naturally, Google wanted to maximize this advantage, and so the company made the appropriate acquisitions to operate on the demand side (advertiser side) in addition to the publisher side.
Through a series of acquisitions, Google built DV360, which allows advertisers to use their own data to target customers across publisher inventory. Google always has strong ties to data, in this case powering DV360 with Google Analytics 360. In addition to this, Google’s AdX allows advertisers to create campaigns across Google-owned properties in addition to millions of websites from third-party publishers on the DoubleClick publisher side, as mentioned above.
An easy analogy here would be to compare it to a real estate transaction, since ads are transactional between a buyer and seller. In this case, Google was representing both the buyer and the seller, and in some cases brokered its own real estate to the buyers. You can imagine due to Google’s scale of doing millions of transactions a day, things might get unethical real quick.
Here’s how a Google executive put it:
“[I]s there a deeper issue with us owning the platform, the exchange, and a huge network?” the executive allegedly asked. “The analogy would be if Goldman or Citibank owned the NYSE.”
With that in mind, let’s continue because the depth of Google’s black box is quite deep.
The product AdSense further pools the data provided by publishers. When millions of websites join AdSense to pool data, Google can record more information on a person’s browsing history. It provides a complete view of the consumer for more enhanced targeting. Another area that Google allegedly monopolizes the market is that the company mixes its first party data with this third party data, but only in instances where Google will benefit.
The AdMob acquisition in 2009 provided a similar strategy as DoubleClick but on mobile. It deepened Google’s reach on the supply side for the mobile market. This, of course, was especially advantageous considering Google bought Android in 2005.
You can imagine, that the depth of Google’s data on desktop users and mobile users is deep (and likely quite dark). Meaning, Google knows more about you than you know about yourself. Now, take that depth of data and add the serious conflict of interest that can occur when Google bids against competitors.
Where Google (Allegedly) Went Wrong with AdX
Despite the allegations below that Google was unethical, I want to point out that antitrust could be harder to prove for AdX. This is because many corporations combine first-party publisher data with a third-party ad exchange, such as Amazon, Facebook, Disney and Comcast. Microsoft is building its ad exchange, as well right now, after acquiring Xandr from AT&T. However, Xandr/Microsoft’s strategy is to support the “free and open web” by adopting the Unified ID.
Point being, if the product AdX is found to be anticompetitive, it could have far-reaching implications for other companies. This wasn’t the case with Microsoft, as the company was rather isolated on its throne in the late 90s. With that said, Google is the worst offender in terms of the sheer advantages it has compared to other corporations with large media properties.
Here are some of the more unethical things Google is being accused of:
According to the lawsuit, there was a 65% drop in revenue if publishers chose to not use Google on the demand side. Advertisers are also stating this was a conflict of interest as Google restricted inventory in this case. This would be like a real estate agent refusing to show a house if they did not have both the buyer and the seller to double-end the transaction.
Google also allegedly circumvented waterfall auctions to prioritize their own bids on AdX. Waterfalls were prevalent throughout the ecosystem because they allow exchanges to be ranked by bids. Based on historical bids, if the ad exchange in the number one position doesn’t buy the inventory, it goes to the next ad exchange in the waterfall (the number two position).
Where Google may have manipulated the bidding is by allowing their exchange to meet only floor prices to win the bid, even when another exchange would have bidded higher in a waterfall-like auction. This would be like a real estate agent only presenting their Buyer’s offer to a Seller even if they knew they could get higher offers from another agent.
Due to DoubleClick and AdX waterfalls having the issues described above, programmatic header bidding was introduced to offer true, real-time bidding to increase publisher yield. It essentially increased competition by holding an open auction rather than a closed, blackbox auction that pushes inventory back and forth in an attempt to sell the inventory.
Per Digiday written in 2015: “One notable side effect of header bidding adoption is that it puts pressure on Google’s DoubleClick for Publishers ad server, which, through its dynamic allocation feature, lets AdX — but no other exchange — see and bid on every impression.”
That sentence and general understandingand general understanding of what AdX did to manipulate the waterfall process nicely sums up where Google could face trouble in a courtroom. According to the lawsuit, publishers saw 30% to 40% more revenue through header bidding by simply removing Google’s ability to manipulate the waterfall auction. I bolded “general understanding” because Google is so powerful that the ad ecosystem knew full and well that it was using its monopoly in anticompetitive ways but there was nothing any publisher or advertiser could do about it.
Google has tens of thousands of engineers and is a very advanced company, which is why the allegations are quite complex. The lawsuit points out that Google then later manipulated header bidding by allowing AdX to bid last. As long as AdX beat the previous bids, then it would win the bid. Going back to the real estate agent scenario, this would be like having multiple offers on a house, and the listing agent going to their exclusive buyers to reveal what the prices are to help the buyers win the bidding war.
Google is also accused of using more acquisitions for ad technology that would later be leveraged to subsidize bids. This means Google paid the difference on an advertiser’s bid in order to be the winning bid. In this case, Google simply increased its margin or cut in order to make up for the amount that was subsidized.
Google’s DSP called DV360 was also allegedly engineered to decrease bids from competing ad exchanges, including those who were using header bidding for a more fair auction process. This was done by setting the highest competing bid at the floor price while AdX was able to bid higher.
Google is accused of suppressing header bidding through covert mechanisms by reducing header bids by up to 90%. Meanwhile, Google’s own DV360 bid was not decreased. This was done even when Publishers attempted to set a lower floor for competing ad exchanges, meaning, Publishers were without recourse even if they agreed to a lower bid.
Conclusion:
Given the sheer impact a weaker Google could have on the ad-tech ecosystem, we wanted to do a deep dive and get in front of this. I believe this is the number one catalyst across ad-tech this year and we want our readers to benefit no matter the outcome. As the market can often do, there may be some price movements ahead of the trial, and if so, we will be watching for entries closely.
We offer an Advanced service with specific stock picks that may benefit from Google’s lawsuit and we also offer real-time trade alerts for all of our portfolio entries and exits. You can learn more about this service here.about this service here.
This article was originally published on Forbes on Feb 17, 2023,01:18am ESTForbes on Feb 17, 2023,01:18am EST
Earlier this month, Google’s stock (Alphabet) tumbled 7% when chatbot Bard was unable to complete a search with 100% accuracy. During a demonstration, Bard returned incorrect information about which telescope was the first to take pictures of a planet outside the Earth’s solar system. This was a minor mistake given how far large language models and generative AI has come, rather it was the timing that was a bit flawed as OpenAI’s ChatGPT, the chatbot powering competitor Microsoft Bing, had been dominating headlines since its November 30th launch.
Microsoft, being an opportunist, took it a step further and announced Bing would now be powered by a faster and more accurate version of GPT-3.5 one day after Bard’s failed demonstration: “We’re excited to announce the new Bing is running on a new, next-generation OpenAI large language model that is more powerful than ChatGPT and customized specifically for search. It takes key learnings and advancements from ChatGPT and GPT-3.5 – and it is even faster, more accurate and more capable.”
Both companies have been preparing for this moment for many years. Microsoft invested $1 billion into OpenAI a few years ago with a new $10 billion round announced last month. Meanwhile, Google acquired DeepMind in 2014. Google also previously developed conversational neural language models such as LaMDA, which is used by Google’s Bard for its conversational AI technology.
