Google Now, Maps and Apple Music

Google Now looks like Google's most magical, artificially intelligent product. And in some senses it is, but it is also in some senses Google's most manual product. Each category that Now knows about and makes magical suggestions around is the result of a human making an editorial choice to create that category. Google Now gained cricket scores not because it 'learned' that there was cricket but because someone at Google wrote a recipe for cricket. 

Obviously, you can't do this for everything - Google Now cannot scale to the whole internet. It can do a lot, and certainly enough to be a great product, but it can't do everything, not until we have 'true' HAL 9000-style AI, which is a long way off. The underlying domain is not actually infinite, but like Borges's library it might as well be for any manually-edited project - Yahoo's manually-edited directory peaked at 3.2m sites but had become absurd long before that. So there are gaps - you're making something that looks like AI but isn't. Google Now covers the gaps by keeping quiet, where Siri covers the same kinds of gaps by making jokes (that was probably a better product management decision - if you baffle Siri you get a blank stare or a laugh but if you baffle Now you never know about it). 

 Contrast this with Google Maps, which is also partly a manual product. Hundreds or thousands of people drive Streetview cars down roads and hundreds or thousands of people check the images and edit the maps. There's lots of machine vision too, as well (and crowd-sourcing), but the back-stop is lots of paid employees. The algorithms alone aren't good enough yet. Editing the internet by hand was just too big, but editing maps isn't - it's just very expensive. Google is willing to spend that (and Apple is going to try too). 

So, mapping the internet by hand is impossible - you need algorithms. But mapping the world with algorithms alone is also impossible, for now - you need people to look at the data too.

I see Apple Music as sitting somewhere in this second category - manual curation at scale. Here the problem to be solved is that the commodity streaming service's 'search box plus 30m tracks' offers no way to discover anything you might like but haven't already heard of. You need personalised suggestions, from somewhere. But how do you suggest things from 30m tracks? It is in principle pretty easy to get some data about what people like, especially once they start listening (and so stop lying). But how do you know what aligns to that preference data?

Pandora applies an algorithm. Apple Music is trying the Google Maps approach: "doing this at least partly by hand is not an impossibly large problem, just a very big one". Just as Google manually adds metadata to the raw maps (street names, one-way streets, business names etc) Apple manually places tracks into playlists with its own metadata. Then it takes the interest data it has about a user and suggest 10 or 20 or 30 playlists, and, hopefully, there's a good chance that enough of them will be right. (It covers the gap that Siri covers with jokes and Now covers by keeping quiet by overshooting - it's probably OK if 15 are not quite right if 10 are on target.)

How many playlists you need? 5,000? 10,000? With a few hundred editors that's not actually an impossible challenge, just a big one. And a cynic might suggest that really, you only need a few hundred for the vast majority of music listeners, if you do them right. 

What are you afraid of?

As a company moves from insurgent to incumbent, and gets big and complex and involved in lots of different things, it tends to end up with lots of different objectives, tactics and strategies. At that point, trying to understand it from outside, it can be useful to think not about what it's trying to do but what it's afraid of. This company want to do lots of things, but what's the existential threat? What does it want not to happen? What scares it, late at night?

For Google, the fear is around reach. Google is a data company, and a machine learning company, and everything it does is about reach - reach to get data in so that it can understand everything better, and then reach so that it can serve that understanding out to the users. And so Android exists partly to enable the expansion of the mobile internet, but also, and more fundamentally, to ensure that no-one (meaning first Microsoft and later Apple) would be able to block Google from reaching those users, both to give them each results and to see what they are doing. Google is afraid of going blind. 

For Apple, I'd suggest the fear is that the developers leave. This is what happened in the 90s and it was a key part of the company's near-death experience (and arguably Apple only survived because the web made the lack of Mac apps matter less as a reason to buy a computer). Once developers start leaving you're in a vicious circle that's very hard to reverse (this is where Windows Phone is now). Today the iOS ecosystem is smaller than Android in absolute users and downloads, but has 7-800m live device, which is three times the size of the PC install base in 1995, and twice as much app store revenue per user as Google Play. More importantly, perhaps, the users are highly concentrated in key locations - Chase isn't going to abandon its iPhone app because there are 500m Android users in China.  So right now the ecosystem looks sustainable, but that could change. Developers can leave. That's Apple's existential fear.  

This is a useful lens to apply to the announcements at WWDC and IO. Google, this year in particular, always seems happier and more comfortable talking about the great stuff it can do with its own unmatched cloud intelligence - Now on Tap, for example. Losing that intelligence is what Google's afraid of. Apple is happiest talking about the new platforms and technologies that it wants developers to use - Apple Pay, iBeacons, Extensions or App Search. And losing that developer adoption is what Apple's afraid of. 

The (lack of) app store metrics

Apple and Google both give headline statistics of how well their respective app stores are doing, generally at their summer developer conferences. These are rounded numbers at scheduled events and they're not always comparable, but they do give us a sense of what's going on.  

