Apple vs. Spotify – Duck lines

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Two lines of ducks are forming.

  • With a new alliance between Spotify and Tencent and the acquisition of Shazam by Apple, the big players are getting their ducks in a row to dominate the global music industry.

Spotify and Tencent

  • Following on from Tencent’s failure to acquire the company (see here), a compromise has been reached where the two companies will acquire a cross holding in each other and “explore collaboration opportunities”.
  • To me this means two things:
    • First: Tencent will be able to integrate the Spotify service into the ecosystem experience that it assembles to enable it to address developed markets.
    • This could form part of an offering that also has a gaming offering using Supercell and an instant messaging offering using Snapchat.
    • Second: I expect that Tencent will get access to Spotify’s best in class music categorisation and recommendation system for use in making its Chinese service better.
    • For this I expect that Spotify will receive a revenue share from Tencent as I think it very unlikely that Spotify has any real chance of succeeding in China on its own.
    • This is because Tencent’s QQ music is already the leader with 41% share and because like everything else, China’s music market is predominantly about Chinese music for Chinese users.
    • The Chinese music market has been tiny historically, but this is beginning to change as the more affluent end of the market is beginning to pay for streaming services.
    • Consequently, the Chinese market is almost all digital with only a tiny physical presence.
    • It is this change that I think has interested Tencent in Spotify’s technology as technology is what I have long believed underpins Spotify’s superior performance relative to Apple Music enabling it to keep Apple at bay.
  • A close collaboration between Spotify and Tencent could mean a fully global offering with the exception of India which would probably require an acquisition to get a foothold.


  • At the same time, it seems likely that Apple has reached a deal to acquire Shazam, the music recognition company, for $400m.
  • This is well below the $1bn valuation at which Shazam raised money in 2015 but in 2015, there was a much greater supply of belief.
  • The issue that Shazam has had is that it has had great difficulty in making money as 2016 revenues appear to have been around $50m with the company hovering around break-even.
  • I suspect that the company has not grown nearly as quickly as it expected which has meant that profits expected by investors have not materialised making them willing to consider a lower offer.
  • From Apple’s perspective, I do not see this as an acquisition of a service but much more a technology.
  • Shazam has been analysing and recognising music for nearly 20 years and as a result is pretty good at characterising, recognising and understanding music.
  • This is one of the traits that makes Spotify’s service so good as it is able to take that and match it to users’ tastes.
  • Consequently, I see Apple taking Shazam’s technology and incorporating it into Apple Music in a bid to improve its service and compete more aggressively with Spotify.
  • I continue to believe that the best way for Apple to do that would be to introduce a free tier, but that is a whole other discussion (see here).
  • This is great news for SoundHound as the loss of independence of its major rival will make it far more appealing to anyone who competes with Apple at any level.

Take Home Message

  • Streaming has reversed a long decline in music industry revenues and consequently is widely considered likely to become the standard way to distribute music.
  • I still think that the market is big enough for two players to thrive and Apple and Spotify remain at the top and look unlikely to be seriously challenged.
  • Hence, these recent moves look to be aimed at cementing the position of the two leaders ensuring that streaming remains a duopoly outside of China and India.

Qualcomm & Microsoft – Dream with caveats.

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Some space left for this proposition