As much fun as the media has had lately poking fun of Bard, there have been similar, compelling reports of ChatGPT-powered Bing also having accuracy issues.
Point being, both are in the early stages and mistakes are being blown out of proportion. Which brings up more important questions for investors – given that technology can require many iterations, what’s the right timing for generative AI and chatbots to drive real advertising revenue?
Investors can get burned by being too early. For example, autonomous vehicles (AVs) were promised in 2019, and the Metaverse has not driven any real gains despite a large media push in early 2021. How does AI compare in terms of time to market?
Secondly, Alphabet has a lot of turf to defend. It won’t only be Bing, but also browsers like Opera that will incorporate ChatGPT into its sidebar. From there, it’s easy to imagine other competitors may crop up over time, some replacing search engines entirely with conversational AI applications powered by speech recognition, which are otherwise unimaginable today.
We look at these key points below for a 360-degree view on Google’s stock given search is on the precipice of its first major shift in over two decades.
Background on AI-Powered Search
“AI is the most profound technology we are working on today. Our talented researchers, infrastructure and technology make us extremely well positioned, as AI reaches an inflection point.” -Sundar Pichai, Alphabet’s Q4 earnings call.Q4 earnings call.
Despite the mishap with Bard, it would be a human-generated mistake to think Alphabet does not command a place of leadership right now in generative AI. Alphabet was one of the first tech companies to focus and invest on AI and natural language processing (NLP). We pointed out to our premium research members in July of 2022 that ChatGPT is based on transformer architecture that Google initially introduced in 2017 when we saidpremium research members in July of 2022 that ChatGPT is based on transformer architecture that Google initially introduced in 2017 when we said:
“Transformers are becoming one of the most popular neural-network models by applying self-attention to detect how data elements in a series influence and depend on one another.
Sequential text, images and video data are used for self-supervised learning and pattern recognition, which results in more data being used to create better models. Prior to transformer models, labeled datasets had to be used to train neural networks.
Transformer models eliminate this need by finding patterns between elements mathematically, which substantially opens up what datasets can be used and how quickly.
Google first introduced transformer models in 2017 and transformers are used in Google and Bing Search. Transformers also led to BERT models, which stands for Bidirectional Encoder Representations from Transformers, and is commonly used for text sequences. Transformers are also used in GPT-3 (it’s the T in GPT) which improved from 1.5 billion parameters to 175 billion parameters. GPT-3 has the ability to report on queries it has not been specifically trained on.”
Earlier this month, Google’s CEO, Sundar Pichai, gently reminded the AI community of how cutting edge Google’s research is when he stated, “Transformer research project and our field-defining paper in 2017, as well as our important advances in diffusion models, are now the basis of many of the generative AI applications you're starting to see today.”
BERT was designed to help Google better understand search intent, as despite billions of searches every day, about 15% of those searches are for brand new terms. This prompted Google engineers to develop a model that could self-learn.
The result is that searches results are more accurate by taking into consideration the nuances of language.
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Multitask Unified Models (MUMs) are 1,000X More Powerful than BERT
Multitask Unified Models (MUM) were introduced in 2021 to further address conversational nuances and is 1,000 times more powerful than BERT. MUMs will have a large impact for search users as it decreases the amount of effort put into seeking the desired information. It’s not only addressing the 15% of search based on new terms, rather it’s a powerful iteration that returns search results that more closely resemble how humans interact.
According to Google, it takes an average of eight queries to answer a complex question. With MUM, this is reduced to one query. You can theoretically ask “should I travel to Hawaii or California this Fall?” and MUM will be able to compare travel rates and weather patterns to answer this question with more depth. Similar to if you ask your friend this question, they might answer “Hawaii is more expensive to travel to but California is prone to wildfires in the Fall, so I would go to Hawaii.” To search for this answer would take many queries, but with MUM, succinct, human-like responses are provided in only one interaction.
Large language models have been helping to improve search results for many years. Therein, Google presents its moat; which is not only a deeply engrained behaviour pattern where search users automatically turn to the multi-decade leader out of pure habit, but that Google search truly presents the highest quality search results today.
Google’s commanding lead on search is not a legacy metric, by any means, rather it symbolizes the lead Google has on data for training large language models.
Bard’s demonstration may have been problematic compared to Chat-GPTs more favorable reviews, however, it’s nothing more than that for now —- which is a mix of bad reviews and good reviews by a limited number of beta users.
TPUs:
This brings us to Google’s TPUs, which are essentially ASICs (application specific integrated circuit) on the efficiency/flexibility spectrum. I first covered the differences between TPUs and GPUs nearly four years ago in 2019 for our premium members when I said:first covered the differences between TPUs and GPUs nearly four years ago in 2019 for our premium members when I said:
“TensorFlow is rising in popularity as a machine learning framework and TPUs primarily run TensorFlow models. This is one of Google’s more successful experiments. They are cheaper and use less power than GPUs and are specifically focused on machine learning.
TPUs train and run machine learning models and power Google Translate, Photos, Search, Assistant and Gmail – i.e., image recognition, language translation, speech recognition and image generation.”
Although there are ongoing debates between TPUs and GPUs, the primary difference is that TPUs are application specific and have been optimized for Google’s AI tools. Meanwhile, Nvidia was the first to break ground in deep learning due to the ease of programming GPUs and the relative speed in which parallel computing can train networks. Nvidia also offers its customers an aggressive product road map.
An example of this is the H100 DGX SuperPods, which we covered for our premium members in July when we said:
“Nvidia and Microsoft recently worked on a Mega transformer model with 530 billion parameters and the future for AI engineers is trillion-parameter transformers and applications. The H100 is already prepping for this. According to Nvidia, the training needs for transformer models will increase 275-fold every two years compared to 8-fold for other models. The H100 GPU with its Transformer Engine supports the FP8 format to speed up training to support trillion-parameter models. This leads to transformer models that go from taking 5 days to train to becoming 6X faster to only taking 19 hours to train.”
As of today, TPUs do not necessarily provide Google an advantage over Microsoft’s partnership with Nvidia. When TPUs were first launched, it was expected that it would provide Google an important lead in launches such as Bard. However, Nvidia has proven to be a more difficult competitor than originally expected, and I imagine Microsoft will not stray from this partnership as the company will instead focus on other areas, such as taking more market share with Bing.
Introduction of Bard powered by LaMDA
LaMDA is a conversational language model that powers Bard. Two years ago, Google launched LaMDA to better mimic open-ended conversations by training the language model on dialogue. The result was a more human-like chatbot that personally knows you well enough to recommend movies or books, is sensitive enough to change an uncomfortable conversation, can discuss its own “death” by being turned off, —- and also has machine vision to where it can look at a picture and discuss the picture intelligibly.
Bard was released this month for beta testers and will be available to the public “in the coming weeks.” As mentioned in the introduction, Bard answers questions with real-time data whereas ChatGPT is trained on data from 2021 or earlier (note: the new Bing version is rumoured to use real-time data, see below).
Bard is also free, and given Google’s search revenue, the company may have incentives to undercut competitors that charge paid plans for conversational AI.
