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Month: November 2018

GM Stock Risky Due to Autonomous Vehicle Bubble

Posted on November 29, 2018June 30, 2026 by io-fund
GM Stock Risky Due to Autonomous Vehicle Bubble

This week, General Motors Company cut more than 14,000 salaried staff and factory workers with plans to close seven factories worldwide in what Bloomberg calls a “sweeping realignment to prepare for a future of electric and self-driving vehicles.” Unfortunately for GM, and their employees, the future of autonomous vehicles is much farther off than what the company represents. Investors in GM stock should be cautious, and realistic, as to when new revenue streams will occur, as cutting costs, even to the tune of a net savings of $4.5 billion, might not be enough to wait out the innovation cycle.

In light of the recent layouts, there is $1.5 billion of reduced capex that the company will be saving by cutting the low-demand production lines and the anticipated plant closures (a drop in the bucket compared to the annual capex of $27.5 billion), however, the $1.5 billion capex is not being reinvested into electric vehicles or autonomous vehicle production at this time. The lack of reallocation conflicts with statements from the company CEO, Mary Barra, who promised the company would double investment in electric vehicles and self-driving technology during this week’s announcement.

The bottom line is that GM is correct to prepare for tough times, but they are not disclosing the true timeline for long-range electric vehicle and autonomous vehicle deployment and investors will have to wait years before they see any real profit from new production lines.

Three Words to Heed for GM Stock: Gartner’s “Trough of Disillusionment”

In September, Autonomous Vehicles fell into the “trough of disillusionment,” which is the downward slope published by the analyst firm, Gartner, to show the hype cycle for certain technologies. You can think of this as “winter is coming” for tech products – a time when all of the buzz and excitement finally meets reality (note: artificial intelligence winter is a well-documented thing).

ABI Research, an advisory firm that reports on market-foresight trends, predicts 8 million consumer vehicles with Level 3 to Level 5 autonomy will ship in 2025. Compare this to the 94.5 million vehicles sold in 2017 – which equates to 8.5% of sales. This is a small and fairly insignificant percentage of market share to be chasing 7-years ahead of deployment. Yet, investors have poured cash into auto manufacturers due to marketing campaigns that provide false hope for the near future.

Twitter post

The reality for autonomous vehicles includes regulations, production cycles, and delays in implementation for what is an extraordinarily difficult problem to solve – how to get machines to respond like humans at crucial moments. This gap between investor expectations (perception) and commercial deployments (reality) has created an autonomous vehicle bubble.

Per statements from GM, long-range electric vehicles are a minimum of 8 years before they represent a slim 10% of GM’s current production. In 2017, the company committed to a volume production goal of “1 million units globally by 2026,” with the majority of EVs being sold in China. GM’s overall production was about 10 million units globally in 2016.

Brief Background on the 6 Levels of Autonomy

You can skip this section if you know the six levels of autonomous vehicles as published by SAE International. If not, this background is important to understand why the autonomous vehicle bubble formed, and why and when it will burst.

Level 0: No Automation. The driver performs all of the tasks.

Level 1: Driver Assistance. The driver handles all of the accelerating, braking, and monitoring of surrounding environment. An example of this level is when a car brakes for you in a critical moment.

Level 2: Partial Automation. The vehicle assists with steering and acceleration functions and allows the driver to disengage. Bubble formed here with investments pouring in, fueled by high hopes of Level 4 or Level 5 commercial deployment by 2020.

Level 3: Conditional Automation. The vehicle controls all monitoring of the environment using sensors. The driver’s attention is critical but the AV system runs the safety critical functions. This level does not require human attention under 37 miles per hour. Bubble will burst at this level as commercial deployments are delayed and reality sets in that AV investments will not see returns for many years.

Level 4: High Automation. Vehicle is capable of steering, braking, and accelerating, as well as responding to events and changing lanes. The system is switched into the mode under safe conditions, but the vehicle cannot determine dynamic instances like traffic jams or merging onto the highway. Most likely ETA 7-10 years.

Level 5: Complete Automation. No human attention required. No need for pedals, brakes, or a steering wheel. The AV controls all critical tasks, monitoring of the environment and identification of unique driving conditions like traffic jams. Most likely ETA 10-15 years.

