Upgrading Scoring Mechanisms with Insights from the Clay Community
We are looking to upgrade our various Scoring mechanisms and wondering how people have found success doing this within the Clay community. I totally understand how we would use Clay to implement a determined scoring model, but frankly we could use some autonomous / data-backed assistance in determining the model and making it "self-healing" over time. Problems we're trying to solve:
ICP: Are our "fit" definitions correct or do we have an incorrect opinion of our market?
Signals: Aggregating various 3rd party (6sense, G2, etc.) and 1st party (website, inbound touches, etc.) into a single score
Inbound: Prioritizing the right inbound leads for our Sales Development team
Churn Risk
Opportunity Likelihood to close
Account Likelihood for Cross-sell / PLG expansion
Are people building all of those scoring models in Clay or using 3rd party tools (Forwrd, MadKudu, RevSure, etc.)? How are you doing the analysis to determine the models up front?