Other ChatGPT alternatives
Anthropic is building a 52-billion-parameter pretrained model called Claude, which is a potential rival to ChatGPT. Google invested $300 million into Anthropic last year, with a similar arrangement as Microsoft and OpenAI, which includes a stake in the R&D of the startup. Anthropic was founded by former employees of OpenAI. Whether Claude can actually exceed Google’s own language systems is yet to be determined, or perhaps Google is simply spreading its bets and wanting access to its competitors’ former talent. Despite being in closed beta, there’s an excellent write-up here about the differences between ChatGPT and Claude.
DeepMind is also not to be underestimated. Google’s sister company is behind many of Google’s AI product integrations to-date. In September of 2022, DeepMind introduced Sparrow which is trained with human feedback, similar to ChatGPT, but will use up-to-date information from a Google-powered internet. DeepMind’s previous release, Chinchilla, was competitive with ChatGPT 3.0 before the more advanced ChatGPT 3.5 was released.
There are many other large language models, such as Google’s PaLM and Microsoft’s Megatron, in the 530 to 540 billion parameters size and also based on Transformer architecture.
Notably, this is not meant to be a comprehensive list rather a sample of the level of innovation occuring in this space.
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AI to Drive Advertising Revenues
The strength in Search highlights the advantage that having first-party data provides. The company had global desktop market share of 84% in online Search at the end of December 2022, according to data from Statista. Desktop share dropped slightly from 88% at the end of December 2015 to 84% at the end of December 2022. Meanwhile, Microsoft’s Bing share increased from 5% to 9% during this period.
Source: Statista
According to data from Statista, YouTube has 2.5 billion monthly active users. It ranks second behind Facebook which has 2.96 billion monthly active users.
Source: Statista
According to the data from Nielsen, the company also has a leadership position in streaming in the U.S. For the month of December 2022, YouTube (including YouTube TV) accounted for 8.7% of TV usage, followed by Netflix with 7.5% and Hulu with 3.4%. With AI, the company is helping advertisers address pain points like frequency and measurement.
Source: Nielsen
Android has a dominant market share in Mobile Operating Systems. As per the datafrom Statcounter, Android accounted for 71.8% share compared to 27.6% for Apple iOS at the end of Q4 2022. The share for Android has come down marginally from 74.5% in Q1 2018.
Source: STATCOUNTER
This vast amount of first-party data from Chrome and Android can be efficiently used to train complex AI models. A few years ago, I accurately predicted Apple’s IDFA changes would cause problems for advertising companies in an editorial for Forbes:
This is a problem for the ad industry because it goes well beyond personal sentiments and niceties around privacy and slow-moving government regulations and pits tech giant against tech giant in the black box world of ad software, user tracking and engineered loop holes. There is little question who will win as Apple goes up against Google, Facebook and many others. After all, it’s Apple’s device, Apple’s operating system and Apple’s app store. The only question is why this hasn’t happened sooner.
Similarly, Google is a large real estate owner with arguably more data than any other tech company in the world. This advantage cannot be overstated when it comes to training large language models (LLMs). In addition to having a strategic advantage for future development of LLMs with data, Google can offer advertisers instant ROI.
Philipp Schindler, Senior Vice President and Chief Business Officer said in the earnings call, “Going forward, we are focused on growing revenues on top of this higher base through AI-driven innovation.”
This will be accomplished with AI campaigns, such as Performance Max and Smart Bidding. Smart Bidding uses machine learning tools to optimize the bid of the advertisers. ML tools can analyze millions of data signals and can better predict future ad conversions. The further advancement in AI helped to improve the bidding performance in 2022.
Performance Max will replace Smart Shopping Campaigns. Performance Max allows advertisers to access all Google ad channels from a single campaign and uses Smart Bidding to optimize performance by efficiently matching the conversion goals of the advertisers. Advertisers saw a 12% increase in conversion value with Performance Max when compared to Smart Shopping Campaigns. This is a drop in the bucket in terms of what’s likely to follow over the next few years in terms of better ad tools.
Financials
Alphabet’s current revenue growth is one of the lowest in its public history. Last quarter, revenue grew by 1% to $76.05 billion and on constant currency basis grew by 7%. Next quarter, analysts expect revenue to grow 1.1% to $68.78 billion in Q1 2023. From there, the revenue growth is expected to gradually increase.
Google Search revenue was negative (1.6%) YoY to $42.6 billion and YouTube ads revenue was negative (7.8%) YoY on the back of the tough macro environment. Per the earnings call, “In YouTube, we are prioritizing continued growth in Shorts engagement and monetization, while also working on other initiatives across our ad-supported products.”
The number of YouTube creators is at an all-time high. This can create a flywheel opportunity as content increases with more creators, which leads to an increase in viewership, which in turn is expected to drive more revenues. In order to reward creators, the company has started revenue sharing with YouTube Shorts, which now averages 50 billion daily views. This is up from 30 billion daily views in Q1 2022.
Google Cloud revenues was up 32% YoY to $7.3 billion. The company is seeing strong momentum from enterprises and governments for digital transformation. Management mentioned in the earnings call, “Google Cloud is making our technological leadership in AI available to customers via our Cloud AI platform, including infrastructure and tools for developers and data scientists like Vertex AI.”
Source: Company IR
In light of the soft revenue, net income declined to $13.6 billion compared to $20.6 billion in the same period last year. EPS was $1.05 and missed estimates by 11.9%. The company also recently announced a reduction of about 12,000 employees to improve long-term profitability
Risks to consider
Microsoft’s investment in OpenAI is an obvious risk with quite a bit of awareness. Google has not faced a similar threat for many decades. Microsoft also recently announced a new version of Bing which is yet to be available to the public. A student named Owen Yin previewed the new Bing before it was shut down. The new version is expected to replace the search bar with a chatbox.
However, you can also search the traditional way by toggling between chat and search in the toolbar. The new Bing is also expected to have access to the real-time data, unlike ChatGPT, which is trained on the data collected through 2021. The new version is expected to provide detailed answers rather than just links to websites. Similarly, the users will be able to chat with the bot regarding their queries and develop a conversation. It is also expected to perform more creative tasks, such as writing an email or a poem.
Opera also plans to integrate ChatGPT with a Shorten button feature, which will provide summaries in the side bar.
Conclusion:
I would not be surprised if we exit 2023 with a reimagined way to use Search Engines. The iteration cycle here is likely to move quickly compared to AVs or the Metaverse, as there are real-world applications where AI can be applied without safety issues (AVs) or friction in terms of user adoption (Metaverse/VR headsets). Instead, the scale has already been built with Search being a viral, daily activity used by nearly every human on earth. AI advancements will simply improve what is already in place.
Cutting-edge chatbots can be quickly deployed on the search engines that already exist, and this is a substantial difference from other overhyped, early-stage technologies. Their accuracy may still need time, but they're probably not too far off from being deemed “reliable enough.”
Investors should expect that AI will become a winner(s)-take-all market. In time, the difference in how search and other applications operate in terms of user experience plus ROI for advertisers will help carve a larger lead.