Autonomous Vehicles – Stuck in Second Gear

Hurricane auto sales from last September helped GM stock, which rose 11.9% from the previous years, however the stock has retraced and is now trading at $35 per share. GM is no stranger to pushing the autonomous vehicle hype with executives commenting that Cruise Automation was making “rapid progress” back in October 2017, and in a blog post, the CEO stated, “in the coming months, we’ll take the next bold steps in testing our autonomous technology as we lead the way to fully self-driving vehicles without any human driver as a backup.” Those months have come and gone, of course.

Tesla is another example of a company that has made unfulfilled AV promises. In 2017, Tesla missed the deadline for a full rollout for self-driving cars. Since 2015, the company had been promising that every car made going forward would have the hardware necessary to facilitate full self-driving capabilities. In line with inflated expectations, Tesla announced it would officially stop promoting the “Full Self-Driving” option for its cars.

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Waymo has been in testing since 2009 and has racked up more than 8 million miles on public roads and more than 5 billion miles in simulation. There are 600 self-driving Chrysler Pacifica Hybrid minivans on the road with goals of launching a commercial driverless transportation system later this year. This, and many other “near deployment” announcements have created massive expectations for the AV market, which is forecast to grow 10x from $54 billion in 2019 to $556 billion in 2026 at a growth rate of 39.47%.

The primary risk today for GM stock is that these forecasts assume commercial deployments will occur on time. As Mike Ramsey, a lead author on the Gartner report points out, even if GM and Waymo continue to debut driverless minivans or launch ride-hailing fleets, commercial deployments won’t be ready anytime soon. For example, the 2019 Audi A8 with Traffic Jam Assist with Level 3 partial automation, which has been anticipated for some time, has extended its release date another year due to foggy federal regulatory framework, infrastructural differences, and a lack of consumer understanding of self-driving technology.

More Evidence of the Autonomous Vehicle Bubble

In two side-by-side headlines we see Mary Barra of GM propagating a very different perception than what company insiders have reported. On November 1st, at the New Times conference moderated by Andrew Ross Sorkin, Barra stated the company is “on track” to roll out a ride sharing service in 2019 that would rely on autonomous vehicles, with the New York Times reporting Barra “added the company had a strategy to show how its vehicles are safer than human drivers.”

Dealbook

Meanwhile, on October 23rd, GM insiders told Reuters, “Nothing is on schedule,” citing unexpected technical challenges, such as Cruise cars not correctly identifying whether objects are in motion. Current employees and former employees also reported that Cruise software struggled to identify whether objects on the road are stationary or moving, failed to recognize pedestrians, and has mistakenly seen phantom bicycles.

Reuters

The regulation hurdles between Level 2 and Level 3, and delayed deployments, will put immense pressure on stocks, like GM, that are overvalued based on AV speculation. Press plays a large role in this. Headlines are a continual churn of autonomous vehicle “moments” – every partnership, every mile driven, every make and model that adds another feature. To be clear, we’ve only gone from a Level 1 to Level 2. We are not able to release Level 3 AV right now –that includes Waymo, GM, Audi, Mercedes, BMW, and yes – even Tesla.

Research studies have proven that consumers are very confused by the high profile promises, which Thatcham Research calls “dangerously confusing.” In a recent study, 71 percent of respondents around the world believe they can buy an autonomous vehicle today – yet there is not one autonomous vehicle on the market. The top three brands that consumers mistakenly believe distribute self-driving cars include Tesla (40%), BMW (27%), and Audi (21%). Of these, 11 percent say they would take a brief nap while using assist systems (hopefully, you’re not the person in the crosswalk when this happens).

GM Stock Investors Must Define “Future”

The company’s decision to lay off a sizeable work force seems sensible enough from a shareholders’ perspective (however unfortunate for the Midwest laborers). However, what is not sensible is having high expectations of when the future will deliver new revenue streams.

For value investors looking to buy GM’s high yield at depressed prices, don’t base the decision on GM’s PR push around electric vehicles and autonomous vehicles unless you’re comfortable not seeing profits in these production lines for many years to come.

Posted in AI Stocks, Autonomous Vehicles, Consumer Tech, Electric Vehicles, Tech StocksLeave a Comment on GM Stock Risky Due to Autonomous Vehicle Bubble

Holding Nvidia Stock Will Pay Off Due to Two Impenetrable Moats

Posted on November 15, 2018June 30, 2026 by io-fund
Holding Nvidia Stock Will Pay Off Due to Two Impenetrable Moats

Tech stocks are getting slammed right now, and Nvidia may be one of Wall Street’s biggest losers in the sell-off that began last month and continued into this week. Nvidia’s stock has seen a 30-day high of $292 and a whiplash low of $176 – equaling a 40% plunge in the matter of four weeks. Today, it stands at $197.60.