  • Windows on ARM is back for another crack at the PC market and while I can see a place for it, it is unlikely to cause Intel too much grief.
  • Microsoft and Qualcomm have launched a series of laptops that are running Windows 10 on Qualcomm’s SnapDragon 835 chipset.
  • In addition to offering better battery life, the presence of the chipset enables the always-on functionality and connectivity that users are used to with smartphones and tablets.
  • If that were all that there was to this story, then I would be pretty sure that Qualcomm would quickly take over the PC market but, as always, the devil is in the details.
    • First: Software compatibility: Many of the devices will ship with Windows 10S (for which they are best suited) but will be upgradeable to the full version of Windows 10.
    • Microsoft has compiled Windows 10, Edge and shell to run natively on ARM and had also recompiled a series of DLLs (dynamic link libraries) to ensure that the major desktop applications run properly.
    • For everything else, Microsoft has created an emulator (generally a big drain on performance) that will allow other third-party apps to run with some exceptions.
    • These are: 64bit apps won’t work yet, kernel mode drivers are not supported which means that most antivirus and games that use DRM or anti-cheat software wont work properly.
    • This means that buyers of these devices will not be able to be 100% certain that everything they might want to run will work.
    • I see this as a big sticking point, as failure to perform as expected will infuriate users and create a lot of bad press around these products.
    • This is the same concern that I had around the launch of Windows 10S which I continue to think makes some sense in the classroom but nowhere else (see here).
    • Second: performance. These devices need to perform as well as Intel devices in their pricing tier otherwise buyers are likely to be put off.
    • Given that Intel has much higher gross margins than Qualcomm in silicon, this might be achievable, but it will also depend on the quality of the implementation by the PC makers themselves.
    • Third, market dynamics: The PC market has changed dramatically over the last few years as casual users have deserted the platform.
    • This is because, these users predominantly used a PC for browsing, email and media consumption and smartphones and tablets offer a more convenient and better way to conduct these activities.
    • Consequently, these users have ditched the PCs that they owned and replaced them with smartphones and tablets instead.
    • It is this that I have long believed has been mostly responsible for the softness that has been observed in the PC market over the last 5 years.
    • This trend also means that the users that are left are much more focused on the functions that PCs do really well like content creation and high-end gaming.
    • For these users, performance is critical, and I suspect that Windows 10 on ARM will not be powerful enough for them.
  • This leaves Windows 10 on ARM somewhat in limbo but for students, schools and very price sensitive users, this may represent a good option.
  • Hence, if Intel is going to feel any heat from this, it is going to be at the very low end of the market which is not where it makes most of its money.
  • The amount of traction that these devices get depends mostly on their price and the quality of the implementation by the PC makers but I think that it is pretty clear that the performance driven end of the PC market is almost certain to remain Intel’s

Artificial Intelligence – Zero to hero.

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DeepMind AlphaZero is smarter with 1000x less effort.

  • DeepMind has taken another step forward in the quest for machine intelligence with the demonstration of the rapid training of a single algorithm to play Chess, Go and Shogi.
  • While this is without doubt another step forward, I do not consider that the second major challenge in AI is close to being solved.
  • RFM has identified three main challenges that need to be overcome for AI to really come of age (see here).
  • These problems are:
    • First: the ability to train AIs using much less data than today,
    • Second: the creation of an AI that can take what it has learned from one task and apply it to another and
    • Third: the creation of AI that can build its own models rather than relying on humans to do it.
  • DeepMind’s previous publication took a shot at problem one (see here) and while it represented an advance, I did not consider it to have really solved the problem.
  • Its current publication (see here) takes a shot at problem two, but again has made an advance, but in my opinion, has not really cracked the problem.
  • DeepMind describes a new algorithm called AlphaZero which is a generic version of AlphaGo Zero (Go algorithm (see here)).
  • It uses a deep neural network instead of the specific policy and value neural networks that were designed to play Go in AlphaGo Zero.
  • AlphaZero is then given the rules of Chess, Shogi (Japanese version of Chess) and Go and asked to play itself and to use reinforcement learning to improve.
  • In each case AlphaZero was quickly able to obtain a level of play that allowed it to beat the best algorithm available in each of the three games including the original AlphaGo Zero.
  • It is also highly relevant that AlphaZero did far less “thinking” than its opponents.
  • Each machine was given 1 minute of thinking time and during that time AlphaZero searched 80,000 positions per second for chess and 40,000 per second for Shogi while Stockfish (Chess) searched 70 million per second and Elmo (Shogi) searched 35 million per second.
  • In effect, AlphaZero expended 1000x fewer resources to arrive at a better solution than its opponents due to its use of its deep neural network to tell it where to search.
  • The ramifications for this are substantial as it implies that once trained, algorithms could be easily and efficiently executed on mobile devices where resources remain extremely constrained.
  • However, it is critical to recognise that for each game, DeepMind trained a different instance of AlphaZero.
  • DeepMind started with three instances of AlphaZero which were all identical other than they each had the rules for a different game.
  • However, through playing themselves and reinforcement learning they all diverged from one another as they gained expertise in the specific game they had been asked to play.
  • The end result is that despite a common starting point, the three algorithms become very different by the time that they are capable of playing these games at a very high level.
  • Consequently, to me this does not represent the solution to problem two because one cannot take the Chess version of AlphaZero and have it win at Shogi.
  • However, what it does do is represent a major step forward in the training of algorithms as the AlphaZeros all trained themselves and they all came from a common starting point.
  • This should make training of algorithms in the future easier, quicker and cheaper than they are today which is why this is yet another very significant advance that has been made by DeepMind.
  • Seeing that DeepMind is owned by Google, it is Google Ecosystem devices and services that are likely to benefit from these advances long before anyone does.
  • This will allow Google to differentiate its services more effectively and make them more appealing to users.
  • We gave already seen signs of this where Google is able to do portrait mode with one camera when everyone requires two.
  • This reconfirms my position that it is Google that leads the world in AI developments for digital ecosystems with Baidu and Yandex in 2nd and 3rd
  • Given, Alphabet’s exceptional stock performance this year, Baidu now makes the most interesting and cost-effective entry point for anyone looking to gain exposure to AI.