Secondly, investors should not forget the best innovation comes from the private markets, and even if stock-driven media focuses on Google Versus Microsoft, there will be a few David-versus-Goliaths where the smaller team comes seemingly out of nowhere to win the hearts and minds of consumers with a viral entry on the market. However, back to point number one, look for the Goliaths to court the smaller teams and bring them into the fold rather than compete head-on.
It may be clear that there are some puts and takes with Alphabet, such as search being on the precipice of a multi-decade shift, yet the reality is that ad revenue for the company is flat to declining. Our firm uses a blend of broad market analysis, technicals and fundamentals to time entries, such as when we bought Nvidia at its lowest trading point in October 13th for $108 with a real-time trade alert provided to our Members. Our process helps to reduce risk around stocks and find strong entries. Nvidia is up 100% from that recent entry. Our firm will do something similar with Alphabet, as we believe there is a further drawdown in its future. We hold weekly webinars on Thursdays at market close to go over the exact levels we plan to enter stocks. You can learn more here.
Royston Roche, Equity Analyst at the I/O Fund, contributed to this article.
Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.
This article was originally published on Forbes on Jan 27, 2023,12:17am ESTForbes on Jan 27, 2023,12:17am EST
Ad-tech stocks across the board had a tough year last year. Investors are hoping that 2023 will be a better year, yet according to the projected ad spend for 2023, this may not be the case.
It’s clear that lower ad budgets in 2022 affected nearly every ad-tech stock, including companies that own large audiences, such as Alphabet and Meta. It did not matter if an advertising company has audiences as large as 2 billion or more, runs large R&D departments that can leverage AI, or is centered in the leading media growth trend of connected TV (CTV) ads. Broadly speaking, because ad spend budgets were slashed on a year-over-year basis, this one, single headwind caused 50% to 80% selloffs across the advertising industry. Therefore, it’s prudent to look at whether ad-tech budgets will increase this year or if 2023 will look more like 2022 in terms of top line growth.
Here’s What Happened to Advertising Stocks in 2022
The stock market of 2022 was hectic, and the blowoff top in 2021 is primarily blamed for this. However, irrespective of the stock market’s performance in 2021, the global economy and the United States economy is in a slowing growth environment.
“Total digital ad spending worldwide will not grow as robustly over the next two years as we expected in our Q1 forecast. We now project 2022 digital ad spending worldwide to reach $567.49 billion, up 8.6% over 2021. In our previous forecast, we expected 15.6% growth to $602.25 billion. Our Q1 forecast predicted digital ad spending worldwide would reach $756.47 billion by 2024, but we now expect it to reach only $695.96 billion.
The key words here are “will not grow as robustly as we expected.” Stock investors get trapped when growth slows and forecasts come down mid-year. This is because not only must stock valuations contend with a growth rate cut in half (8.6% versus 15.6%) — but analysts must also try and figure out when a bottom will form on the slowing growth. Most will lean conservative, which pushes valuations down even further.
GroupM also lowered their forecast for 2022, from 8.4% to 6.5% (excluding US political advertising), and pure play digital advertising was cut from 11.5% to 9.3%.
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What to Expect for Ad Spend in 2023
According to the sources noted above, 2023 will not be the year of recovery for ad budgets. As of now, growth is expected to be lower than 2022.
Magna predicts that global advertising revenue will grow to $833 billion in 2023, or about 5% year over year, compared to 7% in 2022. GroupM is projecting 5.9% growth, or$856billion in 2023 (excluding US political advertising), compared to 6.5% in 2022 (excluding US political advertising). Both of these 2023 estimates reflect downward revisions of 1.5% and 0.5%, respectively. Including US political advertising GroupM is projecting 7.8% for 2022 and 4.6% in 2023.
Source: Company Websites
According to Insider Intelligence, China will weigh heavily on 2023 numbers as the second-biggest digital ad market is expected to “post its lowest digital ad growth on record” due to “tougher regulations and economic headwinds.”
According to IAB, the U.S. advertisement market is expected to grow by 5.9% in 2023, which is lower than the 9% growth seen in 2022. The slowdown in growth is the direct result of the challenging macro environment.
On a brighter note, the CTV market is expected to grow 14.4% in 2023 and will grow faster than the overall advertisement market. They forecast Linear TV spending to see a drop of (6.3%). Across the advertising channels, digital video, including CTV, is expected to have the highest share of 22.4%, up from 19.3% in 2022.
There are also positive comments from other ad-tech companies on CTV. Hunain Khan, Director, Programmatic CTV supply at Xandr said, “2023 marks a new age of CTV, due to the increased amount of available premium inventory through AVOD platforms.”
Similarly, Hitesh Bhat, Director, CTV/OTT, EMEA at PubMatic said, “2023 will be an interesting year for CTV in Europe, but I’m avoiding “the year of CTV’ hyperbole. The ad-funded opportunity will grow significantly with the entrance of huge players such as Netflix, Disney+, Paramount+ and the combined HBO/Discovery+ offering. I think Netflix and Disney will be careful in terms of ad loads, so as not to annoy viewers who are still also subscribers.
The Dentsu ad spending report forecasts that global advertising spending in 2023 to increase by 3.8% YoY to $740.9 billion. It is lower than the 8% expected growth for 2022 and the 19.6% growth reported in 2021. The forecasts have been slashed from the July report, which projected a growth of 5.4% for 2023. Some of the reasons mentioned in the report for the slowdown include rising inflation, interest rates, recessions, and political uncertainty. The report suggests that if we exclude the media price inflation, ad spending is forecasted to drop (0.6%) in 2023.
The Americas region is expected to grow 3.7% YoY to $339.1 billion, the EMEA region to grow 3.8% YoY to $156.7 billion, and Asia Pacific is forecasted to grow 4% to $245.1 billion.
Digital ad spending is expected to grow 7.2% YoY to $422.8 billion. It is down from 13.7% expected growth in 2022. Digital ad spending accounted for 57.1% of all advertising spending in 2023. The share is expected to increase to 59.5% in 2025.
According to Insider Intelligence, digital ad spending is expected to grow 10.5% in 2023 from the expected 8.6% in 2022, both of these estimates reflect downward revisions of 2.6% and 7%, respectively.
The CMO survey done in September 2022 showed that the marketing spending increased by 10.4% in the previous one year for marketers. However, they predict that the growth will slow down in the next one year to 8.8% and will start trending toward the pre-Covid level of 5.8%.
A majority of the companies say that the inflationary pressures are decreasing marketing spending levels. Marketing leaders in large companies report marketing spending reduction due to inflation and on the other hand, marketers in the smallest companies report an increase in marketing spending. The survey also suggests that the marketing expenses as a percentage of total revenue have reverted to the pre-Covid levels, as seen in the below chart. It reached a high of 13.2% in February 2021 to 8.7% as per the September 2022 survey.
Source: CMO SEPTEMBER 2022 SURVEY
The I/O Fund has launched a new $99/year Premium Newsletter called "Essentials" — this newsletter delivers premium samples for our readers who want more actionable analysis for their tech portfolios. This month, we released a stock pick that we believe will be a leader in 2023 plus a video with the buy plan.$99/year Premium Newsletter called "Essentials" — this newsletter delivers premium samples for our readers who want more actionable analysis for their tech portfolios. This month, we released a stock pick that we believe will be a leader in 2023 plus a video with the buy plan.
