Marketing automation platforms encourage one way to score leads. They use implicit and explicit scores, where implicit score represents activities taken by your leads and explicit relies on the exact values in fields like title, company and demographics. But is this the best way to score leads? With all the capabilities inherent in marketing automation, why are we tied to only tracking two scoring dimensions?
Today we develop lead scoring strategies by thinking the way our sales people think, assuming certain factors mean more than others and going with those for implicit/explicit scores. We only pass leads where both scores are high enough to warrant a sales call.
But there are more dimensions on which to score leads, and we need to get past some of our assumptions. Most importantly, by splitting out different parts of your scoring, you’ll be able to better track and report on your programs. How can you do this?
Conceptualize the different factors that make a lead good for follow up. Your sales people know the most about this, so start asking them questions. How would they describe their best leads? What activities do they take? What characteristics do they share? Can you incorporate those thoughts into your lead scoring program? Below are some examples of factors to consider (most of them are already a part of your current scoring systems):
- Decision maker: Does the lead have buying authority? Will they be the one who makes the final decision?
- Job title: What is the person’s job title? Does it help you differentiate people who you think would be good leads?
- Industry segment: Are there certain industry segments that your company sells more to?
- Individual visits (overall or by content type): As an individual, did the contact visit a lot of web pages? Can various web pages be classified together in a way that makes sense for lead nurturing or sales follow-up?
- Individual downloads (overall or by content type): Did the lead download different white papers making her a more likely sale?
- Events attended: Does the lead show a lot of interest in your company’s webinars or live events?
- Company-wide activity: Sometimes a decision maker may not do their own research on what they want to buy from your company, but others may. Tracking overall activities by company (or account) may help to identify good leads.
- Company-wide spend: How much does a company already spend with you? If they spend a lot, but submit a form, there may be a good opportunity to up-sell.
- Top companies (by domain, company name, etc): You may have a list of top companies you definitely want to close. Membership in this group of targets could be a great way to score your leads.
- Form submissions: Some forms may be better than others. Score “Contact me” forms higher as they show real interest in speaking to a sales person.
2) Choose which factors seem to make the most sense for your business and score on each separately
Wait a minute, you might say. Why would I break down my explicit and implicit scores into their contingent parts? Because you want to isolate different variables and see what works.
From the above, perhaps you choose decision maker, industry segment, individual activity, company-wide activity and top companies. To score on all these, make a matrix …
|Rating = 1
|Rating = 2
|Rating = 3
|High-level decision maker
|Low-to-mid-level decision maker
|Not a decision maker
|We specialize in these industries
|Related to industries where we really focus
|Peripheral to the areas where we specialize
|Individual shows lots of activity on our site
|Individual shows some activity
|Individual shows little to no activity
|Company shows lots of activity on our site
|Company shows some activity
|Company shows little to no activity
|Lead’s domain matches our top 50 targets
|Lead’s domain matches targets 51-200
|Lead’s domain doesn’t match any top targets
Your leads will be scored 1, 2 or 3 for the five factors above. But how will sales know which prospects they should call? At the beginning they won’t because you need to test which of the factors above really makes a difference to your conversion rates. You want them to call all leads, or perhaps all leads who submit a “contact sales” form and a random 25% from the rest.
3) Report on the results of your scoring
Once you decide on the factors above and implement your scoring program, report on conversion rates by factor, by rating. Here you’re looking for correlations – does a higher decision-maker rating result in a higher conversion rate? What about industry segment? Below is a sample chart on what your results could look like.
Conversion rates by factor by rating
|Rating = 1
|Rating = 2
|Rating = 3
In this example, the factors for decision maker, individual activity and company-wide activity point to better leads. If you have enough revenue and cost information, try figuring out your ROI per factor per rating. You may find that all your leads have a positive ROI, in which case you’ll want to send all to sales. But flag better ones for quicker follow up.
4) Use results to improve your ROI
With this matrix of results, you can isolate various conceptualizations you’ve made and see if they work in the real world. If they do, configure your marketing automation system to only send to sales based on those scores. But if they don’t make sense, replace them with other ideas to continually refine and improve your lead scoring program.
Just because different platforms use template lead scoring programs showing implicit and explicit as your only dimensions, don’t feel like you’re stuck. You can use as many or as few dimensions as you like to score your leads. You may come up with 10 areas you think make a difference, but find in reporting that only 3 actually correlated to statistically significant results.
Overall, make sure you score leads based on what makes them a good lead rather than on what others tell you is a good scoring system. Brainstorm various ideas, test them, get results and use what really works. Your company will reap the benefits.