In my last post, I wrote about a patent application describing how Yahoo might come out with a widget that could be used with blogs, to recommend old posts on those blogs based upon your lifestreaming activities.
It appears that Yahoo may have even grander and more financially motivated intentions behind collecting information about how you blog, tweet, tag images, and leave other footprints on the Web about your life and interests.
Imagine Yahoo crawling the Web and grabbing information from APIs and feeds published by other sites that provide information about the movies you rent, the reviews that you publish, the pictures that you tag, and the sites that you bookmark. Along with your tweets, your status updates, and your other activities on the Web, this information could be used to build a profile of your actions online.
That profile might then be used to determine which banner ads, job postings, and other advertisements that you may be shown.
It could also possibly be used by some sites to personalize the content that you may see.
That’s the topic of the following Yahoo patent application, which could take lifestreaming data to personalize how you see the Web:
Personalized Advertising Using Lifestreaming Data
Invented by Saurabh Sahni and Pankaj Kothari
US Patent Application 20100023399
Published January 28, 2010
Filed: July 22, 2008
This patent discloses a method to increase the relevance of advertisements displayed on the Internet. An ad server may receive a request for an advertisement from a web server. The ad server may compare metadata to online advertisements within an ad database. The metadata may include data about the user obtained from at least two websites through a lifestreaming process.
The comparison may seek out a best match between the advertisements and the metadata and serve the resulting advertisement to the web server.
The patent application provides details of how this system might work as well as some examples that put it into perspective.
Here’s the first of them:
An online DVD rental service shows that Bob likes to rent movies on weekends from an online DVD rental service. Consider a scenario where system has retrieved application programming interfaces (APIs) from a popular online Digital Video Disc (DVD) rental service and those APIs demonstrate that user Bob has tendency to rent movies on weekends.
In addition, system previously retrieved a message posted by Bob on a free social networking and micro-blogging service, where the message as “Watching movie in Mxim Theater, 5800 Zoo Drive, Kansas City, Mo.” In more recent retrievals, system has obtained metadata that indicates Bob has been listening to songs from the movie Screech on a United Kingdom-based Internet radio and music community website. Bob also had identified a trailer of the movie Screech on a video sharing website as being a favorite trailer.
Today, Friday and the first day of the weekend, Bob has requested a webpage (FIG. 1) that details new movie releases and includes a position for an advertisement. With all above personal data about Bob’s activity maintained as metadata, system may use metadata to retrieve an advertisement from ad database that may be closest to “Buy tickets for movie Screech in Mxim Theater.” The ad then may be served into webpage.
The advertising system might draw all of Bob’s activities that it sees together to decide upon the best advertisement to show him from their database of available ads, upon the premise that he would be more likely to click upon that ad.
Another example describes how the actions of “friends” on social networking sites might also play a role in the advertisements that we might see.
The patent filing primarily focuses upon describing how advertisements might be custom delivered to viewers based upon this activity data. There’s only one brief sentence that tells us that other non-advertisement based content could also use this kind of information, and it doesn’t layout much in the way of details:
The lifestreaming metadata also may enable websites to personalize content according to the user activities.
There have been a number of patent filings and whitepapers from the major search engines that describe how search history and browsing history might be used to personalize advertisements. This patent filing from Yahoo describes a way of actively crawling the Web and gathering data from other sources to collect information about individuals and determine what ads to show them.
In What Personalization Means to Search, I wrote about how Search Engines might turn to “analyzing footprints people leave on the Web” to provide personalization to searchers. I also asked what that might imply in terms of privacy.
I’ve been tweeting about shoveling snow this morning. Will I start seeing ads for snow blowers?
What ads might you see?