Last summer, at their developer events, both Apple and Google gave numbers for the money they had paid to developers in their respective app stores: $5bn in the previous 12 months for Google Play and $10bn for the iOS App Store. Given Android has double the user base of iOS, this meant that the average iOS user was worth around 4x the average Android user in app store revenue. 

This year Apple gave the same number - $10bn (more precisely, it gave a cumulative figure of $30bn this WWDC versus $20bn last WWDC). The lack of growth may be partly due to rounding but still implies that people are spending less on average, since the user base is still growing.  Google gave no number at Google IO but it gave one earlier in the year of $7bn. It looks as through Play is growing faster than iOS and might overtake it this year (unless Apple is rounding down very aggressively - certainly the uneven shape of the graph in 2013 is due to rounding).  

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Since Google Android has close to double the number of users, this implies that the average user is spending perhaps half as much as the average iOS user - a change from 1/4 a year ago but still a big gap. 

Meanwhile, this was the first year since 2013 that we could compare downloads.

Google Play had 50bn app downloads in the last 12 months and iOS had 25bn, with Play appearing to be growing faster. Since, again, Play has more users, this implies roughly the same downloads per user on Android and iOS. 

Incidentally, these numbers show annualized consumer spending on apps of around $25bn, and 75bn apps downloaded in the last 12 months. 

What does Google need on mobile?

I generally look at Google as a vast machine learning engine that’s been stuffed with data for a decade and a half. Everything that Google does is about reach for that underlying engine - reach to get data in and reach to surface it out. The legacy web search is just one expression of that, and so is the search advertising, and so are Gmail and Maps -  they’re all built onto that underlying asset. 

Hence, most of the experiments that Google has launched over the years are best seen as tests to see if they fit this model. Can you apply a vast expertise in understanding data, large numbers of computer scientists and data scientists, lots of infrastructure and a model of total automation and get something interesting and useful - can you get massive amounts of new data in, can you do something unique with it, and can you surface it back out? And, for all of these, are you solving hard, important problems with global scale? 

That is, Google tests new opportunities to see if they fit in the same way that a shark bites a surfer to see if they’re a seal. If not, you don’t change Google to fit the opportunity - you spit out the surfer (or what’s left of him). 

Naturally, sometimes it turns out that you need other capabilities - e.g. radio advertising. Sometimes it ought to be a good opportunity but the friction in actually unlocking the data is too great - e.g. Google Health, where there were too many different and reluctant parties involved. Sometimes Google's skills are just a condition of entry and other skills are more important (Google Plus in social), and sometimes the opportunity is just too small - e.g. Google Reader. But equally, there are projects for which Google's core skills and needs have fit very well. Maps had little obvious to do with web search and nothing to do with PageRank, but was a big problem that Google’s assets could be applied to (and of course, a decade later, Maps turned out to have huge strategic leverage in mobile). The same may be true of self-driving cars - this is not a search question, but it is a data and machine intelligence problem where Google is uniquely placed to do things (or at any rate, that’s what Google believes). 

Android embodies all of this. Originally, it was about reach, in the sense of people being able to use Google. It existed to head off domination of mobile by any third party that might shut Google out (first Microsoft, then Apple) and to enable the expansion of the internet from 1.5bn PCs owned by relatively rich people to, in the next few years from now, 4-5bn mobile phones owned by almost every adult on earth. In both of those aims it’s been an enormous success, much more than any other Google side-project. Apple will have a lot of the top 15-20% of the market, but Android will have almost all of the rest and serves to keep Apple honest even on iOS. 

Over time Android has also evolved to provide reach in collecting data as well - you’re always logged in to Google on your Android phone, and it knows where you are when you do that search or open that app, and where everyone else who ever did that search was, and what they did next (this is one reason why retaining control of the Android UI, and heading off forks, matters to Google). There’s an old computer science saying that a computer should never ask a question that it should be able to work out the answer to - the sensors and other capabilities in smartphones in general and Android in particular massively expand the range of things that Google can work out. So, Android transforms Google’s reach both in collecting and surfacing data. 

The interesting part, though, is that there are now lots of different kinds of reach. 

First, as everyone has talked about for years, the way that mobile moves us away from the plain old web as the dominant interaction model of the internet challenges Google’s central ability to understand the structure of online information and to link to it (and sell links to it). Apps cut off Google’s reach, both to get data into its systems, since apps are opaque, and to surface data out to internet users, since any search in Yelp’s specialist app is a search that wasn’t on Google, and such apps are stronger on mobile than on the desktop. Apps reduce Google’s reach in both senses. This of course is why (like Facebook) it has been pursuing deep links, and is probably also one reason why it is keeping Chrome OS warm as a standby mobile platform. But it also means that Google has conflicting incentives - as a provider of services, should it try always to make things as part of the web, or embrace the new experiences that apps and everything else happening on smartphones can provide? What would the web search team say if Hangouts became a development platform, for example? 

