Maps are only growing in importance as they become the primary portal on mobile phones for a growing list of information and services. As Apple showed us last year, it's critical to own maps - and to do maps well, particularly as a growing percentage of time is spent discovering, accessing, and engaging content within maps. With that said, it's not immediately clear to me what justifies a $1B+ (reported) price tag for Google’s acquisition of Waze, but I'll assume they did great due diligence or offered a high price to get a deal done.
For instance, many companies do acquisitions for audience, but Google's audience - even just on Android or Google Maps is substantial. Waze's website says 30M users; other sources say 50M. Apparently, engagement among users is high ... but is it well distributed? Are there enough active users in each market for the same excellent experience?
However, Waze does add new features that Google Maps doesn't already have e.g., the ability of users to report traffic issues, police cameras, broken down vehicles - you name it. Layering user-generated content into maps in real time in a way that makes sense and is useful to everyone at that place at that moment is not typical. Mobile needs to be highly contextual in ways people are beginning to understand, but are really struggling to implement well. It also increases speed to market if Google/Android team were otherwise developing this on their own.
With maps integrated into every retail, travel, banking, insurance, (ok go down the list) app on your phone, I don’t think any company can have too much map technology, or too many engineers/developers for maps and navigation technology.
Google sets amazing new standards when it comes to web, mobile, and cloud technologies. That's why we are here at Google I/O 2013 in San Fransciso to find out what new technologies and tools developers can expect on all technology fronts. See this special edition of Forrester TechnoPolitics to experience the energy of Google I/O.
At Google I/O, the company managed to impress on a lot of fronts, enough that its stock began to climb as investors realized that Google is keeping up with — and in some cases, staying in front of — its digital platform competitors Apple, Facebook, and Microsoft. The new developer tools and resources announced will certainly lead to better apps, be developed more quickly, and be capable of generating more revenue. And consumer experiences in mobile, Google Maps, and the browser are about to get significantly more useful and elegant.
But one announcement debuted at I/O that doesn’t move the needle for Google — at least not as much as it could have — is the Google Play Music All Access pass. Despite the convoluted moniker, the service is straightforward: Pay $9.99 a month (in the US for now, more countries to come), and you’ll have unlimited access to a cloud-based music library with intuitive features that allow elegant discovery, consumption, and sharing of music.
If it sounds familiar, it’s because it is. The service can’t differentiate on its music library because the best it can do is license the same library that Spotify and Rdio already offer. All Access also creates playlists for you based on your music tastes as expressed by you directly or learned from your listening patterns and friends. That should also sound familiar because the same value is contained to various degrees in Pandora, iTunes, and Amazon Cloud Player.
Bottom line: Despite working really hard, the best that Google can do in music is to catch up to everybody else in the field. And that’s precisely what the company has done.
Last month I published new research on the Database of Affinity — a catalogue of people’s tastes and preferences collected by observing their social behaviors on sites like Facebook and Twitter — and how that database will change marketing. And I'm pleased to say I've gotten a lot of great feedback on that research. So I'm excited to be presenting the idea on stage at our Marketing Leadership Forum in London later this month.
What is the database of affinity?
I hope you'll be able to join us in London on May 21 and 22.
Last week was full of news on wearable devices: First the report from The Wall Street Journal that Microsoft is fabricating a smart watch (whether it’s just a prototype or an actual product is not confirmed); then Google’s release of guidelines for developers building apps (known as “Glassware”) for Glass; followed by the news on Wednesday that Google will start shipping Glass units to participants in its Explorers program.
To put these stories in perspective, Glass is a much, much more important story than any smart watch story — whether that watch is made by Microsoft, Samsung, or even Apple. Smart watches could enable new “glanceable” experiences that we haven’t had on other devices, enhanced by body-generated data, like the Basis smartwatch does today. But they won’t fundamentally disrupt social norms in the way that Glass will. At best, they’ll reinforce existing ecosystems for smartphones — i.e., iPhone buyers might buy an iWatch; an iWatch might displace some phone usage, but wouldn’t replace a phone altogether.