Google & Amazon – Battle for the smart home pt. V.

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Google has a chance to displace Amazon.

  • I don’t think Google will go out of its way to patch things up with Amazon as having YouTube absent from Amazon devices could disincentivise users from going with Echo products giving Google Home a badly needed boost.
  • Google and Amazon have been sparring for several months but I think that the move by Google to pull YouTube off Amazon ecosystem devices may bring this issue to a head.
  • It is also a demonstration that content is king and as of today, YouTube is amore important platform than Amazon Prime Video.
  • Consequently, I think that Amazon needs YouTube on its devices more than Google does as users will simply go elsewhere to get it.
  • This sparring began three months ago when YouTube pulled its native support from the Amazon Echo Show.
  • This was followed by the removal of Nest products from the Amazon website and the implementation of a clumsy and far from ideal workaround to get YouTube content back on the Echo Show.
  • Google has closed this loophole as of today and will also pull support from Fire TV from Jan 1st
  • This battle between Amazon and Google is peripheral to their core businesses as even in video, they do not really compete directly.
  • YouTube is an encyclopaedia of user generated content while Amazon Prime Video is just like Netflix.
  • Google does have YouTube Red but this is a tiny part of YouTube overall.
  • Consequently, I think this fight is all about the home and here Google is way behind Amazon despite having the better product (see here).
  • This is because Amazon has been much better showing developers love and as a result they have preferred to develop their smart home products for Amazon Alexa.
  • The result has been that almost every device sold will work with Alexa with only a few working with Google.
  • This has changed over the last 6 months but Amazon’s ability to advertise its products on its website as well as giving its cheapest product away for free has allowed it to maintain its lead.
  • With the critical holiday selling season upon us, this is a great time to throw a spanner into Amazon’s works as not working with Google services is going to be a problem for the vast majority of users and may push them to consider Google Home.
  • I still see Google as being on the backfoot when it comes to the smart home but it has closed some of the gap to Amazon in terms of third parties and it remains a superior product.
  • This will be a key battle that is played out in 2018 and the level of support offered by device and service developers when they show their wares at CES in January will be a key indicator.
  • The market remains very lowly penetrated and so there is everything to play for but I still think that in the long-run Google should win as it has the better product.
  • I will revisit this position again once it becomes clear which way smart home developers are inclining for their 2018 product launches.

Xiaomi – Market timing

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Xiaomi considers a big equity event just as growth peaks again.