Economic indicators and earnings from tech companies have not exactly warranted this reaction from the market. Fears the semi-conductor industry is slowing down based off Advanced Micro Devices earnings report were negated when Intel reported strong Q3 earnings. And while Apple may be on the precipice of a capped out $1 trillion-dollar market cap due to possible iPhone saturation, Nvidia’s outlook is quite the opposite in regards to public-company growth trajectory. The market may continue to have volatility, but Nvidia investors who are patient will be rewarded due to competitive advantages in GPU-powered cloud performance and developer adoption of Nvidia’s platform.

Brief Overview of Nvidia’s Revenue Segments

To summarize, gaming claims the majority of Nvidia’s revenue at $1.81 billion, up 52% YoY. Gaming will get a nice boost in 6-12 months from the new GeForce RTX 2070, RTX 2080 and 2080 Ti chips, which introduce the possibility of hybrid rendering through ray-tracing. In layman’s terms, ray-tracing mimics how light behaves in the real world by mapping out rays from 3D illumination sources. The imagery is much more realistic as a result. Electronic Arts released the first raytracing game today (November 14th) whereas 6 months ago, the gaming industry did not think raytracing would even be possible. Companies who have signed up for the new Turing architecture include Adobe, Pixar, Siemens, Black Magic, Weta Digital, Epic Games (maker of Fortnite) and Autodesk.

Data center revenue has been picking up speed at 83% YoY, or $760 million, as GPU chips are powering more of the cloud for machine learning and artificial intelligence applications. Data center revenue, once a small blip, claims 24% of the company’s total sales. This will continue to grow steadily into the near future due to the computing power and flexibility GPUs provide over CPUs, which is what Intel sells, or TPUs and FPGA, which are custom machine-learning chips by Google and used by Microsoft that are too specific to one platform for widespread adoption – more on these points below.

Source: TechCrunch

Smaller segments by Nvidia include professional visualization and automotive, which grew to $281 million and $161 million, respectively, up 20% and 13% year over year.

Two Impenetrable Moats: GPU-Cloud and Developer Adoption

Revenue segments are your typical Nvidia stock coverage. But can Nvidia take market share from Intel? Will Google, Microsoft, Facebook and Apple design their own custom chips to compete with Nvidia? This is what investors need to answer for themselves especially if we continue into correction territory.

Regarding Intel, the cloud is too competitive to forego the performance and efficiency that Nvidia delivers. Recently, the Turing T4 GPU became the fastest adopted server GPU of all time in just two short months of hitting the market. Prior to the release of the Turing T4 GPU, Nvidia’s data center growth was 3x compared to Intel. Intel posted 26% growth YoY whereas Nvidia posted 83% YoY. However, Nvidia’s data center revenue is 1/6th compared to Intel’s at $760 million vs. $6.1 billion. This revenue segment will continue to grow as the GPU-powered cloud is built out. Unfortunately for Intel, GPUs are the better choice for cloud customers as the usage pattern is constantly in flux, demanding a wide variety of models and different software frameworks. Intel’s CPU Xeon Processor cannot compete with the performance-per-watt of what Nvidia offers in the cloud. Per the announcement on September 13th, 2018, Microsoft, Google, Cisco, Dell EMC, Fujitsu, HPE, IBM, Oracle and Supermicro plan to release servers with Nvidia’s T4 GPU on board.

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Google and Microsoft have both made chips for their data centers. Microsoft adopted the field-programmable gate array (FPGA) which is used for AI apps. And Google has built a custom chip called the Tensor Processor Unit (TPU) for Google’s TensorFlow deep learning framework. Competing, customized chips will become the new norm as tech giants prefer to use proprietary tech. The biggest weakness that competing customized chips face like TPUs, from Google, and FPGA, used by Microsoft, is that they may be too specialized for developers to adopt. The drawbacks will continue to be price and difficulty, as programming for FPGA is an area not many engineers have expertise in. The same goes for Google Cloud Platform (GCP). They’ll have to get developers to adopt GCP and keep them locked into TensorFlow. Even so, there are alternate frameworks such as PyTorch from Facebook which add further to the fragmentation of developer frameworks. In addition, even if Google uses TPUs for inferencing, it may still use Nvidia’s GPU for training neural networks.