Recently we described an idea called the database of affinity: A catalogue of people’s tastes and preferences collected by observing their social behaviors on sites like Facebook and Twitter. Why are we so excited about this idea? Because if Facebook or Twitter or some other company can effectively harness the data from all the likes and shares and votes and reviews they record, they could bring untold rigor, discipline, and success to brand advertising.
But exploiting the database of affinity won’t be easy. Any company hoping to turn affinity data into something marketers can use will need three things:
Lots of affinity data from lots of sources. The raw data required to build a functional database of affinity doesn’t live in just one place. Facebook controls the most "like" data, recording more than 80 billion per month at last check. But Twitter records more "talking" than anyone else (1.5 billion tweets per month); Amazon collects the most reviews (well over 6 million per month); and Google’s YouTube and Google Display Network have data on how a billion people prefer to spend their time.
The ability to bring meaning to that data. It’s easy to draw simple conclusions from affinity data: If you ‘like’ snowboarding you might like to see an ad for energy drinks. But the real value in affinity data won’t be unlocked until we can find hidden combinations of affinity that work for marketing. That’ll require technologies and teams that can do some serious data analysis — as well as a real-time feedback loop to determine whether people really are interested in the ads targeted to them based on such complex assumptions.
For our Forrsights Workforce survey, Forrester annually surveys information workers.* I’m leading final preparation of our Forrsights Workforce survey focused on end user hardware and aimed at five major markets – the US, Canada, the UK, France, and Germany. By end user hardware, we primarily mean PC/Macs, tablets, and smartphones, but we may also focus a bit on peripherals. And we hope to mirror some of the questions from the Forrsights IT Hardware survey, which we develop after this one, so that we can compare results from this information worker survey to what IT buyers report in their survey. Analyst Heidi Shey is working on the other half of the survey, which will focus on security issues.
Below are the hypotheses and topics we plan to explore in the survey. Please give them a quick read, then post or email feedback by Friday, April 12 (Tuesday, April 16 at the very latest). If you are a Forrester client and would like to see a survey draft, please email your account rep and me.
These are statements of ideas we are planning to test in the survey questions, which are designed to confirm or disprove the idea. But we probably can’t fit all of these, so please help us prioritize – especially if you are a Forrsights Workforce client!
Have multiple devices used for work, including many that are personally chosen and/or owned; they spend significant money on devices used regularly for work; and they expect to continue doing so.
Often blend work and personal tasks on the same device, despite employer policies to the contrary.
This week, Google announced that it will shut down Google Reader on July 1, 2013. In its announcement, Google states that it’s doing this because the usage of Google Reader has declined and it wants to concentrate on fewer products. There was a lot of buzz online about this decision, and some fanatical Google Reader fans put together a petition to keep the RSS reader alive. They garnered more than 50,000 signatures in just a few hours.
This whole debate sparked my interest, and I analyzed Forrester’s Technographics® data to get a better understanding of the usage of RSS feeds over time. I found that Google is right about the decline. Our data shows that it was always only a dedicated group who used RSS feeds at least weekly — about 7% of US online adults in 2008; this had declined to just over 4% last year, with about one in 10 US online adults using RSS feeds about monthly.
For years, brand marketers have guessed at people’s affinities from the barest of demographic, geographic, and contextual clues. We deduce that Midwestern men prefer pickup trucks and that people watching extreme sports like energy drinks, and then we spend billions advertising to these inferred affinities.
But today, we no longer have to guess. Every day huge numbers of people online tell us what they like. They do this by clicking a ‘like’ button, of course — but there are many other ways people express affinity: talking about things on Twitter and in blogs; reviewing things on Amazon and Yelp; spending time with content on YouTube (and telling us where they’re spending their offline time on Foursquare); and sharing things through both public and private social channels.
People’s rush to post their affinities online recalls another flood of data that began a decade ago: the explosion in online searches. John Battelle once described the data created by search as the “database of intentions,” which I’d define as “a catalogue of people’s needs and desires collected by observing their search behaviors.” In the same way, the result of all these online expressions of “liking” has created the “database of affinity,” which Forrester defines as:
A catalogue of people’s tastes and preferences collected by observing their social behaviors.