  • Xiaomi’s genius for timing is confirmed as talk of an IPO is beginning to ramp up just as its recovery growth rates are about to peak.
  • However, this time around, profitability will be open and clear for all to see and it is here where I think the problems will arise.
  • To be fair to Xiaomi, it has executed extremely well and has been rewarded with a period of very rapid growth as its strategy to distribute through methods other than the Internet and to focus on India has paid off in spades.
  • According to Counterpoint, Xiaomi’s performance really turned around in Q2 17A where YoY growth in smartphone shipments went from -8% in Q1 17A to 59% YoY in Q2 17A.
  • This was a result of three big changes implemented by Xiaomi.
    • First: new products. The new flagship Mi 6 launched at the beginning of the quarter was well received and looks to have been the backbone of the recovery.
    • Second: retail channel. I have long been of the opinion that Xiaomi ground to halt because it had fully exhausted the capacity of selling devices over the internet.
    • In order to address a wider slice of the market, Xiaomi has invested heavily in retail with 123 MI stores opened across China and the first results from this push are now being seen in the numbers.
    • Third: India and overseas: Investments in India are beginning to pay off with the Redmi Note 4 becoming the biggest volume smartphone in Q2 17, elevating Xiaomi to No. 2 in India.
    • By far the largest part of Xiaomi’s overseas fan base is to be found in India and this should help the fan base to grow further.
    • However, India can be one of the most fickle markets as it is so price driven and as many Indian brands have found, success can be all too brief.
  • While growth is clearly back at Xiaomi, the comparisons to the torrid time it had in 2016 are really easy as after Q2 2018, growth is likely to slow substantially as the comparisons to the previous year will become much more challenging.
  • Consequently, sometime in H1 2018 is the perfect time to achieve the best possible IPO price as growth will then be at its highest.
  • However, the big question mark for me is profit, as it is through profit alone that an equity based investment can have any value at all.
  • Here, I am still very cautious as Xiaomi’s strategy is based on providing good quality hardware at a great price.
  • This combined with the fact that it does not have Samsung’s scale in handsets means that it is very unlikely to make more than a commodity margin.
  • When I am as kind as I can be to Xiaomi, I can assume that its smartphone ASP is $270 on 118m units shipped in 2018 with $5.4bn in revenues from smart home products.
  • Assuming an EBIT margin of 5%, this gives me 2018 revenues / EBIT of $37.31bn / $1.87bn implying an EV / Sales multiple of 1.3x and EV / EBIT of 26.7x if the company is valued at $50bn.
  • For an EV / Sales valuation, this is not difficult to reach as Apple is trading on 2018 EV / Sales of 2.7x and Xiaomi is growing faster.
  • However, as I have said above, equity valuation is about profit with revenues being used as proxy when there are no profits.
  • Using EBIT, a very different picture emerges as Apple is trading on 8.4x EV / EBIT and at $50bn, Xiaomi would be on 26.7x.
  • Xiaomi is growing faster than Apple but this is unlikely to last very long and its efforts to build a software ecosystem have been crushed by the BATmen at home and are irrelevant overseas.
  • Hence, it has very little with which to differentiate its wares meaning that it has to compete almost entirely on price.
  • Consequently, the most I would be willing to even remotely consider paying for Xiaomi would be double Apple’s EV / EBIT multiple which would give a valuation of $31.3bn, some 37% below the mooted $50bn.
  • To get to $50bn, Xiaomi would need to put up EBIT margins of at least 8.0% which I think is a stretch given the company’s strategy of selling great hardware at good prices.
  • The advantage of an IPO is that these facts will all be laid bare long before investors have to commit to buying the shares.
  • I suspect that its lack of profitability will keep it from going public until it is capable of putting up much bigger profit numbers.



Google – Brain game pt. II.

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Google remains out front in AI but Baidu most interesting. 