Let’s use mobile application development as an example. One of the reasons mobile is a duopoly between Android and iOS is that developers can only learn so many tools and development environments before the process becomes inefficient. In order to truly excel at a language, it has to be universal. For instance, Microsoft attempted to launch a Windows phone, which was met by resistance as developers did not care to learn a new operating system that could not prove itself with user adoption. In turn, mobile users did not buy the Windows phone because their favorite applications were not available to download. iPhone’s success was due to iOS developers who learned tools like XCode to create applications. Android became the competing universal language for the remaining manufacturers, such as Samsung, LG, Sony, Pixel, etcetera. The next wave of AI applications and machine learning inferences will follow the same path of limited competition due to development bandwidth. Developers will self-regulate the number of competitors for processing units due to a need for a universal platform that supports all frameworks.

Here’s a quote from Marc Andreessen of Andreessen-Horowitz, one of the most successful venture capitalists in Silicon Valley:

“We’ve been investing in a lot of startups applying deep learning to many areas, and every single one effectively comes in building on Nvidia’s platform. It’s like when people were all building on Windows in the ’90s or all building on the iPhone in the late 2000s.”

There is an even greater need to simplify artificial intelligence and machine learning than exists for mobile standards. There are thousands of variants emerging each year in AI as neural networks evolve and expand in depth, complexity and architecture. There are multiple frameworks supported by major industry players and Nvidia’s GPUs are flexible enough to accelerate all of these frameworks and workflows including Caffe2, Cognitive Toolkit, Kaldi, MXNet, PaddlePaddle, Pytorch and TensorFlow.

In addition, AI occurs beyond the cloud and Nvidia’s GPUs are available in what is called edge devices, such as self-driving cars, desktops, workstations, data centers and across all major cloud providers.

Conclusion

Nvidia is already the universal platform for development, but this won’t become obvious until innovation in artificial intelligence matures. Developers are programming the future of artificial intelligence applications on Nvidia because GPUs are easier and more flexible than customized TPU chips from Google or FGPA chips used by Microsoft. Meanwhile, Intel’s CPU chips will struggle to compete as artificial intelligence applications and machine learning inferencing move to the cloud. Intel is trying to catch-up but Nvidia continues to release more powerful GPUs – and cloud providers such as Amazon, Microsoft and Google cannot risk losing the competitive advantage that comes with Nvidia’s technology.

The Turing T4 GPU from Nvidia should start to show up in earnings soon, and the real-time ray-tracing RTX chips will keep gaming revenue strong when there is more adoption in 6-12 months. Nvidia is a company that has reported big earnings beats, with average upside potential of 33.35 percent to estimates in the last four quarters. Data center revenue stands at 24% and is rapidly growing. When artificial intelligence matures, you can expect data center revenue to be Nvidia’s top revenue segment. Despite the corrections we’ve seen in the technology sector, and with Nvidia stock specifically, investors who remain patient will have a sizeable return in the future.

Posted in AI Stocks, Cloud Infrastructure, Data Center, Semiconductors, Tech StocksLeave a Comment on Holding Nvidia Stock Will Pay Off Due to Two Impenetrable Moats

Prediction: Here’s Why Roku Will Be The Next Tech Darling

Posted on November 7, 2018June 30, 2026 by io-fund
Prediction: Here’s Why Roku Will Be The Next Tech Darling

Roku’s earnings report for Q3 is scheduled on a potentially volatile trading day depending on how the broader markets react to the mid-term elections. The uncertainty around this outcome, along with rising rates, geopolitical trade uncertainty, and a host of companies tempering their Q4 outlook has caused a style rotation, which has pummeled tech stocks. Regardless, Roku is a mid-cap growth stock in the tech sector that will continually prove itself against headwinds as the company is poised to become one of the most opportunistic growth stories in the market by 2023.

The reason for this is simple: connected TV advertising combines the high engagement of traditional television with the audience targeting capabilities of mobile. These previously two competing forces will combine to create the next advertising phenom, and Roku will emerge as the tech darling of this ever-important shift in ad dollars.

