Thursday, June 27, 2013

Windows Store recommendations could one day reflect your usage patterns

Windows Store recommendations could one day reflect your usage patterns

Yesterday was the day Microsoft made Windows 8.1 available as a public download; today's the day we ask what's next. Here at the company's annual Build developer conference, we sat down with Ted Dworkin, the man who oversees the Windows Store, to do a deeper dive on the store's latest redesign. In particular, we were curious about that new Bing-powered recommendaton engine, and how it might become smarter over time. What ensued was a Pandora's box of a brainstorming session. Naturally, Dworkin wouldn't make any promises about what we'll see in future updates, but he did offer some compelling ideas about how Microsoft could take people's usage patterns into account when recommending apps. For instance, while Windows already knows which applications you've downloaded, a future version of the store might also be aware of which apps you use most frequently, which ones you've uninstalled, which ones you've shared, which ones you've pinned, which ones you've unpinned, et cetera. On a privacy note, the recommendation engine is already optional, so there's no reason why you couldn't disable this kind of data collection too.

For starters, this an interesting idea for the developers attending Build this week -- there are definitely people out there who download apps because they're testing them (or reviewing them) and not because they plan on using them every day. Even more broadly, though, who among us hasn't gone on a downloading spree, just to see what they liked? With usage patterns taken into account, you might get more useful picks, ones that ignore that random Twitter client or Angry Birds game you installed. Again, Dworkin wouldn't say for sure if Microsoft plans on implementing any of this, but our vote would be "yes" if it leads to more recommendations we'd actually use.

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Source: http://www.engadget.com/2013/06/27/microsoft-could-improve-windows-store-recommendations-usage-patterns/?utm_medium=feed&utm_source=Feed_Classic&utm_campaign=Engadget

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