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Internet Marketing: Lead Scoring 101 Cheat Sheet (DRAFT) by [deleted]

How Score your marketing leads

This is a draft cheat sheet. It is a work in progress and is not finished yet.


When most people start implem­enting inbound marketing, they're primarily worried about getting enough new leads in the funnel. But once you have a lot of leads, you need to figure out who's really interested in your product and who's just starting to look around.

That's where lead scoring comes in. Lead scoring lets you assign a value (a certain number of points) to each lead based on the profes­sional inform­ation they've given you and how they've engaged with your website and brand across the internet. It helps sales and marketing teams prioritize leads and increase effici­ency.

How to Use Data to Calculate a Basic Lead Score

There are many different ways to calculate a lead score. The simplest way to do it is this:
Step 1: Calculate the lead-t­o-c­ustomer conversion rate of all of your leads.
That's the number of new customers you acquire, divided by the number of leads you generate. Use this conversion rate as your benchmark.
Step 2: Pick and choose different attributes customers who you believe were higher quality leads.
Attributes could be customers who requested a free trial at some point, or customers in the finance industry, or customers with 10-20 employees.

There's a kind of art to choosing which attributes to include in your model. You'll choose attributes based on those conver­sations you had with your sales team, your analytics, and so on, but overall, it's a judgment call. You could have five different people do the same exercise, and they could come up with five different models. But that's okay as long as your scoring is based on the data we mentioned previo­usly.
Step 3: Calculate the individual close rates of each of those attrib­utes.
Step 4: Compare the close rates of each attribute with your overall close rate, and assign point values accord­ingly.
Look for the attributes with close rates that are signif­icantly higher than your overall close rate. Then, choose which attributes you'll assign points to, and if so, how many points. Base the point values of each attribute on the magnitude of their individual close rates.

The actual point values will be a little arbitrary, but try to be as consistent as possible. Example, if your overall close rate is 1% and your "­req­uested demo" close rate is 20%, then the close rate of the "­req­uested demo" attribute is 20X your overall close rate -- so you could, for example, award 20 points to leads with those attrib­utes.

Lead Scoring

The More Advanced Method

This simple method of calcul­ating a lead score is a great start. Note, though, that the most mathem­ati­cally sound method is one that employs a data mining technique, such as logistic linear regres­sion.

Data mining techniques are more compli­cated. Logistic linear regression involves building a formula in Excel that'll spit out the probab­ility that a lead will close into a customer. It's more accurate than the technique we've outlined above since it's a holistic approach that takes into account how all of the customer attributes -- like industry, company size, and whether or not someone requested a trial -- interact with one another.