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Sarah Novotny is the Sr. Editor in Charge of Adotas. Sarah grew up in San Jose, California. Her educational and professional career have taken her to both Los Angeles and New York City where she received a B.F.A. from NYU. As a writer, Sarah has free-lanced for various publications focusing primarily on traditional advertising and media reviews. When not writing and editing for Adotas, Sarah is continuing her acting career in various theatrical and film/television productions.

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Spotlight

eBureau’s Gordy Meyer Speaks

Written on
November 5th 2007
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thinker11.jpgWhen it comes to lead generation, predictive analytics is an invaluable asset. Few industry professionals have the knowledge and experience in this space as CEO of eBureau Gordy Meyer. Gordy took some time to answer a few questions for Adotas, to give readers insight into the success behind eBureau and the importance of predictive analytics.

Where did the idea for eBureau come from?

Before founding the company, I spent the better part of 2 decades as a user and later a supplier of predictive analytics capabilities for both direct marketing and credit and fraud risk applications.  I’d sold my last company, RiskWise, to LexisNexis and was looking for a new challenge.

How is eBureau different from your last company, RiskWise and other predictive modeling and scoring companies? 

For starters, we have a big focus on solving online advertising and real-time marketing applications, which we didn’t have before.  Stepping back from that, the practice of predictive modeling hasn’t really changed that much – it’s still done manually by teams of statisticians using expensive and complicated software.  We really wanted to reinvent that whole process, strip out the time and cost involved, and open up these capabilities to a potentially much larger, underserved market.  Over the past 3 years, we have built an expert system that automates the whole process of building custom scoring models for clients, and we have integrated a gigantic amount of offline consumer data that we use to build those models. Faster/better/cheaper.  Modeling on steroids.  Nobody’s done this, to the degree that we have, so we feel we’ve created a significant competitive advantage for ourselves.

Where does predictive scoring apply in online marketing and advertising?

In the online lead gen space, we’ve created a bunch of regression models that predict the likelihood of a consumer lead converting into a paying customer.  For our bill-me-later customers, we’re scoring to predict the likelihood of follow-up payment – that’s basically a fraud application.  Our goal is to become the equivalent of a FICO score for online leads.  

Is online lead scoring mainly attractive to CPL advertisers or publishers?

Both, but for different reasons.  Buyers love this because the score can help them prioritize follow-up strategies — send the higher scores to the best call center agents and use more intensive direct marketing follow-up campaigns.  Kick back the low scoring leads. And figure out which lead sources to turn off or crank up more quickly.  Lead sellers, or publishers, are attracted to it because they can assess their own media buys on one hand, while positioning themselves as a premium, quality player.  Ultimately, it will drive premium pricing for higher quality leads, and vice versa. 

In which verticals does lead scoring apply?

I haven’t seen one yet where scoring doesn’t add a significant economic value yet.  We’re able to score leads effectively in online higher ed, mortgage, continuity clubs, home services, credit cards, pay day loans, etc.  

What’s next on the horizon for eBureau?

We’ll continue to execute in online lead scoring at the back end of the advertising process.  We believe the industry is heading towards using offline consumer data to make better, more targeted ad presentations at the front end. You don’t necessarily need clickstream behavioral data to better target online ads.  So it’s kind of a new spin on online behavioral targeting.  Or maybe it’s an old spin – the direct marketing world has been using offline demographic and purchase activity data to target direct mail campaigns for decades.  This is just bringing that well-worn practice into a real-time, online world.



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