2006 Apr 02
Certona Corporation Resonance
by David M. Raab
DM News
April, here 2006

One of the endless debates within the software industry is whether companies should buy integrated suites or individual best-of-breed products. At the moment the pendulum has swung far in favor of suites. Years of belt-tightening have left corporate information technology departments without the staff to even evaluate the dozens of individual solutions available for different applications, let alone do the actual work of merging them into a corporate infrastructure. In the area of marketing systems, this has led to a determined effort by the handful of remaining independent vendors, such as Unica and Aprimo, to expand their products’ scope through acquisitions and internal development. These vendors’ true competition today comes not from smaller specialized products, but the still broader enterprise suite companies like Oracle and SAP and business intelligence experts like SAS and Teradata.

But although reliance on suites is one major trend in corporate systems, another, even bigger trend is the movement towards service oriented architectures (SOAs). These involve free-floating functions, called services, which can be shared by multiple systems. Rather than maintaining their own large databases, services import the specific information needed for a particular task and return a result. In other words, they are the exact opposite of the big suites that are tightly integrated internally but mostly isolated from everything else. SOAs offer a way to introduce small, specialized systems within a larger, integrated structure.

You might call it a battle between suiteness and lite.

Resonance (Certona Corporation, 858-586-0646, www.certona.com) illustrates the possibilities of such lightweight integration. Resonance uses neural network technology to identify linkages between behavior patterns and content selections. The most common application is to predict which items a Web site visitor is most likely to purchase. This is pretty important in itself—the company claims to increase total revenue on e-commerce Web sites by five to 25 percent. We’ll discuss later how it makes that happen. But the point for the moment is it accomplishes this with minimal change in the Web sites themselves. All the client needs to do is place some tags on the existing Web pages. These send real-time reports of customer behavior to the Resonance server and receive relevant product recommendations in return. The technical mechanism can be Web services or, even simpler, HTML iframes. (An iframe is a region within a Web page which is controlled by an external program. It is often used to let third-party advertising services to present content to visitors.)

This simplicity of deployment allows Certona to sell its services on a performance basis. The company measures the difference in results between the product recommendations it serves on a client’s Web page and the recommendations the client would have served otherwise. It then shares the increase in revenue. Apart from the small amount of labor required to insert the Resonance tags and send a catalog of available products (typically refreshed daily), there is no investment required by the client to set up a test. Revenue splits range from five to 25 percent depending on the situation.

The technology underlying Resonance is fully self-adapting: that is, it generates recommendations without users defining business rules or building predictive models. This is an important distinction that allows quick deployment, low operating cost and fast adjustment to changes in customer behavior patterns. It is particularly suitable for businesses that offer many different products, where the cost of building rules or models for each item is prohibitive. In addition to product recommendations, the approach is suitable for document searches, suggesting related Web links, targeted online advertising, and individualized outbound emails.

In practice, Resonance works by tracking behavior as customers move through a Web site. It watches not only what they select but where they came from, the path they follow, and the time spent looking at each item. The system starts by simply observing activity during a training period. This may last from a few days to several weeks depending on site traffic. During training, Resonance builds up a history of how previous customers have behaved and thus learns which items are likely to be selected under which conditions. This knowledge is converted into scoring rules that generate multi-value profiles for each visitor and each product. Profiles and scoring rules are continuously updated as new behavior occurs. All this occurs anonymously—the system is tracking Web sessions, not known individuals.

Resonance makes recommendations in real time by selecting the products whose profiles most closely match the cumulative profile of the current session. The system becomes more accurate over time as it observes more data patterns and sees less-common products being purchased.

Recommendations can be further improved by adding more information to the mix, such as profiles of registered customers and standardized product attributes. But these are optional and typically much less important than behavior during the current session. The vendor states it begins to have a useful profile for an anonymous visitor after as few as three or four clicks.

Recommendations can also be filtered against conventional rules, such as not offering a product the customer has already purchased or only recommending products within a given category. These rules are set by the client, although Certona staff must currently load them into the system. An interface to allow clients to enter rules for themselves is planned for future deployment.

Clients do have access to daily Web-based reports on site performance, including revenue per visit, items per order, average order size and conversions. The system also reports on visitor movements from one page to the next.

One side benefit of Resonance is that the product profiles themselves can serve as a way to classify and group related items, even if no previous categorizations exist. This can be very important in applications such as organizing document or media collections.

Certona, previously N-Space Technology, has been evolving its technology for several years. It began work on Resonance in 2004 and released the system in 2005. It has signed about a dozen clients since then. Resonance is offered as a hosted service only.

* * *

David M. Raab is a Principal at Raab Associates Inc., a consultancy specializing in marketing technology and analytics. He can be reached at draab@raabassociates.com.

Leave a Reply

You must be logged in to post a comment.