Amazon Silk Browser Sets Tech's Teeth on Edge
When you're a major tech company and you roll out a product that deigns to track information about users - personal or behavioral - it tends to have quite the blowback.
Such is the position Amazon (NASDAQ:AMZN) found itself in Sept. 28 after the e-commerce giant introduced its Kindle Fire tablet, a 7-inch, custom Android media-chomping slate that will cost only $199 when it arrives Nov. 15.
The tablet itself delighted users, but it's the machine's window to the Web that has some people nervous. That would be Silk, a special mobile browser Amazon built to churn Web pages at a heady clip on the Kindle Fire. Silk leverages Amazon's Elastic Computer Cloud (EC2) Web services platform for speedy information retrieval.
Even more exciting, Silk "learns" about traffic patterns on individual sites over time, allowing it to begin fetching the next page that users may wish to visit. This, in addition to the processors, storage and fat data pipes of EC2, helps speed up Web browsing.
Amazon explained: "As you begin to use the browser, this view will become customized to display your most frequently visited sites, allowing for fast navigation to the sites you visit most often."
Of course, the speedy Web page pre-fetching opens users up to something they may not like. To harness its cloud for Web browsing, pages Kindle Fire users visit through Silk may be "cached to improve performance and certain Web address information will be collected to help troubleshoot and diagnose Amazon Silk technical issues."
However, Amazon said this data is collected anonymously and stored in aggregate, and no personal identifiable information is stored.
Amazon also claimed it generally will not keep this information for longer than 30 days. Moreover, Kindle Fire users may opt to switch to off-cloud mode, so that searches they do on the Fire don't traverse Amazon's pipes and into its cloud.
Yet just the fact that Amazon may collect some Web address info is enough to put privacy advocates and techies who are familiar with what that means, on the defensive. Chris Espinosa, a development engineering manager on Apple's Xcode team, was wowed by the possibility of this data collection potential for Amazon. In a blog post, he noted:
"Amazon will capture and control every Web transaction performed by Fire users. Every page they see, every link they follow, every click they make, every ad they see is going to be intermediated by one of the largest server farms on the planet. People who cringe at the data-mining implications of the Facebook Timeline ought to be just floored by the magnitude of Amazon's opportunity here. Amazon now has what every storefront lusts for: the knowledge of what other stores your customers are shopping in and what prices they're being offered there."
Not so fast. GigaOm's Om Malik asked Amazon: "Is Amazon able to peer into its customer usage behavior and use that to offer services based on that data? For instance, if you see thousands of your customers going to buy SeeVees shoes from say a store like James Perse at a certain price, can you guys use that data to specifically tailor the Amazon store and offer up deals on those very same pair of shoes?"
Amazon replied that Silk will not do this, as such data is only used for troubleshooting and technical resolution.
The idea is interesting, though. By dint of its size and troves of customer data, Amazon has the potential through the Kindle Fire and Silk to build not only a massive recommendation engine, but a huge price comparison engine that no one could match.
Moreover, it would disintermediate Google from its precious mobile search user base. Imagine 20 million or more Kindle Fire users by this time next year, using Silk instead of a Google Android browser to search for data. Amazon gets to keep the consumer fully locked into its consumer shopping experience.
Fortunately for Google, its search is the default on the Kindle Fire, but Silk has the potential to be a powerful mechanism to wall the Fire off from some users who find Silk to smooth to avoid.