  • The first results from Google’s AutoML project are beginning to surface and are implying once again (see here) that machines may end up being better coders than humans.
  • AutoML was announced at Google i/o in May 2017 and failed to attract much attention mainly because I suspect that most commentators did not grasp the significance of the concept.
  • AutoML is neural network that is capable selecting the best from a large group neural networks that are all being trained for a specific task
  • This is potentially a hugely important development as it marks a step forward in the quest to enable the machines to build their own AI models (challenge no. 3 (see below)).
  • Building models today is still a massively time and processor intensive task which is mostly done manually and is very expensive.
  • If machines can build and train their own models, a whole new range of possibilities is opened-up in terms of speed of development as well as the scope tasks that AI can be asked to perform.
  • RFM has highlighted automated model building as one of the major challenges (see here) of AI and if Google is starting to make progress here, it represents a further distancing of Google from its competitors when it comes to AI.
  • In the subsequent months since launch, AutoML has been used to build and manage a computer vision algorithm called NASNet.
  • AutoML has implemented reinforcement learning on NASNet to improve its ability to recognise objects in video streams in real time.
  • When this was tested against industry standards to compare it against other systems, NASNet outperformed every other system available and was marginally better than the best of the rest.
  • I think that this is significant because it is another example of when humans are absent from the training process, the algorithm demonstrates better performance compared to those trained by humans.
  • The previous example is AlphaGo Zero (see here).
  • I see this as a step forward in addressing RFM’s three big challenges of AI (see here) but there remains a very long way to go.
  • These problems are:
    • First: the ability to train AIs using much less data than today,
    • Second: the creation of an AI that can take what it has learned from one task and apply it to another and
    • Third: the creation of AI that can build its own models rather than relying on humans to do it.
  • When I look at the progress that has been made over the last year in AI, I think that Google has continued to distance itself from its competition.
  • Facebook had made some improvements around computer vision, but its overall AI remains so weak that it is being forced to hire 10,000 more humans because its machines are not up to the task (see here).
  • Consequently, I continue to see Google out front followed by Baidu and Yandex with Microsoft, Apple and Amazon making up the middle ground.
  • Facebook remains at the back of the pack and its financial performance next year is going to be hit by its inability to harness machine power.
  • For those looking to invest in AI excellence, Baidu is the place to look as its search business and valuation has been hard hit by Chinese regulation but is now starting to recover.
  • Baidu represents one of the cheapest ways to invest in AI available.

Digital sensors – Heart of the matter.

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Apple is creeping up on the medical devices industry. 

  • Apple has taken wearables a step closer to replacing medical devices, but the user experience is still so limited that the immediate term for the medical, devices industry still looks secure.
  • KardiaBand (AliveCor) is a strap for the Apple Watch which incorporates in it a sensor that is capable of producing a full electro cardiogram (ECG).
  • Critically this accessory has been approved by the FDA meaning that it is good enough to be a medical device producing medical data that can be relied on by a doctor.
  • The Apple Watch app that comes with KardiaBand can use the heart rate sensor on the Apple Watch to detect abnormalities and recommend to the user that he records his ECG.
  • Atrial fibrillation is a leading cause of stroke and it is thought that 66% of strokes could be prevented with early detection.
  • It is the signs of this that the KardiaBand app is looking for via the Apple Watch sensor which can then be confirmed through the recording of an ECG.
  • This does not come cheap at $199 for the band and $99 per year for the monitoring service, but if it works as advertised, I think it is a tiny price to pay for avoiding a stroke.
  • However, the use case is not ideal requiring a large metal plate to be present in the device’s strap and it does not offer always on monitoring.
  • This combined with its price means that it will only really appeal to users who are known to be at risk from stroke and it does not enable the replacement of an existing medical device.
  • I see the combination of Apple Watch and KardiaBand as a halfway house as it does not really offer real time monitoring to a medical grade, but it is a step in the right direction.
  • Sensors are becoming the eyes and ears of AI (see here), but almost all sensors are not nearly good enough to produce data that can be used in critical applications.
  • Nowhere is this more true than in eHealth where inaccurate data is useless at best and deadly at worst.
  • This is why there is still a big market for extremely expensive medical monitoring equipment, but I see signs everywhere that this will eventually come to an end.
  • This also explains the problems that the likes of Fitbit, Xiaomi, Garmin and others are having as the data they generate is of such low quality that it can really only be used for recreational fitness.
  • eHealth is where the quest for accurate data begins but I see this quickly spreading to other industry verticals.
  • Accurate sensors are one way to attack this problem but the other is to use better software to clean up and improve less-than-perfect data sources.
  • Google is a good example of this as it can use software to produce better imaging effects in portrait mode with one camera than Apple can with two (see here).
  • Given the substantial rewards that are on offer, I think that investment in improving the quality and accuracy of sensors will only continue to increase in the coming years.
  • This is an area where I would want to be involved.
  • The issue, of course, is to separate the solutions that have real prospects from those that are merely riding the wave of hype and easy investment.

Amazon – Size 12s

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Amazon is stomping on Microsoft’s patch.  