Google May Be the Stronger Ad-Tech Company in 2023
According to analyst consensus, Google is expected to generate $168.44 billion in net digital ad revenues worldwide this year, down from Q1 expectation of $174.81 billion. By 2024, Google’s ad business will reach $201.05 billion—or 2.8% below the Q1 expectation.
“Google has an edge over its other ad-reliant competitors in an economic downturn, as advertisers facing budget cuts typically prioritize lower-funnel channels with higher ROI like search,” said Evelyn Mitchell, analyst at Insider Intelligence. “Search has also retained full functionality in the wake of Apple’s privacy changes. Search ads are served in response to a user query and don’t usually leverage data about that user, so they’re less affected when iOS users opt out of being tracked. Meanwhile, social media advertising relies more heavily on consumer data.”
Source: EMARKETER/INSIDER INTELLIGENCE, NOVEMBER 2021
Source: EMARKETER/INSIDER INTELLIGENCE, APRIL 2022
The above two studies from Insider Intelligence show that Facebook and Instagram have the highest number of social media network users in the US. However, these platforms have lost the top spots in terms of engagement as TikTok and YouTube has the highest daily time spent by the users. Due to higher engagement, these platforms are likely to do better for social media advertising makes more sense.
On that note, Insider Intelligence expects Meta to generate $112.68 billion in digital ad revenue for the year 2022, representing a YoY drop of 2%, which is down significantly from the Q1 forecast of $129.16 billion. The firm has lowered the forecast for Meta through 2024 by nearly 20% citing Instagram’s ad revenue to grow by 2.6% YoY to $43.28 billion compared to a 50.2% growth in 2021. The estimate is significantly lower than the Q1 forecast of $54.16 billion. They expect Instagram revenue to reach $59.61 billion by 2024, which is more than 27% lower than the Q1 projection.
Below, Lead Tech Analyst Beth Kindig covers why Meta’s lack of access to third-party data spells trouble for its future growth. This webinar was recorded in April of 2022 yet is still relevant today.
Snapchat ad revenues are also negatively impacted by the economic slowdown. Insider Intelligence has slashed the 2022 ad revenue estimates by 18.3% from their Q1 forecast. They have also reduced the 2024 ad revenue by 33.6% from their Q1 estimates.
The TikTok Threat is Real
Insider Intelligence expects TikTok’s global ad revenue in 2022 to grow 155% YoY to $9.89 billion, below its Q1 estimates of $11.64 billion. They expect TikTok ad revenue to grow 36.7% in the next two years to reach $18.49 billion. However, the 2024 forecast has been by lowered by 21.6% from their Q1 estimates. Jasmine Enberg, the principal analyst at Insider Intelligence, said, “TikTok has transformed from an experimental play to a must-buy for many advertisers,” She further said, “But TikTok isn’t immune to the macroeconomic challenges causing advertisers to trim their overall digital ad budgets. Meanwhile, growing anti-TikTok sentiment among media executives and renewed calls by government officials to ban the platform are causing some advertisers to be more cautious about their spending there.”
According to the Sensor Tower report, social channels accounted for 61% of US digital ad spending in Q3 2022. The US digital ad spending is strong as it grew 5% quarter-over-quarter to $23 billion. Facebook leads the top advertisers in the United States. However, TikTok had the highest growth as it grew 29% QoQ and is a threat to other social media channels.
Disney+ increased its advertising spend in TikTok from $3 million in Q1 2022 to $17.9 million in Q3 2022. TikTok has been successful in being popular among the younger generation audience which has attracted marketers to its platform. As per Omdia research TikTok’s ad revenue is expected to exceed Meta and YouTube’s total video ad revenues by 2027.
Other ad-tech trends to watch for 2023
First-party data ownership is gaining popularity. The data is more reliable even though it might be smaller than the third-party data. The quality of the first-party data is superior and helps better understand the customer’s needs. Contextual targeting is another trend to watch. Contextual targeting means that users will see ads relevant to the topic you are watching or reading. Previously, you used to get ads based on browsing history. Contextual targeting might increase the chances of increasing the return on investment as the ads are relevant to the content. There could also be increased use of AI/ML tools in contextual targeting.
Conclusion
The overall advertising market is expected to slow down in 2023. Some of the crucial reasons are rising interest rates, inflation, and slowing global growth. Even though the estimates have been reduced, the digital ad market is expected to fare better than the broader advertising market.
We believe there will be a handful of winners despite more headwinds in 2023 and we cover these winners for our premium research site. However, until ad budgets resume growth, the industry at large is likely to be volatile in stock price.
Royston Roche, Equity Analyst at the I/O Fund, contributed to this article.
Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.
Magnite provided a stark reminder that the bottom line is more important than the top line in current market conditions as the stock moved 80% off the earnings report with low revenue growth yet the small cap has rare strength with its improving bottom line and 20% cash flow margin.
Low Growth; Strong Bottom Line
The company reported Q3 revenue of $127 million, which grew 12%, and beat estimates by 2.8%. This is down from 23% last quarter.
For Q4, management is expecting revenue to be $154 million for growth of 8.3%. Perhaps Magnite also benefited by being the last to report as many ad-tech companies guided lower than 8.37%. Analysts were expecting growth of 8.25% for Q4.
CTV ad revenue grew 29% year-over-year to $55.8 million, and represents 44% of revenue. Management is guiding for 10% CTV ad revenue growth next quarter for $64 million in revenue, at the midpoint.
Mobile weighs on the company’s growth with 7% this quarter for $44 million, compared to 14% last quarter for $44 million. The segment was flat sequentially. Mobile represents 35% of revenue.
Desktop is the weakest segment at (7%) growth this quarter for revenue of $27 million compared to 1% drop last quarter for revenue of $27 million. This segment was also flat sequentially. Desktop represents 21% of revenue.
Magnite breaks down United States and International growth with both regions growing YoY. The United States represents 78% of GAAP revenue.
The United States region GAAP revenue grew 9% YoY to $114 million, up from $106 million last quarter. International grew 18% YoY to $32 million, and was flat sequentially, with $31.2 million last quarter.
The company reported GAAP EPS of ($0.18) and Non-GAAP EPS of $0.18. This is an improvement from Q2 and also an improvement from the year ago quarter. In fact, this was the strongest EPS on GAAP and Non-GAAP basis over the past five quarters excluding the holiday quarter.
Analyst estimates for adjusted EPS next quarter are $0.32. Assuming the company reports this EPS, it will exceed last year’s holiday season with adjusted EPS of $0.26 and it will also beat Q4 2020 with adjusted EPS of $0.19.
This improvement is important to note and to continue to track as few companies are able to improve bottom lines right now let alone a small cap.
Pictured Above: Magnite stands out for its improving bottom line.
The GAAP gross margin was down from 53% in Q2 to 51%. However, the GAAP operating margin has improved to (15%) in Q3 from (17%) in Q2. The improvement is more evident when you compare to Q1 at (34%) and the year ago quarter at (18%). Excluding the holiday period, Q3 2022 had the strongest GAAP operating margin from the past five quarters.
