Five Common Lead Scoring Mistakes

We know these mistakes because we’ve made them—that qualifies us as experts as long as we help clients NOT make these mistakes again. The assumption is that you ARE scoring leads. Mistake #1 would be that you are not, so let’s start with a simple scoring plan. You need to be collecting qualifying criteria to score, and the basic criteria are:

• Interest in your products (some identified need)
• Opportunity size (how big is the company, how many likely users)
• Intent to purchase (do they have a budget established, etc.)
• Purchase influence (is the contact the decision-maker [economic or technical], an influencer, or just part of the mob)
• Timing (when are they going to buy)

More advanced attributes include:

• Pain (what challenge are they trying to solve)
• Fit (how well do your solutions fit their challenge)
• Buzz (have you deployed successfully in companies they care about)
• Reference ability (can they help you enter new business segments)

Many companies use a simple BANT (Budget, Authority, Need and Timing) criteria and build their score from that. Then they use opportunity size to select the appropriate sales organization. Regardless of how you do it, you wind up with something that looks like “hot, warm, cold, useless” or A,B,C,D, which leads to…

Mistake #2: Pejorative labels

What’s a C or cold lead? Usually, it simply means the timing isn’t right. Then why are you giving it to the sales force? What will they do with it? What would you do with it if you were selling? So, what you are telling them is, “Here, ignore this.”

What’s the difference between an A (hot) and a B (warm) lead? Often, it is that the sales force HAS to report on every A lead they fail to close. That makes hot leads a liability and the source of many arguments. “It wasn’t hot, it was warm at best. Took me months to close it. I had to go find the decision-maker.” We once did a hugely successful pay-per-lead program that disintegrated over arguments concerning what was warm or hot.

Would you like to eliminate the conversation entirely? Have an arcane scoring system that no one completely understands but you. What we really like are three digit numbers derived from an automated scoring process with no score less than 100. You’ll never hear, “It wasn’t a 233, it was a 170 at best.” Sounds like a cheap trick, but it works wonderfully and you can use the scores to really manage the leads and results.

Mistake #3: Casting the process in stone

The best scoring processes work backward from results. You start off by scoring and distributing by assumption, then you take the leads that made it to the informational meeting stage and see what factors show up most often (we don’t recommend using conversion to sales as the starting point—there are too many sales force variations that you don’t control). Increase the weighting of the dominant factors. Continue to do this on a quarterly basis and your scoring will become highly predictive and will accommodate to market shifts.

Mistake #4: Casting the score in stone

Today’s cold lead is tomorrow’s hot (or better yet, today’s 134 is tomorrow’s 247). A cultivation process should be a constant attempt to rescore all leads. Someone reads your eNewsletter and updates their profile. New score! Someone reads your newsletter for six months and never updates. BUT, they originally said they were a year away from making a decision; now it’s six months later and they’re still listening. New score! Your telemarketer gets back in touch and finds more information about their needs. New score! The score is really their position in the sales funnel. Once you get them where the sales force can effectively do something with them, they graduate to real leads.

Mistake #5: Assuming low score means low value

Too often we see people throwing away leads that have a “low score.” Except for the truly unqualified respondents (competitors, students and the purely curious), they are actually the most valuable leads you have. Using data from tests that we’ve run numerous times, we surveyed all leads over a year old and asked them if they bought a solution (not just the client’s version, but all the competitors, too). In every survey we did, from 80 to 90 percent of the respondents bought a solution, regardless of their initial lead score. Now look at your lead score distribution from a typical campaign: 10% hot, 20% warm, 60% cold, 10% junk. Where’s the money? People also assume old leads are worthless. During a recent database cleanup effort for Adobe using email and mail to re-qualify lead data, our client actually wanted to toss out anything over two years old. We convinced them to test a sample of their data and actually got a marginally higher response rate and a better average qualification score than their new data. Considering that the high-quality leads cost them at least $100 each to acquire (probably more), the several hundred thousand records were even more valuable and well worth the time and effort.