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Certona Corporation Resonance
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Certona Corporation
Resonance
by David M. Raab
DM News
April, 2006One 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 president of ClientXClient, a consulting
and software firm specializing in customer value optimization.
He can be reached at
draab@clientxclient.com.
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