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.

Apple

  • 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.

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.

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.

E-commerce – Look East.

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In mobile, China is more developed than USA.

  • Comparing China’s Singles Day against Brown Thursday, Black Friday and Cyber Monday in USA reveals just how much more advanced the development of the mobile online consumer economy is in China.
  • The first figures for Brown Thursday Black Friday are coming in with Adobe estimating that $7.90bn (Gross Merchandise Value, (GMV)) was spent online with another $6.6bn expected to come on Cyber Monday.
  • Of the $7.90bn, 37% of the revenue was produced by a mobile device of which 70% was transacted via a smartphone (26% total turnover).
  • While these figures are the best ever for the USA in terms of total turnover and smartphone share, they pale into insignificance when compared to Singles Day in China.
  • Between them, Alibaba and JD.com make up 87.2% of all B2C e-commerce in China and on Singles Day they racked up $44.7bn in GMV.
  • In just one day Chinese e-commerce turned over 5.7x in GMV than the two US days put together.
  • If one includes the expectations for Cyber Monday, then the total US holiday shopping period is dwarfed by a factor of 3 to 1.
  • Furthermore, 90% of all of Alibaba’s GMV was transacted on a mobile device and AliPay handled a total of 1.5bn transactions.
  • It is clear that a big discrepancy here is that Singles Day a recently created, online-only event whereas Black Friday has been going since 1952 and remains mostly an offline event that’s is slowly migrating to online
  • However, the scale of the difference between the two clearly demonstrates that when it comes to online transactions and mobile, China is far more developed than USA or other developed markets.
  • I have long believed that there are two main reasons for this:
    • First: the offline experience in China is very poor.
    • This is the case for many sectors but particularly in retail.
    • Chinese offline retail is a fragmented and frustrating experience where decent service and information with regards to inventory, product lines and so on is routinely not available.
    • When an online offering appears where this information is clear and one is able to easily purchase goods and know when they will be delivered, shoppers quickly adapt.
    • Hence, Chinese consumers have very quickly adapted to online shopping as the experience and ease of use is far superior to offline.
    • Second: China is a mobile first market.
    • Cellular connectivity in China has better penetration of broadband connections, higher throughput and lower latency than fixed Internet (see here).
    • Consequently, mobile is the first choice for Chinese users as it almost always offers a better user experience.
  • This is also why we have begun to see reversal of the direction of innovation in mobile services.
  • Historically, Chinese companies have copied ideas pioneered in Developed Markets, but this hs changed meaningfully.
  • For example, many of the innovations that are being put into instant messaging platforms by Facebook, Snapchat, Apple and so on are already available in WeChat, LINE, Kakao-Talk etc.
  • This is a trend I expect to continue going forward.
  • China remains dominated by the BATmen of whom I have preferred Tencent for the last 15 months.
  • However, given its rally and its apparent slowness to monetise its ecosystem fully, I am beginning about switching into Alibaba.

 

Uber vs. Lyft – Blood in the water

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This is Lyft’s best chance to catch Uber. 

  • With yet another skeleton emerging to hinder Uber, Lyft is increasing its recent fund raising by $500m as I think it has realised that now is its best chance to reel in Uber.
  • Lyft has increased its recent $1bn round that was led by Google and CapitalG by another $500m bringing the total post-money valuation to $11.5bn.
  • The extra money will be invested in passenger and driver products which I think basically means reducing the fares and increasing driver take-home in a bid to gain market share.
  • 2017 has been a great year for Lyft but only because Uber has pretty much had the worst year imaginable.
  • Constant turmoil, management turnover, bad press, unhappy drivers and a series of scandals has led to the company focusing on anything but its core business in 2017.
  • This has taken another downward lurch with the disclosure that it suffered a data breach on 57m users and failed to make the users aware that their data had been compromised.
  • This is exactly the kind of bad press that Lyft can capitalise on when it comes to tempting existing Uber users to consider trying Lyft.
  • So far in 2017 this has been very successful as 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%.
  • Furthermore, with Google is now backing Lyft as the best way for it to get its self-driving technology (Waymo) to market, this gives Lyft much deeper pockets than it had previously.
  • 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.
  • If Lyft can take another 6% or more of market share from Uber, Uber will have lost its hallowed status and as a result I would expect its financial performance to deteriorate materially.
  • All of this plays in Lyft’s favour as Uber’s reputation is now in such a bad state that it has to tread very delicately wherever it goes.
  • This means that the aggressive expansionism that gave Uber its dominant share is no longer possible handing all the initiative to Lyft.
  • I have been very negative on Lyft to date as its position looked hopeless but with Uber constantly shooting itself in the foot has given it a fighting chance.
  • There is no way I can justify a $70bn for Uber given this outlook, and if Softbank is offering this to shareholders to build its stake, I think this represents a great opportunity to exit.

