You have learned about overrides but want to learn best practices on the overrides that will make the most sense in your model? Follow the guidelines of this article to get examples and tips 🎲
Prerequisites
You have an Architect or Admin MadKudu role
What is an override?
Overrides are rules you can add to your model to restrict the scores of your leads and contacts based on demographics, firmographics, or technographics traits.
To learn more about overrides, follow this link 🔗
Overrides can:
boost the score of leads
downgrade the score of leads
avoid the score of leads falling beyond or going beyond a threshold
Override downgrading the score of leads
The idea is to make sure certain categories of leads will always be scored low whatever their other defining traits. This is particularly relevant for leads that you don't want to send to your sales team. Here are some classic overrides our customers usually create:
Score spam emails low
Score student emails low
Score leads from your own company low
Score leads from your competitors low
Score leads from 'low GDP per capita countries' low
Override boosting the score of leads
The idea is to make sure certain categories of leads will always be scored good or very good whatever their other defining traits. This is particularly relevant for categories of leads that you're newly targeting or some of the big companies in the market that may have not performed well in the past but that you still want your sales team to talk to. Here are some recommendations:
Score fortune_1000 emails at least good or very good
Score target account emails at least good or very good
Score leads from 100,000-employee companies at least good
When boosting segments of leads, also try to think about your ICP or certain specific technologies that your product integrates with. You don't want to miss out on these!
Override boosting an ICP persona
To create such overrides, the best way is to first create a persona computation and then add an override focused on this computation. Here's how to create a persona computation.