Filter Scoring Models for Customer Audiences 📶

Time and time again, we've heard feedback from Correlated customers that the more granular control they can have over how their PQL Scoring Models are built, the happier they'll be. So, we listened!

Introducing "Filters" for Scoring Models!

Now, in addition to having control over the goal set for your scoring models and the customer data that goes into the models, you can also define "filters" for the types of accounts or users that should be scored. To see how it's done, let's walk through an example:

• You have a high volume of self-serve accounts that sign up, and your reps need to focus on the ones who are most likely to convert.

• First, set the model's "filter" to look only at customers who are on your free self-serve tier.

  

• Next, set the "goal" to indicate a successful conversion, for example adding a credit card, or ARR > $0.

  

• Finally, Correlated will score all self-serve sign ups moving forward on their propensity to convert to paid, so your reps can focus on the accounts with a "high" score and close more deals.

  

Get started building the perfect PQL Scoring Model in Correlated today!