Furthermore, ownership of an actual mobile platform creates more basic conflicts - should Google make a new app for iOS first, given that’s where many of the most engaged users are? Should it provide it for ‘forked' devices such as the Kindle Fire, if they have enough users, though that erodes a point of leverage for control of Android? For these kinds of questions it’s easy to see how individual product managers might have incompatible objectives - the Maps PM probably wants Maps to be great on iOS and might well like it on Kindle, but people thinking about maintaining Google’s control over Android clearly would not. 

That is, how much does Google need to pull things to the web, or, alternatively, to Android, and how much should it let the logic of individual product teams prevail - and where there's conflict between product teams, who wins?

These are really classic ‘strategy tax’ questions. A product feature conflicts with the company’s overall strategy, so do you leave out the feature (and so pay the strategy tax) or compromise the strategy? To give examples from other ages of the tech industry, Microsoft's Office for Mac and Apple's iTunes for Windows both in theory undermined those companies' core products, but both were the right thing to do for the broader strategy. The question for Google is to work out which part is the tactic and which is the strategy. What kind of reach do you want, and which sacrifices to you want to make?

This problem reminds me of a book published a few years ago by Pierre Bayard, a French academic, called ‘How to talk about books you haven’t read’ (review). His observation is that the question ‘have you read this book?’ is actually much less binary than it appears: if you compare a book you read as a teenager 20 years ago and half-understood with a book that’s just come out and that you’ve read 3 reviews of, but haven’t actually read, you might know rather more about the latter than the former. There are books you read and understood, books you’ve read and half-remember, books you can’t remember that you’ve read at all, and books that you’ve read half of, or know the key ideas of, or have heard about, or that you know are exactly the same as three others by the same author that you really have read. Reading and knowing about a book are not binary. 

In the same sense, Google needs reach, but mobile means that there are lots of different kinds of reach. Consider someone who has an ‘official’ Android phone, perhaps even a Nexus, and is completely logged in - so Google has ‘perfect’ reach to them as an end-point. But, as I wrote here, suppose they live in a quiet suburb and drive only to work and to a few shops, never use Calendar, open Maps once a month and get a few personal emails in Gmail each week. Now contrast that with a 20-something in a big city who loves their iPhone and is not logged into any Google service - but is on this phone for hours every day, uses Google Maps (or maybe just apps that embed it) and is doing web search all the time. What kind of reach does Google have for these two? 

Then, consider a farmer in rural Myanmar who’s just got their first phone: a $30 Android, with enough spending power to get perhaps 50 megs of cellular data a month, if that. What is that reach worth - what do they search for, what can the information they provide to Google be used for and, to raise the boring, pedantic question, how much are they worth to the advertising industry? Are they a higher priority than extending Google Now to the Apple Watch? 

The key change in all of this, I think, is that Google has gone from a world of almost perfect clarity - a text search box, a web-link index, a middle-class family’s home - to one of perfect complexity - every possible kind of user, device, access and data type. It’s gone from a firehose to a rain storm. But on the other hand, no-one knows water like Google. No-one else has the same lead in building understanding of how to deal with this. Hence, I think, one should think of every app, service, drive and platform from Google not so much as channels that might conflict but as varying end-points to a unified underlying strategy, which one might characterize as ‘know a lot about how to know a lot’. 

Another way to think about this, perhaps, is the comparison with Internet Explorer. Microsoft was entirely successful in ensuring that its own web browser dominated the internet for a decade or so. But really, whatever browser people ran, they were going to run it on a Windows PC anyway, because what other mass-market global platform was there? So too for Google: what matters is to win at 'search', whatever that means and wherever and however far from PageRank that leads you. Nail that and reach will come to you - get it wrong, or find yourself irrelevant in whatever the new new is (as happened eventually to Microsoft), and nothing else will matter. 

New questions in mobile

The mobile platforms wars are over, for now - Apple and Google both won. But nothing is settled. The nature and scope of Android is unstable, interaction models themselves are in a flux between apps,web, messaging and notifications, wearables are emerging and Facebook and Amazon haven't given up on controlling the interface. Time for new questions. 

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Phases in mobile

This was the launch ad for Orange, in 1994. Orange was one of the very first mobile operators to think that mobile could be a consumer product rather than a piece of technology sold to niches, and one of the first to think in terms of brand and brand values, and the products that might flow out of them. The founding CEO, Hans Snook, was crazy enough to suggest that pretty much everyone would have a mobile phone. 

It's probably one of the best ads ever made. 

Also, note the freephone number and the lack of any suggestion of data services. All about voice. 

This video was made by Orange in 2000, 6 years later, the year of Europe's €110bn 3G spectrum auctions. At this point there were no phones with colour screens on sale outside Japan, but they did a pretty good job of predicting the future - it's fun to try to spot how many of those services have now been launched. None by telecoms companies, of course. 

This, of course, is the first of the original launch ads for the iPhone, in 2007, 7 years later. The fascinating thing about this video, today, is how much that we now take for granted was then entirely new. And, of course, this changed the world again. 

Finally, another 7 years later, Apple's note to the developers for a platform that didn't exist before. By the end of this year around 2bn people will have a smartphone, spending around $20bn a year on apps. 

This, of course, begs the question of what extraordinary leap we'll have made in another 7 years.