Pay TV Attrition is a Blood Bath

Pay TV has had better decades. The peak for Pay TV user growth in the United States occurred in 2011 when it began an inevitable erosion due to bloated, costly monthly packages, a lack of flexibility for on-demand, and advertising-stuffed programming choices. The following year, pay TV subscribers fell by 8,000 in 2012, which accelerated to 164,000 subscriber losses in 2014. Three years later, those losses grew 20x to a staggering 3 million subscribers (source: Leichtman). And by 2023, live-linear OTT video subscriptions will surpass traditional broadcast TV[1].

Cord-cutters have driven a formidable marketplace. In fact, the global OTT devices and services market will reach $165 billion in 2025 compared to $29 billion in 2015[2].

Also Read : Update on $ROKU – Will Roku Miss Earnings?

“All TV is now OTT” –ABI Research

Roku offers the most synonymous OTT business model with cable and satellite TV providers and can capitalize long-term on this massive subscriber loss by leveraging its advertising, audience development and content distribution services, which make up 89% of gross margins from the platform. As of Q2 2018, if Roku were a traditional cable TV company, the 22 million active subscriber base would rival Comcast as second largest distributor of content in the United States. Only AT&T has more with 47 million DirecTV subscribers. Compare this to Charter Communications, which has a $65 billion market cap and only 16 million users or Comcast with a $171 billion market cap with the aforementioned 22 million subscribers. Roku’s market cap is at $6 billion with shares priced at $56 with the same number of users as Comcast.

The Next Phenom in Tech is Connected TV Advertising

I’ve covered Roku extensively in previous analysis including strengths on how the company is vendor agnostic, player vs platform revenue and the company’s global potential. Connected TV advertising, however, is by far the most important piece for Roku’s trajectory.

Bear with me here as I talk about some of the problems and technicalities in the advertising industry, and why Roku is well positioned.

As Digiday puts it, “Two of the big trends in digital media aren’t compatible: The drive to enforce viewability standards and the shift to mobile, particularly apps.”

Viewability issues are a serious issue for big brands who are averse to mobile in-app advertising because it’s too challenging to track. In addition, many big brands do not need immediate purchases which is called “purchase intent” – which is mobile’s main value over television.

For instance, Coca-cola doesn’t expect you to buy a soda immediately after seeing an ad. Audi doesn’t expect you to buy a car immediately either. So, a lot of the benefits of mobile aren’t worth the downside to these big brands. Advertising budgets shifted to mobile because they had to find audiences, not because it’s a superior method to advertise.

Also Read : Roku Q3 Earnings: Choppy But Unshakeable Long-Term

Here’s how the two compare:

  • Pay TV has high completion rates as viewers are comfortable in their homes and better prepared to receive advertisements.
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  • Mobile offers audience data to better target viewers based on individual preferences.
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Connected TV advertising, which is Roku’s specialty, combines the best of both television and mobile. It offers 100% viewability and completion rates with the audience data and dynamic ad insertion found on mobile. Forbes covered this in a recent article which stated Ad Supported OTT is the future reporting OTT ads have a 97% completion rate and 100% viewability.

In a recent study by FreeWheel, 200 billion video starts found OTT ads had ballooned from 2% to 32% in a four-year period due to heavier investments from advertisers.

In the Q2 2018 Video Advertising benchmark study released by Extreme Reach, a tech platform for video ad campaigns, connected TV impressions overtook mobile, accounting for 38 percent of all video ad impressions down from 33 percent in Q1.

Here’s a quote from Extreme Reach:

“CTV is clearly on the path to becoming the dominant platform for media consumption, and premium inventory is the most sure-fire audience draw.”

– Mary Vestewig, Senior Director, Video Account Management at Extreme Reach.

AppNexus, the world’s leading independent advertising technology company, announced in July of 2018 that advertiser spend in its connected TV marketplace grew 748% year-over-year versus the second quarter of 2017 and 68% quarter-over-quarter. AppNexus currently sees 20 billion monthly connected TV impressions per month.

From an investment standpoint, the implications of attracting more advertising dollars than mobile is enormous. Big brand budgets have been looking for a solution to traditional television that isn’t confined to the attention span and limited screen size of mobile viewers. With Roku, that option is finally here.

Also Read : Roku’s Stock Price: Will There Be Another Pullback?

Subscriptions are Saturated

Subscription video-on-demand (SVOD) comprises 40 percent of the OTT market with the majority of the revenue coming from the United States. By 2022, SVOD penetration will be 132% of US TV households with many homes having more than one SVOD platform[1].