Down the income statement, the GAAP net margin of (17%) mirrored the operating margin with a 1 point improvement sequentially and YoY. This resulted in $24.4 million in net losses.
On an adjusted basis, the company reported a profit of $25.6 million, up from $20 million last quarter and up from $20 million in the year ago quarter.
Where Magnite shines is the cash flow margins. Operating cash flow of $28.6 million represents a margin of 20% on GAAP revenue. The company stated that it will have free cash flow of “over $105 million” which is up from the previous guide of $100 million. This will represent a FCF margin of 20.5%
Please note the following I/O Fund internal note on Magnite’s FCF calculations which deduct cash interest payments from operating cash flow.
“Some companies calculate FCF in a different manner. If the company does not provide FCF, we can calculate using operating cash flows minus capex from the cash flow statement. In this case, the operating cash flow calculation itself is different which is a rare case. The operating cash flow is adjusted EBITDA less Capex. The FCF involved the deduction of cash interest payments which is available in the supplemental disclosures of other cash flow information as the recent earnings call provided the interest payments for this quarter, however, they did not provide cash interest separately.”
The company has $253 million on the balance sheet and $725 million in debt. The debt is less of a concern as long as the company is FCF positiveas long as the company is FCF positive and doesn’t pursue anymore acquisitions. The debt includes $400 million in convertible senior notes and a term loan of $355 million due to the SpotX acquisition.
The company’s net leverage has greatly improved from 6.2X in Q2 2021 to 2.6X in Q3 2022. This also improved from 3.1X in Q1 to 2.8X in Q2.
Magnite reported stock based compensation of $17.4 million, or 13.7% of revenue.
Magnite Proves the Valuation Trade is Alive and Well
Despite Magnite being comfortably profitable on an adjusted basis and free cash flow positive with a 20% margin, the stock was priced for bankruptcy or another fatal risk at 1.5 forward P/S going into earnings. I believe the stock rallied because the risk/reward didn’t reflect the valuation, rather reflected the broader “small cap” bucket where most small caps have serious profitability issues.
The low valuation coupled with clear evidence Magnite is unlikely to go out of business anytime led to the stock rallying.
Magnite helps to illustrate that 2022 market conditions continue to be more favorable for stocks with strong bottom lines. This is a critical adjustment for growth investors as Magnite’s top line does not fall into a growth definition at 12% this quarter and 8% next quarter.
Note: All numbers quoted ex-TAC unless otherwise stated. GAAP margin is calculated on the GAAP revenue of $145.8 million. Please note, we do not own Magnite at time of writing but plan to enter if we can find the right technical setup.
I couldn’t be more disappointed with Snap’s management. Not only the lack of guidance but the lack of willingness to describe exactly what the issue is with their business.
In the call, the management said they are seeing 9% growth to-date this quarter yet are modeling revenue to be flat year-over-year. This is an absurd comment to not substantiate. Why would August be 8% growth, October 9% growth and the holiday season be negative growth, which in turn weighs on October’s progress? I’m not sure which is worse, was this a flippant comment they made and we will see 9% or higher growth come next quarter? Or, are they really seeing such a serious headwind that November and December will greatly decelerate? I believe I have identified the serious headwind with no help from Snap’s management team, which I detail below.
Here is one comment that was made on the call regarding the expected revenue deceleration during the holiday season:
“By the end of August, when we shared 8-K about the restructuring, the quarter-to-date revenue had improved to about 8%, and so that implied things accelerated a bit. With the full quarter number at 6% this quarter, obviously, things slowed down into about the low single digits in September, so. And then we’ve seen things move up a bit in the beginning of this quarter with the early weeks being at about 9%.”
Here they try to spin the December quarter:
“It’s Derek speaking. I’ll take the first part of that and then hand it up to Evan. I think first, just stepping back for context on Q4. Even flattish year-over-year revenue growth is about a 15% step-up on a quarter-over-quarter basis. So, we are expecting revenue to grow seasonally at a pretty good clip. So, the issue that we’re seeing here is that if you look back to a year ago, we grew at over 40% year-over-year in the prior year. And many of the really significant macro impacts that we’ve seen over the course of this year weren’t impacting the business nearly as much as they were a year ago.”
To add to the absurdity, they have relied on excuses such as Ukraine, macro for brand advertisers or Apple’s changes. This doesn’t explain why November and December would weigh on October as both are consistent (not variables) throughout Oct-Dec.
Here, an analyst calls out that it doesn’t totally add up:
“Just on the brand side. I think many are curious kind of why brand will suffer so hard going into a seasonally strong period. Is this more macro-related? Is it — given some of the restructuring, is that having some impact?”
This was the answer, which was not a good one: “And certainly, with the performance that we saw from the brand portion of the advertising business in Q3 gives the — sort of informs our expectation of the decel to move through the rest of the quarter.”
So, I’m sitting here wondering why a 19% DAU growth isn’t translating to higher revenue growth and trying to sift through the garbage being stated on the call. Following strong DAU growth for many quarters, management is providing a 6% growth rate this quarter and “maybe” a 9% growth or “maybe” a 0% growth rate. Something is very wrong here.
Furthermore, how can the 19% DAU growth not give them more confidence in terms of the revenue they can drive next quarter?
Because I’ve worked around mobile global UA, I believe the answer to this question is that Rest of World user growth greatly weighs on this company’s business model. This is the only true explanation that makes sense to me. If the majority of the user growth is in the $0.90 ARPU to $1.00 ARPU, then this is going to pull down revenue. This also means that next quarter — even with strong DAU growth — the company cannot accurately guide because ROW cannot monetize high enough to support YoY growth.
I pointed this out in the analysis here for our Re-Entry when I stated: "My interpretation is that DAU will outpace revenue growth because DAU growth will come from Rest of World where users are monetized at a lower rate than North America and Europe. This has been the trend over the past year in Snap’s key metrics."
It’s one thing to have advertiser falloff and softer ARPU in North America in the $8.00 ARPU range (which you’ll see below has not occurred!!) and another thing to have even nominal falloff in a region that is at the $1.00 ARPU range, because the majority of the user growth is occurring here, then it only requires small decimal points to drag down overall ARPU quickly.
My regret is believing management when they said it was “platform changes” or “Apple’s ATT” or “macro headwinds. Excuse my language in this write-up, but instead here is the total garbage investors were offered:
“Operationally, our advertising business has become a lot more technically complex over the past few years as advertisers are working to better measure and optimize their campaigns. That means that we need to drive increased coordination across our sales, engineering and product teams, which is one of the reasons I’m so excited to have Jerry leading these teams as our COO. I’ve already observed a significant change in the way that our teams are working together, and I’m really pleased to see the focus on our advertising customers driving everything that they do […] We saw about an 8% increase in impressions year-over-year in the quarter, which is really a function of daily active users and engagements.”
My note: again, this doesn’t address why there would be a deceleration in Nov/Dec and why they can’t guide. The company had 19% DAU growth and 8% growth in impressions and they can’t give a guide? Very strange.
They said eyeballs are doing well again:
“So, at a very high level, both in the U.S. and globally, viewership is up. And so that means that our overall opportunity is expanding if we can continue to increase folks’ depth of engagement. And that’s really important, of course, for advertisers who really value the reach that we provide.”
