Fair Issac Forms New E-Business Consulting Practice

Share this article:
Fair, Isaac and Co., Inc., a customer analytics and decision technology vendor, said yesterday that it has formed a new e-business consulting practice called Digital Marketing Science.


The San Rafael, CA company said that it started the division to create a new e-marketing model that will help e-marketers make informed online decisions. It will combine First Isaac's analytics with advanced marketing science techniques.


The service will extract information from e-commerce data to help optimize e-marketing decisions ranging from strategic decisions such as "Should we build a call center or be purely Web-based?" to tactical decisions such as, "How can we improve our conversion rates and customer acquisition costs through targeting and Web site personalization?"


The formation of Digital Marketing Science expands Fair, Isaac's commitment to e-marketing-related Internet services, a category that industry analysts believe will grow to over $60 billion by 2003, a better than five-fold increase from 1999.


Tom Grudnowski, Fair, Isaac's president and CEO, said that his company is ideally positioned to serve sophisticated e-marketing needs because of its technology and deep expertise in powering "better decisions through data."
Share this article:
close

Next Article in Database Marketing

Sign up to our newsletters

Follow us on Twitter @dmnews

Latest Jobs:

Featured Listings

More in Database Marketing

Making Data Breach Readiness a Priority

Making Data Breach Readiness a Priority

5 ways marketers can prepare for possible data breaches.

What's H-appending? DiscoverOrg Taps Marketo's Webhooks

What's H-appending? DiscoverOrg Taps Marketo's Webhooks

Cloud-based marketing automation behemoth Marketo joins forces with marketing intelligence company DiscoverOrg to improve its data collection capabilities.

A Toast to Marketing Attribution

A Toast to Marketing Attribution

Vino accessories and storage company Wine Enthusiast indentifies top and underperforming affiliates using algorithmic marketing attribution.