IS AI THE ANSWER TO ONLINE CONVERSION WOES?

"Artificial intelligence (A.I.) alone will not make your Web site smarter or more customer-centric, but it will be a key tool as the new economy shifts from the Information to the Decision Age." That's how Clay Stobaugh, CEO, TripleHop Technologies, begins his explanation of the latest technological breakthroughs affecting online businesses.

With the release of Steven Spielberg's movie, Artificial Intelligence (A.I.), due out this summer, the true value of A.I is a hot topic for those seeking new ways to provide personalized customer experiences, and increase browser-to-buyer rates on their Web sites.

TripleHop Technologies, www.triplehop.com, a provider of decision support tools for the networked economy, took advantage of A.I. technology by developing a patent-pending system that combines artificial intelligence with several additional layers of filtering. The company realized early on that combining multiple filters with A.I. results in a system that's greater than the sum of its parts.

By combining what TripleHop calls the three "Cs" -- contextual filtering, collaborative filtering (TripleHop has developed it own, patent-pending algorithm, which it calls "attribute-based collaborative filtering"), and click-stream analysis -- users are provided real time recommendations and advice on given topics at a level of depth not possible with each separate filtering method alone, thereby increasing the likelihood of a purchase.

"The most common consumer use of A.I. technology is through standard collaborative filtering, which was an effective recommendation technology in the early days of the Internet. However, there are well-known challenges with this system. Collaborative filtering bases all its consumer profiles on one criterion, whether it's purchasing history or ratings assigned to movies or books. It assumes that all user history has equal weight when making comparisons with other users. It also can't predict if you are referring to an ongoing interest, like gardening or classical music, or whether you are currently making an unrelated purchase, say a gift for a friend," says Stobaugh. "By using collaborative-filtering at a substantially more granular level than other available systems, and combining it with other levels of filtering, our technology solves those issues."

One of TripleHop Technologies' early applications has been to bring a more sophisticated recommendation engine to travel Web sites by creating the in-store, e-travel agent experience, online. This is a time-honored practice that begins when a potential customer walks into an agency and is greeted by a knowledgeable travel agent.

In that scenario, the travel agent politely gathers information about the visitor and matches it with the information contained in the available trips. The agent also considers what other similar customers purchased in previous interactions. The end result is that the customer is presented with highly tailored suggestions to pique his or her interest and thereby increase the individual's likelihood to purchase.

"Our system provides travel Web sites with the ability to personalize in a way that "fits" the customer. Not only are the recommendations in line with what the customer is seeking, but it explains why a particular recommendation is suitable by providing a ranking -- a five-star ranking versus a two-star ranking for example," says Stobaugh. "So far, we've had tremendous success in travel and other online industries."

TripleHop Technologies travel clients include Orbitz, Eurovacations, Ski-Europe, Preferred Traveller, Lastminutetravel.com, and Travelot. One client, Ski-Europe, revealed that the portion on the Web site powered by TripleHop's travel recommendation recorded a 70% increase in the lead conversion rates.

About TripleHop Technologies

TripleHop Technologies provides decision support tools to consumers and enterprises. The decision support tools include recommendation engines, knowledge management, CRM, information retrieval and personalization applications. The primary set of applications is a series of turnkey, industry-specific recommendation engines, including TripMatcher, ShopMatcher, GiftMatcher, JobMatcher and a soon-to-be-released FundMatcher.

TripleHop Technologies has developed a patent-pending Matching Engine that uses artificial intelligence to predict customer preferences while simultaneously building a rich behavioral profile. This Matching Engine technology powers recommendation engines that enable clients' prospects to receive personalized recommendations that make it more likely to convert them from "browsers into buyers." The Company has secured funding from Spef and Deutsche Bank Capital, and is headquartered in New York, New York. Additional information about the company and a demonstration is available at www.triplehop.com.

Contact TripleHop Technologies, New York, Anna Janosi, 212-697-9191.