Alibaba – Offline grab.

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Alibaba is very different to Amazon.

  • I think Alibaba’s investment in Sun Art has nothing to do with Amazon’s strategy with Whole Foods, and everything to do with the woeful state of the offline transaction experience in China.
  • Alibaba intends to invest $2.9bn in Sun Art, a hypermarket operator which has 446 stores in 224 cities across China and turnover of around $16bn.
  • Alibaba will acquire a 36.2% stake in the company which to date has operated as a j.v. between French retailer Auchan and Taiwanese conglomerate Ruentex Group.
  • Offline retail in China is still massive at $4.5tn despite the rapid expansion of e-commerce and is a great example of why online and mobile have been so successful in the Chinese market.
  • Chinese offline retail is a fragmented and frustrating experience where decent service and information with regards to inventory, product lines and so on is routinely not available.
  • Consequently, when an online offering appears where this information is clear and one is able to easily purchase goods and know when they will be delivered, shoppers quickly adapt.
  • It is the terrible offline experience with regards to almost everything that has allowed so many other goods, services and activities in China to rapidly migrate from offline to mobile.
  • I think that Alibaba’s strategy with Sun Art is all about turning it into a high quality and efficient retailer using the technologies and logistics expertise that it has gained with the development of its e-commerce business.
  • This is very different to Amazon and Whole Foods as Whole Foods already provides a pretty good and reliable retail experience with good logistics.
  • I think that Amazon’s interest in Whole Foods is about ensuring that there will be enough volume in perishable items to give it the scale to push more and more groceries through its site.
  • In effect, Amazon has acquired a huge customer for that business to give it critical mass so it can economically expand groceries to its online customer base.
  • In contrast, I think Alibaba is doing something very different in making a play to take a big piece of the Chinese offline market.
  • If Alibaba can make Sun Art and its other partners like In Time and Lianhua Supermarket superior to then these stores should begin to gain market share over their rivals.
  • Given that Chinese retail is such a vast market, steady market share gains here has the scope to keep growth going at Alibaba (albeit at lower margins) once e-commerce begins to slow down.
  • It also offers Alibaba the opportunity to move other sectors of retail online once it has licked them into shape.
  • Hence, I think this move makes complete sense for Alibaba as there is a very clear opportunity for it in China which is completely different to that being followed by Amazon.
  • I am warming up to Alibaba as it is beginning to understand the importance and opportunity presented by the data its digitall assets generate.
  • While it is behind Tencent in Digital Life coverage, I am increasingly of the opinion that it is moving more quickly to understand the opportunity offered by the digital ecosystem.
  • Hence, when Tencent runs out of steam, I will be considering this one very carefully as a possible switch.

Google vs. Facebook – AI dividend.

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Google’s AI already paying dividends

