A prediction engine API is useless without a reason for existing. The most basic reason for utilizing a prediction engine is to entice users with more that you offer. Many people think that prediction engines are good for only one thing: selling items online. Yet this is short-sighted, and that mindset must change. A prediction engine can have MANY uses for anything a consumer might want — sometimes even more information.

One area I see the prediction engine being the most powerful in is visitor retention, and not just for consumer items such as buying DVDs or toys. Imagine a blog that covers a niche topic such as programming techniques or guides. A blog like this would have a variety of tags and categories, allowing users to traverse the site based on finding articles of common topic. Yet that is a very uninteractive experience — users don’t really have much input into what they like and dislike about articles. Even the sites that ask for user input do almost nothing for the user while they’re on the site. Asking for a rating is helpful for long term changes, but it is completely a waste for the user RIGHT NOW. Why should a user bother rating a site or a page if they don’t get anything out of it (I call this an information profit). How about tossing that user’s ratings into the prediction database, and allowing that engine to generate a list of articles the user would like? By giving real-time feedback based on a user’s preference, the engine gives the user instant reason for taking 5 seconds to judge an article’s value to them. The value by itself is useless for the short term, but the aggregate of the user’s opinion combined with all the users on a site offers huge value for the user now and the site operator in the future.

The power for an individual blogger or web operator is big, but it is also big for blog networks or any network of information provided. By integrating the decision making process across a network, even a loosely-organized network that is not really integrated under one topic or idea, can reap huge dividends for the site operator in reader retention, while also providing the user with an interesting path of topics to read. The user’s investment is almost nothing — 5 seconds to click a rating. With a Web 2.0 or AJAX interface, the user won’t even be taken off the page they’re on, but they could receive an instant update to interesting articles. The user’s profit is just that — more information for the information-hungry visitor. The web operator’s investment is taking the little bit of time to learn the prediction engine API, and possibly a small financial investment to provide for the server-time needed to process the information. Yet with a system such as CRITEO, the web operator’s costs are scaled — few users, little cost. Many users, higher cost. More users = more advertising dollars. More users sticking around = much more advertising dollars. And the best part: once the web operator takes the time to connect to the predictive engine, the rest is simple. There is almost no upkeep, maintenance or modification needed for the web operator to keep using the product, but the product will continually adapt to both the web operator’s and the visitor’s needs.

The user can also instantly let the web operator know that an article is useless or useful, and the web operator can run reports to diagnose what they SHOULD write about next. This is incredible power for almost no real price time-wise or money-wise.

This entry was posted on Tuesday, December 5th, 2006 at 7:30 am and is filed under Possible Markets. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.