• by David Dowhan , December 18, 2008

In 2009, we're all going to hear more talk than ever before about what constitutes "quality"  online leads. And there will be plenty of accompanying disagreement about what the word quality means as lead buyers try to squeeze the most out of their pressured budgets.

 

In some markets, it may take days or even months before a buyer can truly assess the quality of a given lead. Moreover, quality can be volatile month to month, even from the same lead source. If you can't reliably measure quality, how do you know if you're paying the right price for leads? How can you effectively manage your call center when lead quality goes up and down?

The overwhelming majority of lead buyers have no idea how to predict which individual leads have the best chance of converting. So it will be up to the best-informed sellers to help educate the lead generation marketplace. One of the best places to look for such guidance is the online education sector, which has historically been one of the biggest markets. Now that sector -- composed of career colleges and online schools -- is leading the way in the most intelligent use of predictive modeling for real-time lead scoring, and it won't be long before other marketers follow suit.

To date, the discussion of online lead quality in online education circles has centered on a number of lead traits, including exclusivity, completeness of data, data verification, lead source and the lead's motivation or intent. However, from the perspective of the more savvy online education marketers, whether or not the leads are "worth it" can be narrowed down to a single, indisputable measurement: lead ROI. Lead ROI is simply how much you paid for a batch of leads and how many of those leads resulted in a sale. These companies are not only insisting on ROI, they want it to be quantified before they buy leads, not after. Sophisticated predictive lead scoring technology -- much the same as that used for many years by offline direct marketers and financial institutions -- makes this possible.

Put yourself in the shoes of an online education marketer. There are a large number of lead sellers pitching you. They all claim to have an abundant source of high quality leads that can be yours for the right price. So, you try a small test with a few of the most promising lead sellers, and the first 500 leads are amazing!

You run the numbers and place a month's order for 5,000 leads at $47 per lead. At the beginning of the month, you get a decent flow of 100 leads per day -- about 33% shy of the 5,000 per month pace you were hoping for. Your call center works the newest leads on a "first come, first served" basis and reports that the leads seem fine. Toward the end of the month, your lead flow increases to 250 leads per day. The lead seller informs you that it has activated some additional high-quality sources, which is why you're seeing the volume increase. Unfortunately, the spike in volume means that your call center is falling a bit behind and new leads may sit a day or two before anyone can get around to calling them.

This goes on for another couple of months until you see the initial student enrollment reports from the leads at the beginning of the campaign. Things are not good. The enrollment rate is down by 20% from the initial test campaigns, which means that your cost/sale is 20% over budget. As more enrollment feedback comes in, things only get worse, since your call center wasn't able to keep up with the volume spike of new leads. You pick up the phone and immediately halt the new campaign that looked so promising just a few months ago.

Here is how leaders in online education tackle the same problem by using real-time predictive lead scoring that taps into huge databases of consumer-specific financial and purchasing attributes. The lead scores tell you that those initial 500 test leads are a combination of high quality and low quality leads. There are generally more high quality leads in the mix, so the overall average lead quality is favorable and worth $47. Using the lead score, you set up 3 pricing tiers: good quality leads are priced at $55, average quality leads are priced at $38, and the worst 8% of the leads are only worth $5. The campaign begins to run at 100 leads per day, but the lead score indicates that the quality of the campaign has deteriorated. Luckily, your pricing tier automatically reduces the average cost per lead to $37. The lead seller also sees the drop in quality within the first couple of days. Since the lead score reports the quality of every lead in real-time, the lead seller uses this feedback loop is able to trace the source of the bad quality back to a couple of new affiliates. They shut down those affiliates and their average price per lead climbs back to $47.

Throughout the month, the lead seller tries different approaches to improving lead quality and identifies some new sources that bring their average up to $50 per lead. These are better-quality leads and worth the extra $3 each. With the increase in volume, your call center is now getting 250 leads more per day. Fortunately, you have used the lead score to prioritize your follow-up efforts. The highest scoring leads are routed directly to your best call center agents and the $5 leads simply receive an email follow-up. Despite the spike in volume, your close rate goes up by 14% this month because you are focusing the right resources on the right leads. Pop the Champagne; you just got a promotion.

All of the above is radically changing the dynamics of how leads are bought, sold and managed. Indeed, coming as this trend does during a steep economic downturn and a flight to quality by marketers, it has the potential to revolutionize the lead generation industry. Reducing wasted marketing dollars is a trend that's fashionable regardless of where the economy is heading.