  • Both Google and Facebook have a fake news problem but Google’s leadership in AI means that it is likely to have a better solution and will not have to materially impact the financial performance of the company to fix it.
  • Over the last 2 years, Google, Facebook, Twitter and so on have become far more important when it comes to delivering current events to users.
  • This is particularly relevant when certain events occur that result in regular citizens present at these events uploading videos and commentary long before the more established media outlets can arrive on the scene.
  • As a result, important information often appears on Google, Facebook and Twitter first, meaning that the accuracy and veracity of this information is of paramount importance.
  • Unfortunately, during these sorts of events, there is often a scarcity of information available making it the easiest time to successfully propagate fake news.
  • This is the problem with which both Facebook and Google are wrestling, but from looking at how both are dealing with it I think there is a huge gap between these two players.
    • Facebook: To combat this problem, Facebook has announced that the total number of employees working on safety and security will be doubled from 10,000 to 20,000.
    • Given that the total number of employees at the end of June 2017 was 20,658, this implies that 50% – 60% of all Facebook employees will be working in non-revenue producing positions.
    • This will mean that costs will meaningfully outstrip revenues leading to a “significant” decline in profitability.
    • These humans are being shipped in to deal with the problem because Facebook’s AI is not even close to being good enough to deal with it
    • Furthermore, I think that this is a problem that humans cannot really solve given the velocity that is required.
    • Google: to be fair to Facebook, Google’s data tends to be somewhat more structured than Facebook’s making it easier to analyse but this does not come close to explaining the difference in AI ability.
    • Although Google remains reluctant to discuss the methods it is using to combat this problem, this is something that it has been dealing with for many years and there has been no sudden increase in current for forecasted headcount.
    • There has also been no sudden decline in gross margins (current or forecasted) which would indicate that Google had taken on contractors to help fix the problem.
    • While Google does use fact checking services to ascertain the veracity of some of the content that appears in its searches, I think that almost all of its efforts are going into closing the loopholes in its algorithms that allow fake news to surface.
    • This is why there is no financial impact on Google from this problem compared to Facebook.
  • Furthermore, I think that using humans to combat fake news will end in failure.
  • This is because it takes the human system around 2-3 days to reliably label an article or item as fake by which time is has trended and already been seen by millions of users.
  • Consequently, I do not think that having tens of thousands of humans scouring Facebook for fake news will actually solve the problem.
  • Hence, I think that this will result in $1bn+ of shareholders money being wasted in every year that humans are being used.
  • This highlights the gravity of the AI problem that Facebook is trying to deal with and think it is one that Google is much closer to solving.
  • Hence, I see Google being able to far more effectively manage this problem and at a fraction of the cost.
  • From a shareholder value perspective, perhaps it is time to consider switching from Facebook to Google.

Tencent Q3 17 – Time purchase

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Mighty core business buys time.

  • Tencent reported strong results driven mostly by its content offerings which gives the company time to work out how to fully monetise the vast the community it has created.
  • Q3 17 revenues / net income RMB65.2bn ($9.8bn) / RMB18.0bn ($2.7bn) nicely ahead of estimates of RMB61.0bn / RMB15.8bn.
  • Tencent called out smartphone games (especially Honour of Kings) and its online video platform (which it now believes has overtaken Alibaba and Baidu to become China’s No. 1 place for video streaming) as top performers during the quarter.
  • Most revenue streams grew between 45% and 50% YoY but it was the contribution from other businesses such as first-time monetisation of WeChat Pay and cloud services that really drove the numbers above expectations.
  • Overall, these revenues grew by 143% to RMB12.0bn which pushed the corporate average revenue growth rate to a 7 year high of 61% YoY.
  • While the core businesses continue to defy the slowdown I have been expecting, the laggard in the company remains the monetisation of the ecosystem that it has created.
  • This is what Baidu and Google are really good at and what Alibaba has been showing increasing signs of getting to grips with.
  • The vast majority of Tencent’s revenues come from selling content like games, in app purchases or streaming subscriptions making it more like Netflix and Amazon rather than Google or Facebook.
  • Tencent has created a community of 980m users at least half of whom regularly interact with Tencent in multiple Digital Life segments.
  • This creates a substantial revenue opportunity for Tencent but one I think that it has struggled to really get to grips with.
  • Online advertising is still just 18% of revenues which I calculate is between one third to one half of what it should be for an ecosystem with 980m active users.
  • It is here that I still see the real upside for Tencent as it has done little in the last 15 months to address this opportunity.
  • To be fair to the company, management time has been very successfully invested in growing the existing businesses but the time will come when it will need to monetise this opportunity to keep growth going.
  • Here, I think that Tencent has a lot of work to do as its score on RFM’s 8 Laws of Robotics is pretty low, particularly against Laws 5 and 6 which focus on the integration of services and user data.
  • To monetise the ecosystem effectively, I think a good score against these measures is required and Tencent has so far shown little sign of grasping the importance of integration.
  • However, while the core business continues to defy expectations, this is not a problem from a share price perspective and buys management time to get to grips with integrating its assets into a single place where users can live their Digital Lives.
  • This is how I can continue to like Tencent as an investment despite its apparent slowness to move onto the next stage of its development.
  • While the core business continues to deliver, the valuation remains underpinned with the potential further upside coming from monetisation of the ecosystem.
  • This is why Tencent remains my preferred pick globally.