By Jeff Liebl, Vice President, Marketing & Business Development, eBureau - 

As consumer lead generation efforts migrate from decades-old direct mail practices to online marketing and advertising techniques, that old reliable offline standby—the business reply card—is being supplanted by the now ubiquitous Web-based registration form.  I can't cite an industry statistic, but I've got to believe that the number of times someone has gone to a landing page and filled out an online registration form now has to be in the many billions of instances. 

To an online marketer who buys leads generated by registration forms via cost-per-thousand, cost-per-click or cost-per-lead advertising, such leads can cost less than $1 to more than $100 each.  What marketers do with all these leads runs the gamut, from loading them into next quarter's newsletter distribution list to routing them to the next available call center sales agent. 

It’s time for a quantum leap in judging lead quality before purchasing online leads. 

If lead generators could gather far more information about the consumers behind their leads than is currently obtained, it would open up a new world of possibilities for buyers and sellers. The problem is, with online registration forms, shorter is better.

The more fields that you require to be filled in, the higher your dropout rates. For the answer to this conundrum, we need to take a page from traditional offline marketers (think Book of the Month Club) that have long used external consumer demographic data—coupled with predictive modeling techniques—to help them understand which prospects will actually pay the monthly invoice after receiving the free books or other merchandise up front.

There is a wealth of consumer information sitting in proprietary databases—such as age, gender, marital status, presence of children, homeownership, education level, estimated household income, past purchasing habits—that can be harnessed to provide a more complete view of a consumer lead.

A third-party information service provider can append these qualitative attributes to online leads in real-time, providing a more comprehensive view of each person who fills out a Web site registration form. For example, is someone who earns $18,000 a year and doesn’t own property a good candidate for a homeowner’s insurance policy? Or a second-mortgage?

Taking predictive modeling one step further enables marketers to answer the following questions before they purchase leads: Can I predict whether this lead will convert? How do I make smarter follow-up decisions?

Ultimately, what we all want to know is whether an individual sales lead will convert into a new customer.  By using predictive modeling techniques, an information services provider can deliver a “lead quality score” for each and every new online lead generated, in real time.  By knowing which online leads are more likely to convert on an individual basis (versus a source-level basis), you can make more intelligent routing and follow-up decisions for every lead as they come in. 

In this way, you can ensure that the highest scoring leads get the red carpet treatment and don’t slip through the cracks, while little or no time and money is spent on low-scoring leads that have nearly zero chance of becoming customers. This technique is proving itself out in many vertical industries, including automotive, cable/satellite television, higher education, entertainment/media, financial services, healthcare and consumer medical equipment, home improvement, and many others. 

The bottom line is that marketing ROI doesn’t end once a consumer has registered on a landing page, it has just begun. Tools now exist in the real-time, interactive world that can help marketers make better decisions and further move the needle in the performance of their online lead generation campaigns.

Jeff Liebl is Vice President, Marketing & Business Development at eBureau, based in Minneapolis, MN. He can be reached at jeffliebl@ebureau.com.