How to get the best leads at the right price?

Customized predictive models provide a process that evaluates each new, incoming lead, and then automates important marketing decisions.

For many of today's direct marketing professionals, cost-per-lead (CPL) online advertising has evolved to a point at which it now serves as the focal point of integrated campaigns because of the abundance of low-cost, high-volume consumer leads it delivers. As a result of this evolution, online lead generation is currently the fastest growing segment of online advertising expenditures, increasing 74 percent in 2006 to $1.3 billion, according to the Interactive Advertising Bureau (IAB). Furthermore, industry experts forecast that this spending will approach $2 billion in 2007.

However, the outsourcing of lead generation campaigns to third-party agencies, while a seemingly convenient and cost-effective move on the surface, comes with several inherent risks that direct marketers should keep in mind. The most pressing areas of concern for CPL advertisers today involves unevenness in the quality and consistency of the online leads they are receiving from multiple sources, and their inability to understand the value of these leads prior to purchase or during follow-up.

While the process between buyers and sellers of online leads is gradually becoming more transparent, the fact remains that many companies lack visibility into the sources and quality of the leads they are purchasing.

Simply stated, this is the double-edged sword of online lead generation. While large volumes of leads can be generated in a short period of time, the quality of those leads often remains, largely, a mystery until after they hit the call center or mail fulfillment house.

As a result, many direct marketers are complaining about unpredictable conversion rates that, in turn, have triggered a shift among advertisers toward a greater focus on the quality, rather than quantity, of purchased online leads. Thus, in today's online lead generation environment, how does one properly balance these two considerations?

In the end, the costs and risks associated with CPL advertising strategies must be closely weighed against their expected returns. When negotiating with outside agencies that specialize in the generation of sizeable quantities of low-cost leads, marketers must be more intelligent and pragmatic than ever to efficiently manage the costs in the lead-to-conversion process.

For example, using call center agents to pursue poor quality or invalid leads to inevitable dead ends will result in high costs that negatively impact marketing return on investment. To address this dilemma, the marketer must find a practical solution to properly evaluate the reliability of acquired leads, and then specifically determine which resources will be allocated to each lead.

There are definitive lead evaluation tools now available for guiding the decisions of online lead buyers along these lines. For years now, predictive scoring has been used by traditional direct marketers to intelligently segment customer prospects and house file lists prior to launching direct mail campaigns. This approach resulted in better-targeted lists, increased response rates and excellent marketing ROI. Now, in the real-time, online realm, a company can apply the same techniques to "score" online leads using predictive statistical models that accurately measure the probability of actual sales conversion. This approach gives advertisers tremendous power and flexibility to objectively assess the quality of an online lead right up front.

How is this done? First, customized predictive models are developed that utilize past campaign results appended with identity, demographic and behavioral data. Once created, these models provide simple, three-digit scores that can be used to evaluate each new, incoming lead, and then automate important marketing decisions. By scoring every lead received from its source in real-time, marketers obtain insight into and control of their online lead management activities.

The real-time scoring of online leads carries three important implications for direct marketers who rely heavily on CPL advertising:
•This tool gives them a concrete basis for rejecting low-scoring leads altogether. Additionally, many CPL agreements come with scrub rate provisions, so predictive scoring can be used to identify which leads should be kicked back to the provider.
•Scoring allows for better allocation of contact center resources by prioritizing leads with the highest likelihood of conversion. At the same time, this approach enables marketers to avoid the unnecessary follow-up phone and mailing costs on very low-scoring leads that have a near-zero chance of ever converting into a paying customer.
•Predictive scoring can facilitate a rational, tiered pricing structure for online leads, and enable buyers to negotiate and pay varying rates for different quality levels of leads.

Just as banks use credit scores to make instant decisions regarding consumer loan qualifications at different interest rates, predictive scoring can also help direct marketers effectively assess and monitor the consistency, quality and value of their online lead purchases. More importantly, this easy-to-use approach maximizes conversion rates, as well as the total ROI associated with today's CPL online advertising campaigns.

Source: Article by jeff Liebl is vice president of marketing and business development at eBureau.