In the early stages of a recent client engagement, it became apparent that the schema already in place to determine and assign lead scores was, well: broken. The most glaring symptom was the absurdly high scores: hundreds of contacts had lead scores of more than 1,000, even though the supposed threshold for a sales-ready lead was a mere 100 points.
Amongst companies who adopt marketing automation technology, the problem of lead score inflation is a common one, mainly due to the rudimentary way in which most companies first decide to assign those scores. The basic lead scoring recipe is typically a variation on the following:
* assign positive scores for desired behavior or demographics (e.g. attends Webinar, VP-level title or above)
* assign negative scores for undesired behavior or demographics, or inactivity (e.g. visits career page, located outside of North America, no response to any campaign in 3 months)
The loophole in this design arises when “active” prospects, those who regularly visit a Website or respond to nurturing campaigns, for example, build up lead scores well out of proportion to their actual level of interest or stage in the selling cycle. Using the sample logic outlined above, if a prospect took ANY “positive” action at least once every 2 months and 29 days, his or her lead score would continue to climb indefinitely.
Once a contact’s lead score exceeds the threshold value for sales-readiness or “hot lead,” any further increase ceases to have much relevance. Worse yet, lead scores that are clearly irrelevant can lead a sales team to lose confidence in the overall system, to where they begin to ignore lead scores altogether.
One elegant solution to this problem is to assign “expiration dates” to all positive lead scores. Expiration dates make sense because positive behavior is only truly relevant in the short term. A lead that was very active 6 months ago, for example, isn’t very interesting to a sales rep today. However, in most typical lead scoring schemas, that same lead could rack up 60 points in a burst of activity, and as long as he clicked on an email once every 3 months, that score would never go down.
Expiration dates are programmed as follows: add points, wait a certain period, then remove those same points. The time period can vary according to the importance of the activity, for example:
* Visit a Web page: add 1 point, wait 3 days, subtract 1 point
* Visit a high-value Web page: add 10 points, wait 2 weeks, subtract 10 points
* Click link in email: add 5 points, wait 1 week, subtract 5 points
* Request demo: add 30 points, wait 2 months, subtract 30 points
and so on. Note that expiration dates only apply to behavioral scores, not demographic values. The fact that a company has 100+ employees, or is located in the US, never “expires.” In addition, your particular sales process or revenue model may provide for other exceptions, where certain behaviors represent specific milestones along the success path (e.g. download trial version).
The method of assigning and subtracting scores described above is based largely on our work with clients using the Marketo platform, but the same overall approach could be adapted to work with virtually any other marketing automation system. All credit for developing this approach (and helping with the description) goes to Dan Reed, Spear’s Technical Production Manager and resident marketing automation guru. Thanks Dan!
For more tips on how to get the most from your marketing automation investment, download a free copy of our white paper: “Top 10 Tips For Lead Nurturing Success: How to Get the Most From Your Lead Nurturing Program, and How to Plan for Success if You’re Just Getting Started.”