  • With the launch of Alexa for Business, Amazon is stomping with its size 12s all over the territory of its supposed new best friend, Microsoft and its digital assistant, Cortana.
  • Alexa for Business is expected to be launched next week at the AWS reinvent conference and will allow businesses to build their own skills for the digital assistant that can be used in a work context.
  • It will also feature all of the normal functionality such as enquiries and smart office and is expected to feature partners like Concur and WeWork at launch.
  • This has the scope to both generate more skills and applications for the Alexa digital assistant but also to generate increasing loyalty to AWS.
  • Some of these skills are likely to include integration with Office functionality such as calendar management, meeting room scheduling and so on.
  • If this takes off, there is no reason why this should not spread to the desktop and deeper into Microsoft’s core asset Office.
  • The issue here is that Microsoft already has a digital assistant called Cortana, and with Microsoft’s increasingly dominant position in the enterprise, this would seem to be an obvious opportunity for Cortana.
  • However, Cortana is struggling because it was originally designed to run on Windows Phone meaning that many of the skills that it has been taught are not relevant with the assistant sitting on the desktop.
  • Furthermore, Amazon and Microsoft recently announced a partnership where users will be able to ask Alexa to ask Cortana to do something and vice-a-versa.
  • Given Microsoft’s focus on the enterprise, I have been under the impression that the future for Cortana would be in the enterprise where it can be deeply integrated into Microsoft’s market leading apps.
  • At the same time, I assumed that the partnership would offer Amazon a way to use Alexa on the PC and in the enterprise.
  • However, it seems that Amazon is short-cutting its partner by going for the enterprise completely independently of its partnership with Microsoft.
  • The one area where Microsoft has a more relevant product than Amazon is in AI, where RFM has estimated that Microsoft is ahead of Amazon.
  • Consequently, I can see an eventual collaboration where Microsoft’s AI is used to drive Alexa’s services in the enterprise.
  • The only problem here is that this could result in cross over between Microsoft and Amazon Web Services who are fierce competitors in the cloud.
  • Hence, a deepening of this collaboration looks increasingly unlikely as this move puts Amazon against Microsoft in a new area in addition to the cloud.
  • Although Amazon appears to be getting the better of Microsoft, I still cannot stomach the valuation leaving me with a strong preference for Microsoft’s shares.

Uber – Annus horriblis

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Even at $54bn, no shortage of sellers.

  • While attention is focused on SoftBank’s moves to take a 13-15% stake in Uber, the deterioration of Uber’s fundamentals is a warning that its dominant position may already be slipping.
  • Q3 17A revenues were $2.01bn up 21% compared to $1.66bn in Q2 17.
  • However, net losses grew faster with Q3 17A net losses at $1.46bn, up 38% from the $1.06bn it lost in Q2 17A.
  • This represents a deterioration in net margins to a loss of 73% from a loss of 64% in Q2 17A.
  • Given the year that Uber is having (see here) it is possible that the losses have been increased by non-operational items such as compensation payments and restructuring.
  • However, these headline figures come from an investor communication (via Bloomberg) which typically will exclude costs and benefits that come from non-operational sources.
  • Hence, I suspect that the 870bp decline in margins is operational in nature and represents a deterioration in the company’s underlying performance.
  • This should be of huge concern because if its home market is going to descend into a bloodbath of cutthroat competition, then Uber is going to be raising a lot more money and most likely at much lower valuations.
  • I am quite surprised to see such a deterioration as despite Lyft’s recent increases in share, Uber is still hugely dominant in its home market, USA.
  • So far in 2017 Uber’s lack of focus has led to Lyft being able to confidently expect to improve its market share to 33% from 20% at the beginning of the year.
  • This leaves Uber on 66% which based on my rule of thumb for network based businesses, is still enough to eventually win the market, but its margin for error has been substantially reduced.
  • This rule of thumb states that a company that relies on the network must have at least 60% market share or be at least double the size of its nearest rivals to begin really making profit (see here).
  • Coming into 2017, Uber had a 20% cushion before Lyft could really start causing it some problems, but this cushion has now been reduced to just 6%.
  • Uber’s figures are implying that Lyft is beginning to impact Uber’s ability to make money which I think is a real problem.
  • Google is now Lyft’s biggest backer as it represents the best way for it to get its self-driving technology (Waymo) to market.
  • As of Q3 17, Google has $100bn of cash on its balance sheet giving Lyft potentially much deeper pockets than Uber.
  • This combined with how much it has closed the gap on Uber over the last 9 months, means that Lyft is now a real threat.
  • To me, this is a much more important issue because if Lyft is able to impact Uber’s financials, it means that its hallowed status of market dominance has already been lost despite my rule of thumb.
  • This is critical because Uber’s $70bn valuation compared to Lyft on $11bn is based on its dominance of the market and the unassailability of its network effect.
  • Consequently, I feat that the real valuation of Uber may be far lower than even the $54bn that SoftBank is offering existing shareholders to purchase some of their stock.
  • These investors include Benchmark and Menlo Ventures who may have already have arrived at this view and concluded that $54bn is a great exit price.
  • Hence, I still expect there to be no shortage of sellers at this lower valuation.

