Four Dimensional Lead ScoringI don’t know about you, but when I get an MQL or SQL lead notification or check out someone’s lead score, I see a number. One number. If it’s a high number, greater than some threshold we have set or some imaginary threshold in my head, I call the lead and find out more about them. Sound familiar? It should. That’s pretty much how all marketing automation systems and CRMs work. What if we could do better than that? What if we could tell, at a glance, what’s really up with this lead and how we should approach him? That would be nice. Are you listening marketing technology companies?
The Problem With Linear Lead Scoring
In a nutshell, the problem is that we are taking a multitude of important factors and combining them into one score, which doesn’t tell us much at all about the person who is our lead. It just says this person has checked enough “boxes” to become a truly qualified sales lead, at least in our scheme of things. But is this accurate?
In most lead scoring systems there are many ways to get points, some of them weighted more heavily than others. Still, there are many possible paths, for example:
- A person who “goes to school” on your content, visits every page and downloads everything—probably not a customer-in-waiting
- A person who inadvertantly fills out your “ask for a consultation” page but only intends to inquire about a job or to try to sell you something—despite your best efforts, a waste of your time
- A person who is checking you out but has no intention of ever buying from you
Lots of other possibilities, probably thousands in fact, if you have a fairly sophisticated lead scoring algorithm.
What Would be Better?
Let’s break down our marketing metrics into a few important categories that inform us about our lead’s qualification and intentions. Then, we can design both lead scoring and our content strategy to find the signal in the noise. Here are my top four categories.
Before we even get started, we have hopefully put together a profile of each one of our likely buyers and their influencers based on interviews with current customers and reps. In these profiles we want to capture the essence of these buyers—which factors govern their decision to buy from you. With that information, we can start to measure a lead’s “fit” to our ideal buyer personas, for example:
- Functional role in the company/department
- Pain points
- Role in the buying process
- Company size
- Background (previous jobs)
- Years in company and industry
- Country, region, community
Where is our lead in the buying process? How can we tell? By the content they have consumed, which is mapped to buyer persona and buyer journey (a.k.a. sales funnel) stage—and, oh yes, two more parameters to be introduced shortly. What do we measure?
- Consumption of specific content mapped to buyer journey stages
- Visits to pages mapped to buyer journey stages
- Interaction with specific forms and questions designed to capture intent and timing
- Direct engagement with marketing and sales reps
- Type of engagement with marketing and sales reps
- Updates to lead status from MA and CRM by marketing and sales reps
This is all about the volume and quality of interactions with our content marketing and demand generation content. Most lead scoring is heavily weighted toward this category, but as I mentioned earlier, engagement alone can be misleading. What are we measuring?
- Number of pages visited and repeat visits
- Number of form visits and submissions (conversion rate)
- Number and type of CTAs clicked
- Number of emails opened and clickthroughs
- Number of blog visits
- Blog subscription and number of comments
- Unsubscriptions from email, blog (negative)
- Follows, likes, retweets, +1′s in social media
- Number of marketing and sales calls
How fast is your buyer progressing through the journey? What does this tell you about her urgency for more information leading to an imminent sale? Wouldn’t you like to know that so you can prioritize and put the effort where it’s needed most? Here are a few ways to get that information.
- Date/time of last engagement
- Elasped time between first and most recent engagement
- Number of engagements during the last day/week/month
- Amount of time spent on key pages
- Bounce rate on key pages
- Elasped time between form conversion and actual content download
Visualizing Four Dimensional Data
Let’s not overthink this. Yes, we could construct a multi-dimensional scatter plot and try to make sense out of it. Unfortunately, most of us aren’t wired that way, so we would probably just give up trying to interpret it. Instead, why not keep it simple? Let’s take scores for each category, rank them from 0-100 and color code them (0-33 red, 34-67 yellow, 68-100 green). Here’s a possible 4D lead score plot.
Persona Journey Engagement Velocity 85 35 40 10
How would you interpret such a plot?
Persona: This person is nearly an ideal fit and should, if you do things right, ultimately become your customer.
Journey: Not ready to buy, but is definitely ready to be nurtured with relevant mid-funnel content.
Engagement: Fairly engaged but not in an extraordinary way. Keep up the good work with lead nurturing and content personalization. Check velocity for immediate needs.
Velocity: This one is slow and has not been engaged lately. Probably needs additional nurturing right away with some fresh content featuring new approaches or available features.
Overall: I would categorize this person as a “qualified browser.” Not ready to buy. Marginal readiness for a sales call. Lead has gone “stale” recently and should be nurtured immediately.
A few possible scenarios:
Scenario 1—Call now, it might already be too late:
Persona Journey Engagement Velocity 75 75 60 75
Scenario 2—The student or competitor:
Persona Journey Engagement Velocity 10 75 90 60
Scenario 3—The vendor trying to sell you something:
Persona Journey Engagement Velocity 50 10 10 90
Scenario 4—The job seeker:
Persona Journey Engagement Velocity 0 10 75 90
Scenario 5—The opportunity, call and nurture right away:
Persona Journey Engagement Velocity 90 50 60 90
Is this approach available now?
Not that I know of at the moment, but I hope so soon. For those of you who are software developers and idea generators, this is the kind of value-added approach that could separate you from the competition; it’s useful to both Sales and Marketing and probably wouldn’t take much additional coding to implement into existing marketing automation platforms. Having said that, it would still be up to us marketers to implement a sensible 4D scoring system that fits our buyer personas and journeys and to set up workflows to take action on the results.
In my next post, I’ll take this 4D approach to the next level in terms of Content Mapping.
Photo credit: SFU Public Affairs and Media Relations
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