Why Sales Should Stop Ignoring Lead Scores
Much to the chagrin of marketers far and wide, many B2B sales reps have been conditioned to ignore lead scores over time.
The scores just aren’t relevant for one reason or another, causing the rep to feel like the leads are weak and that marketing is leaving the sales team high and dry.
It’s true that no marketer ever wants to hear that the scoring model they toiled over isn’t all that helpful. But the problem is that traditional rules-based lead scoring models can only account for a small subset of data about prospects and customers.
After all, one person downloading a bunch of whitepapers doesn’t mean his or her company is necessarily in a good position to buy. But there could be a bunch of unengaged leads just hanging out in the database from companies that could be in a really good position to buy. If they haven’t opened your emails or visited your site in a while their traditional lead score isn’t ever going to go up.
To help show the impact, let’s go through an example.
You are a marketer at a data security company. You received a lead from an online retailer in your database who attended your webinar six months ago and they never came back to your site after that. A couple weeks ago a bunch of their customers had their credit card information stolen and they made the news for it. That company will likely be scrambling for ways to ensure the issue never happens again, right? This would be a perfect opportunity for your company to target.
Or let’s say you’re a SaaS company with a product targeted to developers. Maybe you have a contact in your database from a sales guy at a tech startup who downloaded your case study last year. But his company didn’t have enough revenue based on your profiling so they never MQL’d. Perhaps they recently just scored a big round of funding and now have the means to buy your product.
Seeing the Full Picture
Out of the box, your engagement/demographic-based lead scoring isn’t going to relay that kind of account/company level data your MA and CRM systems that represents real-world buying triggers. Sure you might be lucky to catch it the news, but not always – especially if you’re dealing with a super high volume of leads. That’s where predictive lead scoring can really help automate filling in those data gaps for B2B marketing and sales teams needing that account-level info by pulling in tons of external sources. Here’s a look at some sample predictors from external and internal sources.
But of course even after all that new data is pulled in via predictive scoring and the leads are re-scored…a score is still a just a score. Sales needs to have faith that the highest scoring leads are truly worth their immediate attention (if the predictive model is truly predictive) and Marketing needs to decide how to re-segment their leads based on the new data. My colleague Keith Burrows has recently shared 10 best practices to ensure success with predictive lead scoring.
How Can You Get Sales to Believe in Lead Scores Again?
Start by taking a different approach to lead scoring as a whole and be able to admit to your peers that the current system isn’t working. A successful predictive lead scoring deployment is a team effort. Sales management and operations should absolutely be included in the decision and roll out process. And once predictive scoring is implemented, marketing and sales should work together to track funnel progress to ensure the model in place is truly predictive. Once marketing and sales are finally on the same page about lead quality, you should be seeing a huge lift in opportunity to win conversion rates.
Image Credit(s): Leah Jones