Verizon / Yahoo – Digital desert.

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No last hurrah for Yahoo.

  • Despite its recent acquisition by Verizon, the decline of Yahoo’s assets seems to be accelerating, further underpinning my long-held position that Verizon substantially overpaid to acquire them.
  • At the same, it also reinforces my opinion that Marissa Mayer’s last actions at Yahoo were by far her best in terms of delivering value to shareholders (see here).
  • Two of Yahoo’s assets are showing accelerating signs of decline.
    • First, Tumblr: Shortly after Yahoo’s $1.1bn purchase in 2013, activity at Tumblr peaked and has been in decline ever since.
    • The change in ownership has made no difference that I have seen.
    • Once Tumblr’s founders and owners had been paid, they had no incentive to continue pushing the platform forward resulting in drift and decay.
    • At its peak in 2014, there were 106m new posts every day which has now collapsed to 35m from where it is still falling.
    • Blog posts (a subset of all posts) has also fallen substantially (45%) to 130,000 per day indicating that key content creators have gone elsewhere.
    • Furthermore, Yahoo has written off $712m of the investment it made, and Tumblr’s founder Alex Karp has announced that he will be leaving at the end of the year.
    • I very much doubt that Verizon has the management bench strength to turn this around leaving the outlook as very bleak.
    • Second, Yahoo Groups: This is a social networking system that is still quite popular with businesses, schools and so on due to its deep integration with email.
    • However, the system has been plagued with technical problems and downtime for over a week.
    • The issues began on November 17th and were not fully rectified until November 25th.
    • Digital Life services upon which users rely need to be as reliable as telecom networks meaning that even downtime of a few hours can have far reaching effects.
    • Taking 8 days to fix basic functionality is unheard of among Internet companies.
    • To me, this is a sign of how little what remains of Yahoo seems to care about retaining usage.
    • As a result, businesses moved their Black Friday promotions to Facebook and many other users are now seeking alternatives.
  • When this is combined with what was the biggest hack in history resulting in the probable compromise of every single account that Yahoo has, it is clear that there is very little point in living one’s life with any of Yahoo’s remaining Digital Life services.
  • Consequently, I expect the drift of users away from the platform, to better and more secure alternatives, to accelerate leaving Verizon with a series of deserted digital properties.
  • On top of Yahoo, Verizon already owns AOL and is trying to rebuild its Go90 mobile video service using the team and assets acquired from Vessel in 2016.
  • The problem I have with Verizon’s strategy is that it was very late to the game meaning that it has ending up acquiring all of the assets that no one else wanted.
  • Furthermore, Yahoo and AOL have both badly failed to generate any traction on mobile but somehow Verizon seems to think that putting all of these together will create a thriving ecosystem.
  • This is of course possible, but if Yahoo was unable to hold onto the talent capable of executing this dream, I think that Verizon has very little chance.
  • This view is supported by the fact that instead of flourishing, the Yahoo assets seem to be accelerating their demise under Verizon’s ownership.
  • The result is likely to be a hefty write down of the assets that it paid $4.5bn for and their eventual closure or distressed sale consigning Yahoo to the annals of history.