Here’s a question where Snap could have been more forthright:
“Ross Sandler:
I just wanted to throw the macro question out. So, it sounds like it’s mostly brand advertising that was weak in 3Q, and it seems like that’s the area that’s forecasted to really drop off as we kind of go forward here in 4Q. So, could you just maybe elaborate a little bit on what you’re seeing? What’s — we can obviously see what’s going on with the macro broadly, but specifically to like rest of this quarter, what commitments you’re looking at that would cause those growth rates to kind of dip into the negative?
And then, related to one of the prior questions, you’re growing your DAUs almost 20% and impressions 8%. So, it seems like we’ve just got a demand problem here, not a supply problem. Can you just talk to that a little bit? Thank you.”
I’ll save you the answer they gave which was evasive and focused on “restructuring, “advertisers can turn performance based advertising off very quickly” and “future of AR”
There were moments where they brought up EMEA and APAC, but this was buried and not discussed as a direct answer to the issue:
“And the third thing is bringing top talent to our three president roles for the Americas, APAC and EMEA. One of them Ronan Harris is going to join us next week. This will ensure that we’re improving our focus on customers in every region and getting closer to the customers’ needs. I think these priorities will set Snap up to be successful in this current environment.”
And then again, it was their last comment before closing the call:
“I think one thing I’m watching specifically is on the sales side. We’ve got these president roles. Ronan Harris is joining a bit later this month as our President of EMEA. We will also have an APAC President and an Americas President, and we’ll be putting folks into those roles as soon as we can. And in addition to that, we’re also thinking about how to better organize our sales teams to go to market in a way that best serves our customers. And we’re sort of thinking about Q1 as the time line for that.”
Yet, if this is what’s going on — and it’s my speculation that it is — the management did nothing to connect these dots and continues to rely on many other trivial excuses that don’t add up to the 6 month variability we are seeing (July-Dec).
I believe they are not connecting the dots because it signals something systemic (not that it matters given the severity of the selloff – they could have not shown up to the earnings call and the stock would probably be doing better today).
It’s systemic because the very regions they can grow DAU will, in turn, weigh on their revenue.
I’ve noted the ROW could be a concern in our previous write-ups, but now that I’ve gotten more information on just how disconnected DAU growth is from revenue growth in Q3, and now in Q4, I feel fairly confident we are looking at company struggling to keep up with previous ARPU that had a higher mix of North America and European growth.
Below is Snap’s overall ARPU. Quick glance shows that it’s declining YoY for Q2. It declined again for Q3 Average revenue per user was $3.11 in Q3 2022, compared to $3.49 in Q3 2021 (not pictured below).
In fact, we can see further evidence of this as ROW declined (9%) and North America only declined (1%).
This makes my bullshit detector go off even more with the Apple excuse because iPhones are not used in ROW regions, instead these regions primarily use Android. Android has not gone through the privacy changes (yet) that Apple has.
If Apple was the issue, North America would have fallen off in ARPU by more than (1%) bc this is the highest concentration of iPhone users. Europe’s (5%) also contributes but the Apple excuse is debunked bc Q3 2021 was when these changes occurred and the YoY would be more drastic in North America if Apple was contributing.
If we look at Q2, another big miss in the earnings report, we see the same pattern. North America was up 8% debunking the Apple issues and ROW is down (11%). This creates a (4%) drag on ARPU.
You can see the largest comp for ROW is approaching, which is Q4’s $1.12. All quarters have a high comp in Q4 but you can see the other regions have been doing a decent job of keeping pace.
On a side note, the company states Russia falls within Europe revenue, so the (9%) in the $1.00 region is also not satisfied by the Russia-Ukraine war excuse. Europe (the Ukraine region) up 2% last quarter in Q2.
So now, it starts to make sense that Snap is not confident about the holiday season as the drag is coming from ROW.
Obviously, I’m incredibly disappointed because the company used the Apple ATT excuse and my understanding is this should be something they can overcome as Snap does not use third party data.
On another note, I firmly believe the company is not selling off due to margins but rather the opaque issues with revenue. This company is going to become FCF positive between $1 billion to $1.5 billion next year and this is well understood. Scanning the analyst notes today, they were encouraged by the bottom line in the report. Not one mentioned ROW revenue, however, despite it’s clear decline in ARPU.
It’s easy to glance at the margins and draw a quick conclusion that the company is very unprofitable, but the well-publicized budget cuts across the board has resolved this issue for the most part.
The market is forward-looking and as soon as next quarter, the shift toward profitability will begin. In fact, the company beat on the bottom line across the board on top of moving toward greatly improved operating income next year. If anything, this was a positive as market expected ($105) million FCF and company reported +$18 million FCF.
If it were the bottom line, it’d be much more straight forward. Instead, I feel the management is dodging the real issue as to why DAU growth does not translate to revenue growth. The longer the DAU strength continues and the longer the revenue weakness continues, the more of a red flag it has become.
Management is responsible for discussing the real issues with shareholders and ROW should have been directly called out in this earnings call and the previous earnings call.
Even worse, to have so many different storylines that don’t add up … Apple, Ukraine, Macro, Brand Ads – during the holidays nonetheless — supposed to get worse from Oct to Dec …? It simply doesn’t sit right.
Conclusion:
I had posted this on the forum in the comments and it sums up my thoughts:
“Snap is pulling levers to not burn cash and will have a 20% FCF positive margin, maybe 25%, and this is well understood at this point. Some people point towards SBC which at $700M net (minus buybacks) is 14% of annual revenue. Not the worst I've seen — cloud is certainly much higher with some favorites in the 30% SBC range.
I believe it's the disconnect between user growth and revenue growth that is causing the selloff, and I think it's important to identify the issue bc Snap will be FCF positive moving forward around $1B to $1.5B — so will Snap's new cash profile (which is widely understood to show up in Q4 and beyond following the layoffs and the shutdown of ancillary products with one-time related costs recognized in Q3) fix the issue? If so, it's a buying opportunity.
I don't think this is a buying opportunity bc what we have is a major disconnect on DAU growth from revenue growth. Why can't the company post a higher growth rate given the 19% DAU growth — usually audience precede revenue growth. If this isn't fixed and the FCF issues are fixed, it may still be problematic business model.”
This write-up was intended to describe what I truly think the problem is with the business model, with no help from management. This correlation would have been much easier to see if Snap had not created many smoke screens to deter from the real issue.
I believe institutional analysts are in the same boat, where Snap’s narrative and excuses has distracted them from looking more deeply at the issue. You can sense on the call, they can’t quite grasp it. It’s not terribly difficult to put together – it’s simply a matter of searching for it, which no one is doing because management is feeding so much garbage on the call.
The conclusion is we are out of the stock with a serious and lingering concern about this management team.
Earlier this week, I/O Fund CEO and Lead Tech Analyst Beth Kindig joined Jeremy Owens, Tech Editor, and San Francisco Bureau Chief of MarketWatch, on Barron’s Live. They discussed cloud valuations including those that are trading at 2X above Covid lows, what metrics matter when evaluating cloud companies, and what to watch for in upcoming earnings season — including a few comments on ad-tech. Barron’s Live. They discussed cloud valuations including those that are trading at 2X above Covid lows, what metrics matter when evaluating cloud companies, and what to watch for in upcoming earnings season — including a few comments on ad-tech.