Total SVOD is expected to reach 171 million by 2022 – up from 59 million in 2016 reflecting a 53% increase.

Previously, viewing data and ratings on SVOD (subscription video on demand) such as Netflix (NFLX), Hulu Plus, and Amazon Prime and other OTT content was not disclosed even by Nielsen (NLSN). However, in a recent interview, Nielsen COO Steve Hasker revealed four previously undisclosed statistics about SVOD such as 89.5% of SVOD content is primarily viewed on the television glass whereas 11.5% is viewed on smartphones and tablets.

Of this time, 80% is spent on catalog programming whereas 20% is spent on original content. For definition purposes, Netflix is original content and something Roku or Amazon Prime offers is considered catalog programming.

Meanwhile, as competition increases, the costs for original programming are escalating with Netflix spending $8 billion in 2018 in order to remain competitive for a small piece of the pie (20% of how time is spent).

Roku has held firm on not creating original programming and the statistics support this. The costs for original programming are likely to escalate as HBO, Showtime, Apple, and now Disney developing its own channel for 2019, will continue to compete for this space.

In addition, subscribers pay for quite a few premium $8+ subscription channels, which will eventually lead to subscription fatigue – not to mention mitigate the reason cord-cutters leave pay TV services – which is to lower costs. For a subscriber with YouTube TV ($40) and three premium channels ($24-26), they are paying $65+ per month. This pricing will meet resistance by cord cutters and ad-supported OTT will continue to be a solid choice for viewers.

Conclusion:

Roku is executing on a market trend that will defy typical growth trajectories. Brand budgets are migrating towards Connected TV as a superior method of advertising over mobile. The Roku Channel launched in October 2017 and is already a top 5 channel by active account research. Investors should keep a close eye on platform revenue, which was up 96% YoY to $90.3 million in Q2. The trailing 12-month ARPU in Q2 increased 48% YoY to $16.60 and was “driven by strong growth in video advertising as we continue to capture more share of TV ad budgets,” as the company stated in their shareholder letter.  Due to connected TV advertising trajectories, I am long on Roku for the next 3-5 years.

Click here for more information on why Roku stock will reach $100 in the next two years.

All analysis contained herein should be appropriately credited to Beth Kindig.

Posted in Ctv, Media, Svod, Tech Stocks, Tech StocksLeave a Comment on Prediction: Here’s Why Roku Will Be The Next Tech Darling

Can Programmatic Ads Save Spotify?

Posted on November 2, 2018June 30, 2026 by io-fund
Can Programmatic Ads Save Spotify?

Summary: According to Q3 earnings calls, Spotify may seek to broker user data in order to keep average revenue per user afloat. Known as programmatic advertising, this method of monetizing data to supplement music revenue may be Spotify’s only hope to stave off competitors who nip at the heels of the music-streaming app

Portions of this article were originally published September 27th, 2018 under 8 Reasons Spotify will be a Sell Recommendation by 2019 at $184 per share. This analysis has been updated to include the recent partnership with Google and programmatic offering Ad Studio.Spotify will be a Sell Recommendation by 2019 at $184 per share. This analysis has been updated to include the recent partnership with Google and programmatic offering Ad Studio.

Half Full or Half Empty? -6% ARPU in Q3 Compared to -12% ARPU in Q2

Spotify Technology met its Q3 forecast for paying subscribers and a few other metrics, but average revenue per user declined due to promotional accounts for families and students. Spotify ended the period with 87 million Premium subscribers worldwide, up 40% year-over-year. Spotify has 109 million monthly active users of its advertising-supported streaming service, up 8 million from Q2 or 20% YoY.

This quarter, Spotify’s average revenue per user percentage has improved but QoQ growth is still in the red. Average revenue per user declined to $5.50 in Q3 from $5.83 in Q2, or -6% following -12% the previous quarter.

Costly Partnership with Google

Spotify lacks the razor-razor blade Gillette analogy for tech companies, which in this case states you should have ownership of a device if you want to bank on the subscriptions. This is one reason I’ve been long on Roku since its IPO. Roku players are the cheap razors that will deliver the razor blades of ad-supported content in the OTT market. (You can read my analysis on Roku here). However, this lack of device ownership is causing trouble for Spotify. Smartphones dominated by Apple and Google are only part of the story. At home assistants such as Alexa are being designed and leveraged specifically for AI activated music services. To get a glimpse of Spotify’s future, consider that major record labels let Amazon offer a reduced Alexa version of the premium service at $3.99 per month and Apple is requiring users to sign in to Apple Music to power the HomePod – which completely shuts out devout Spotify users.

