How to Combine Marketing Automation Lead Scores and Lead Grades - dummies

How to Combine Marketing Automation Lead Scores and Lead Grades

By Mathew Sweezey

In marketing automation lead scoring can often be confused with lead grading, but these two models have several different uses, as follows will illustrate for you:

  • A lead-scoring model is the method for measuring interactions or behaviors. You use lead scoring to measure a person’s sales readiness. Determining sales readiness is typically based on interactions with marketing material and campaigns. Common actions to score are

    • Page views

    • Email clicks

    • Downloads

    • Search terms

    • Campaign touch points

    • Form completions

  • A lead-grading model is the method for measuring demographic qualities of people. You use lead grading to measure a person’s demographic fit. Grades are based on fields in your database and usually use an A-to-F scale, just like the grades you received in school. Common criteria to grade are

    • Job title

    • Company size

    • Company location

    • Company revenue

    • Software used by company

    • Industry

The following shows a person’s lead score based on her interactions with marketing assets, whereas her lead grade is measured from her job title and company size.

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You need to use lead grades as separate database fields in conjunction with your lead-scoring model or you run the risk of sending highly active sales-ready leads to salespeople when they are actually a bad demographic fit.

For example, if you base lead scoring only on engagement with your marketing, your scoring model could identify a college kid doing a research paper as a hot prospect because of his level of activity. If, however, you’re targeting VP-level retail brand managers, your high-scoring college student should be filtered out by a low grade based on the absence of a job title.

If you separate lead scores from lead grades in your database instead of combining them into one score, you can more clearly see the level of opportunity fit on a demographic and activity basis. Separating the two numbers from each other is the easiest way to rule out prospects who are active yet unable to make a purchase decision.