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Overview
Predictive scoring models in Madkudu can help route and prioritize either people (leads & contacts) or companies (accounts).
MadKudu offers 2 main categories of scoring models:
the Customer Fit model
helps answer "who is this person?", "is the company they work for a good fit?"
the Likelihood to Buy model (Behavioral)
helps answers "how are they using our product?", "what actions are most correlated to conversion?", "is now a good time to reach out?"
The third category of prediction models, the Lead Grade, is simply a combination of the two others.
The Customer Fit model (demographic)
Uses firmographic and demographic data — which allows you to check whether or not a lead or account matches your ideal customer profile (Who is this lead? Does this lead look qualified?). Because the model uses firmographic and demographic data as input, the scores will not change much over time.
The Likelihood to buy model (behavioral)
Utilizes your behavioral data (in-app usage, website activity, marketing campaigns, etc.) to measure engagement of the lead or account (What has this lead been doing recently? Has the lead tried to engage with you?). Because the input of the model uses behavioral data, the scores are recomputed several times throughout the day. The behavioral score is all about timing.
The Lead Grade
Combines both Customer Fit and the Behavioral components. It enables you to identify the leads that are the most qualified and the most engaged. Because the Lead Grade has a behavioral component, it is also recomputed several times a day. Learn more about lead grades here.
Note: MadKudu does not support nor offer an "Account Grade"