The Do's & Don'ts of Lead Scoring
By Flora Felisberto
Having implemented lead scoring in the past, I shared the same frustrations with many other marketers -- we’ve spent all this time implementing a sophisticated lead scoring program and sales is not using it. Now what?
Behavioral, demographic, BANT, perhaps all 3? If there’s one thing I learned, it’s this: DEFINITELY keep it simple. Lead scoring is one of those things that’s easy to get carried away with and I urge you not to. In this post, I’ll share lead scoring dos and don’ts as well as some best practices I’ve learned along the way.
The ultimate goal of a lead scoring model should be to help sales prioritize leads. There’s nothing more frustrating for an inside sales person then to have to spend time on leads that have no pain, intention to buy or are just the complete wrong target. In essence lead scoring has nothing to do with generating higher quality leads per se. Rather, it provides a mechanism for marketers to bubble up the right leads. Below is my list of dos and don'ts.
DO pick one kind of score to start with. Because it’s more straightforward and usually has less scoring elements, I recommend starting out with demographic.
DON’T pick random criteria based on assumptions. Start by collecting existing data. What do the leads that advance through your organization’s funnel have in common? What’s their job title, role, company size, revenue range? The same applies for behavior values. For example, in my experience, organic web leads are much more likely to convert and hence should get higher scores. This step is all about identifying your ideal prospect.
DO get sales buy-in. Be warned that if you don’t do this ahead of time, you’ll have to rejigger your scoring model before it even gets out the door. Sales has intelligence that we simply don’t have visibility into. They talk to our prospects every single day and therefore know our audience [in many cases] better than we do. This is also an opportunity to improve the sales and marketing relationship. It creates a shared lead definition that everyone has agreed to. And finally, this is an easy way to establish SLAs for lead follow-up.
DON’T over complicate it. I can’t stress this one enough. In the last lead scoring program I implemented, we went from scoring 4 demographic criteria down to 2. At the end of the day, we realized that only two demographic components really mattered. All the extra scoring was distracting from the elements that really needed to stand out.
DO tie your lead score to something actionable. For example, lead score is a great way to determine Marketing Qualified Leads (MQLs). If a lead reaches a certain demographic OR behavioral score, it should automatically become an MQL. Sales should only follow up with leads that have a high enough score to become MQLs. Because of this, they are much more motivated to understand the methodology behind the lead scores and actually adopt it.
DON’T add up demographic and behavioral score. If you use Marketo, demographic and behavior scores are two separate numbers that are then added together. If you use Eloqua, get a letter and a number instead (which is a much better way to depict the whole picture). Adding two numbers tells you nothing because it could be telling a sales rep to prioritize a lead who is very active on the website (behavior score) but who is the completely wrong target (demographic score). This is a Marketo limitation that is pretty easy to get around. I will write a post on that later.
DO take points away for inactivity, but don’t let the score go below zero. If you keep increasing the negative score, a lead may never bubble up again in the future because it has so many points to make up for.
DON’T be impatient and try to make tweaks to the scoring right away. Give it some time to collect results. As soon as you see data, start revising the scoring to make sure it aligns with the opportunities and deals. For example, did the prospects that advance further down the funnel have the top scores?
It’s important to understand that in most situations, there simply isn’t enough data to build an ideal lead scoring program. Some companies may implement lead scoring with no data at all, and that’s ok. With enough feedback and revisions, you will get there, so be patient.