Working on Lead scoring model

[tusharwagh1]

Hi,

Currently, we're working on a lead scoring model. In lead scoring, we employ demographic and behavioral scoring. We categorize leads into four groups based on their scores and engagement: A, B, C, and D. We represent this on a XY axis graph with demographic score on one axis and behavioral score on the other.

By targeting individuals according to their score, the BDR team can focus on A's and B's. They can wait for C's and D's to reach the threshold before contacting with them. Any thoughts?"

[Dave_Roberts]

There's a few things I like about this approach:

1. The way you're visualizing the total audience is a nice way to see it en-mass and sort of get a snapshot of your database in a chart that you can compare over time to track your progress. I think something like this goes a long way in taking a bunch of complex data and presenting it in an easy-to-understand way for anyone who's on the outside looking in.

2. The way you've got your groups split up into A,B,C,D means that you can treat each of those cohorts differently in terms of how you market/sell to them. I've never really liked the "one-size fits all" marketing where actively engaged members of your database are treated similarly to new members and I think this is a step in the right direction. I do really fancy the idea of having an "A" group which you continue to nurture into an "Advocate" cohort (flipping the funnel) to help make it easy or desirable for those folks to spread the good word about your product and their experience. I think your sales folks will also appreciate this delineation. 

In terms of "reading the chart", there might be cases where moving up and to the right (higher Demographic AND Behavioral score) doesn't necessarily mean "the best" leads. For example, someone might not be within your target demographic, but be really engaged and ready to buy compared to someone in your ideal demographic with your ideal behavior set who has more options to buy and might not close as often. I'd think about trying to keep an open feedback loop with your sales team to try and discover which leads close and where they sit on your XY chart to see if the top right of the chart really is your sweet spot or if there's somewhere(s) else on the chart where lots of deals are closing by comparison. This might give you some insights into when it's time to tinker with your Demographic or Behavioral model to optimize against the deals that really close and keep improving that process into the future. 

[tusharwagh1]

@Dave_Roberts You've highlighted some excellent points about this approach! Will you please share thoughts on marketing sales coordination in this model.

[Dave_Roberts]

@tusharwagh1 -- I grabbed a scatter plot image from Google to help communicate a few ideas here, but for the sake of this example let's pretend this is actually your Behavioral vs Demographic scatterplot chart of your database of users and you've drawn some divisions in there to separate your A,B,C,D user groups. 

Once you've formulated this chart, you're able to see the folks in the B and A categories and ship those over to sales for a pitch. Let's say you maybe add them to a list of some sort as "ready to pitch" or something to that effect. Then your sales team takes the leads and pitches them and those deals either close of they don't. The simple way of looking at this might be as a percentage - let's say sales comes back and says something like "of the 19 leads you passed us, 12 closed and 7 did not. That's 12/19 or 63% of the qualified leads that we were able to close a deal with. What could we do to improve this?"

Now, let's say sales hands you back a list of the leads that closes which you cross-reference with your chart and highlight the winners (closed deals) in green and the losers (not won) in red. This lets you see the "clusters" of winners/losers in each category more clearly. That chart would end up looking something mor like this:

You'll notice that in the B group, you've got 12 leads, 8 winners (66%) and 4 losers. In the A group, you've got 7 leads, 4 winners (57%) and 3 losers. You'll also notice that the folks in group B are kind of clustered together around the "4" line and on the right side of that column. Being able to see this view and having this view informed by the sales outcomes can help you to think about your behavioral and demographic scoring models to adjust them for the sweet spot (that cluster of folks in B). 
For example, if your initial thought is to continue to nurture leads toward the A category, you might instead think about getting them into that sweet spot in B b/c those folks are actually buying at a higher rate. This might mean looking at what behavior and demographic data those users have and increasing the value of those in your scoring model and re-charting this. The idea there would be to get that cluster of winners in B into the top-right of the chart into the A column so it was more aligned with what sales would want (more winners) and more accurately reflected the idea that a higher behavioral-to-demographic ratio represented a more qualified lead. 

The first big idea here in summary might stated more simply as: Close the loop with sales and identify the winners from the losers, then look at what the winners are doing and tinker your scoring model(s) to value the things that winners are doing more than what losers are doing. If I were to put myself in the shoes of a salesperson who was either handed a list of 19 leads or a chart like this where I could see the clusters of winners and losers I think I'd prefer the later and be more likely to engage w/ the marketing team to help dial in that sweet spot and make everyone's life easier.

Another idea that comes to mind for marketing/sales coordination when I look at this chart is in the ability to communicate "what's coming next" on some sort of regular cadence to the sales folks. Quick aside - when I worked in a restaurant back in the day, we'd communicate to the kitchen folks that there was a line-up at the door so they could get ready to jam b/c there's a little delay between seating folks and taking orders but then it all shows up in the kitchen and they get slammed. Knowing that it was coming and being able to get ready kept people in better spirits and likewise, knowing when the line at the door was slowing down gave the folks in the kitchen some sense that they'd get a reprieve soon from the rush. In this same vein, you could look at this chart and give your sales folks a heads up that there are lots of folks in the C category who care moving "up" the chart and will likely graduate into the B/A category next and be ready for them to sell to -- or vice-verse (not in the chart) that there was a big gap in your C group and that sales might be more sparse in the next cycle so they could focus more intensely on the leads they've got now to drive up the conversion percentage.