Spotify’s new strategy is to partner with Google to offer free Google Home Mini speakers to users who subscribe to the Family plan as part of a holiday season promotion. The partnership comes at a cost of approximately 50 basis points to the Gross Margin profile in Q4, the company noted. From Google’s standpoint, they get their entry level smart speaker into more homes, while Spotify benefits by having a partner for smart home infrastructure. Ultimately, this is one example of the lengths Spotify will have to go to in order to compete with Apple and Amazon on their home turf.

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Apple has Homefield Advantage

Most certainly, Apple won’t be beat in its own ecosystem. Apple revolutionized digital music with the iPod and iTunes. With smartphone penetration, the Beats acquisition, its Homepod ecosystem and a huge push into connected car infotainment, Apple can surround Spotify in nearly every direction. Keep in mind, that 66% of the world’s paying app users are iPhone users who trend towards higher incomes (vs. only 34% on Android), so Apple users are supremely important for Spotify’s $9.99 subscriptions.

In fact, the turf war has already receded Spotify’s market share. Record industry sources state Apple is adding paying subscribers at a rate of 5 percent in the U.S. versus 2 percent for Spotify, and that Apple Music may have already taken over Spotify as the number one streaming service in the United States.

In addition, Apple was cleared to complete the acquisition for UK-based music recognition app Shazam Entertainment for $400 million. Due to the threat this poses to Spotify and other smaller apps, regulators in seven countries contested the acquisition when Apple’s plans were first announced. Despite these efforts, the acquisition was approved in August of 2018. To date, Shazam has had well over 1 billion downloads, last reported in 2016, and owns a wealth of information on what music is trending with over 20 million searches per day.

Can Programmatic Ads Save Spotify?

Tim Cook is a chief critic on how applications and websites use private data to increase the accuracy of targeted advertising. Therefore, one area Apple clearly won’t compete is in the brokering of programmatic ads based on users’ music choices. Meanwhile, Spotify has every intention of letting advertisers target its users through Ad Studio.

Spotify would not be the first mobile application to supplement its core product with a programmatic offering. Facebook and Twitter owe at least 1/6thto 1/4thof their current revenue to programmatic proving it can substantially increase average revenue per user. Therefore, if Ad Studio is executed correctly, it may have the potential to limit stock losses even with stiff competition from Apple and Amazon.

Here’s a statement from Spotify’s press release:

“Last quarter we said that we expected our Programmatic and self-serve products to become a significant portion of our Ad-Supported revenue. If we’re successful in achieving this shift in revenue mix, then we also expect to achieve significant operating leverage in the ad sales business, increasing our operating margins. Last quarter we reported on our new automated self-serve platform, Ad Studio, which is live in the US, UK, Canada, and Australia. Ad Studio revenues are still quite small, but we’re seeing exponential growth, so expect to hear more about this product in future quarterly updates.”

Note About Tencent Music IPO:

Spotify owns Tencent Music Entertainment (TME) shares and it’s been stated in past financial reports that “a TME IPO would trigger a fair market value adjustment to the carrying value of our investment recognized in other comprehensive income. The gain could be significant.”  This one-time, non-recurring event would generate a Net income for Spotify with a Net loss returning in the following quarters. Spotify stock holders should be aware that this one-time wave may be worthwhile to hold on for, but that the long-term prospects of the company are still not proven.

Conclusion

Spotify is a small fish in deep waters. Q3 earnings prove music streaming is a tough business. The company is attempting to partner with device owners, like Google, but these partnerships will eat away at Gross Margins in future quarterly earnings. I’m forecasting that Spotify will be in sell status through 2019 unless they can prove themselves with a strong programmatic offering through Ad Studio. Note the Tencent Music IPO will generate a net income for Spotify in the current quarter.

You can access more analysis on Spotify here.

This article and previous Spotify analysis written by Beth Kindig has been published on Seeking Alpha. All original analysis contained herein should be appropriately credited to Beth Kindig.

Posted in Applications, Digital Ads, Media, Mobile, Software, Tech StocksLeave a Comment on Can Programmatic Ads Save Spotify?

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