Metrics and Valuations
As discussed in the podcast, the FOMC decisions have forced tech investors to look for cloud stocks that are expanding their margins and also have positive free cash flow. If you look at the best-of-breed companies that command the top 10 in valuations, the majority of them are free cash flow positive.
We had discussed with our premium research members back in May in a special report Compartmentalizing Cloud Stocks that “It’s true that cloud is deflationary but it’s also true that cloud can have profitability issues […] cloud is quite resilient in terms of growth, due to being deflationary, but those weak bottom lines may be questioned over time. Cash came easy over the past decade, and as cloud investors, we need to reframe our thinking on what constitutes an attractive cloud stock.”
Free cash flow is emerging as an important metric because cash gets rerated in a rising rate environment. As stated, not only were many cloud companies were not public during the previous rising rate environment of 2017 to late 2018 – but in addition to this, the previous rising rate environment was quite tame and we are currently in a more aggressive rising rate environment.
Along with free cash flow, GAAP operating margins are being closely examined. This has resulted in companies with high stock-based compensations being penalized during earnings.
The takeaway is that a best-of-breed company with a 15X or higher valuation must remain FCF positive or it will immediately lose its category high valuation. Revenue growth alone is not determining the top spots in this category any longer. This may seem obvious at first thought but we have found it’s better to close a stock at a higher valuation if it has contracting margins.
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The difference between Subscription and Consumption Models
Consumptions models occur in the Big Data and Analytics trend where data storage, processing, and analytic solutions are based on usage rather than on a recurring subscription fee. This trend is becoming popular because with consumption-based pricing model, revenue is uncapped. The consumption billing model does not have a ceiling on revenue, so if customer consumption rises, so does sales. There is what is meant by uncapped revenue potential.
We covered Snowflake’s Consumption Model in January of 2022 when we said in our free newsletter: “While Snowflake uses a “land -and-expand” sales strategy, it also uses a consumption billing model. For instance, Snowflake bills customers based on the amount of data they store and transfer and what resources they use. Accruing revenue based on consumption rather than a ratable subscription model decreases the predictability of quarterly revenue, but it leaves revenue uncapped. This provides revenue upside, because if consumption soars, then so will revenue.”
Some of the drawbacks, however, include the revenue growth being less predictable than subscription revenue. There also isn’t a floor on revenue because if consumption declines, then so will sales. Contracts help protect against this but are often only 1/3 of next 2.5 years of revenue.
The drawbacks were also discussed in the Snowflake’s Consumption Model article in January of 2022, “Another risk is the company’s consumption billing model, which is inherently unpredictable. This can make growth lumpy and some quarters may disappoint the Street. Investors should expect increased volatility in growth from Snowflake in the near term as new customers ramp consumption. However, management does expect revenue growth to smooth and become more predictable in the aggregate as customer consumption scales and matures on the platform.”
The lack of predictability is seen in Snowflake’s earnings history with Q1 earnings reporting revenue growth of 85% YoY to $422.4 million (beat estimates by 2.3%). However, the GAAP EPS missed by $0.02. The management had a hard time convincing the analysts in the earnings call that the company’s revenue was not discretionary and the consumption was lower due to shifting economic circumstances that impacted certain customers, particularly consumer facing cloud companies.
The company’s CFO, Mike Scarpelli, said in the earnings call, “Consumption patterns may fluctuate from quarter-to-quarter. This variability does not detract from our long-term opportunity. Customer’s overall demand for Snowflake remains unchanged. This is supported by the contractual commitments they are making with us and their longer-term plans for adopting the data cloud across their organization.”
In the podcast, we also discussed how net retention rates are often higher for consumption models as spending ramps over time and is uncapped. It’s easier to re-accelerate here for that reason and it’s not the best apples-to-apples comparison for subscription NRR. The net retention rates for subscription-based companies are in the range of 130-140 range while Snowflake has remained in the 170 range.
Another metric is the remaining performance obligation (RPO). When customers sign onto the platform, they purchase consumption at specified prices, which gets recorded as remaining performance obligations (RPO). These contracts are for about 2.5 years. Although these key metrics are important, as mentioned earlier, what the market will reward or penalize most in a rising rate environment are operating margins and free cash flow.
Over the last two weeks, we've entered two bargain priced stocks on our premium site where the market may have gone too far, too fast — particularly those with an improving bottom line. Become a premium member to unlock real-time trade notifications on every entry and exit. Over the last two weeks, we've entered two bargain priced stocks on our premium site where the market may have gone too far, too fast — particularly those with an improving bottom line. Become a premium member to unlock real-time trade notifications on every entry and exit. premium site where the market may have gone too far, too fast — particularly those with an improving bottom line. Become a premium member to unlock real-time trade notifications on every entry and exit.
Ad-tech opportunity
In the interview, Jeremy Owens reminds me that I was the first person to warn him about how the Apple’s IDFA changes that would negatively impact Facebook’s revenue many years ago. It was a bold call at the time because I called the top for Facebook when it was a stock market darling in 2018. Despite the odds, it turned out to be accurate.
We discuss how ad-tech stocks are trading at historically low valuations with many 50% lower than where they have traded during times of economic uncertainty. The share prices of these ad-tech companies can grow over 100%. When the market senses a bottom is in — which I believe was either Q2 or will be Q3 — buyers will step back in to support higher valuations.
We discuss why CTV ads is the most investable trend in media right now.
What to look in the upcoming earnings season
Microsoft’s results are to be closely watched since the company is a bellwether for Cloud. Its suite of Cloud products drives down costs and it’s the most insulated cloud company. It benefits from cloud migrations and also the need for organizations to reduce costs.
Analysts in the earnings call are concerned that the enterprise sector is the next shoe to drop following consumers. The consumer cycle is very short, whereas for Enterprises, it depends on the renewal cycle and there is a period of negotiation. In addition to constrained enterprise budgets, many startups are not able to raise funding and are going out of business, which can weigh on cloud, as collectively startups are a sizable customer for cloud companies.
The cybersecurity sector has reported exceptional fundamentals given the economic headwinds. Many companies have been reporting high growth rates and are cash flow positive. This sector also has no exposure to discretionary spending, which will help the category sustain long-term.
Bargain Cloud Stocks
We spoke about Best-of-Breed on this podcast yet we are currently building positions in companies that are undervalued and more of a “basement bargain” or “fire sale” valuation as we believe the market has not been entirely efficient with key stocks that have been penalized with low valuations. These stocks are 50% lower than their Covid low and have the potential to bounce back. In fact, one could argue there is more room for gains in these stocks than the best-of-breed companies which are within 30% of historic valuations for cloud stocks.
00:00 Intro
00:44 Valuations
04:40 Consumption-based pricing
11:24 Snowflake vs MongoDB
13:15 Ad-tech
20:15 Upcoming earnings season
22:08 Cybersecurity
24:22 Best practices for retail investors
Please note: The I/O Fund conducts research and draws conclusions for the Fund’s positions. We then share that information with our readers. This is not a guarantee of a stock’s performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.
