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.