Manual scoring can lead to bias because businesses create their own rules for different actions. Scoring based on AI will focus more on identifying patterns across historical lead data. However, AI is only as good as the data it learns from. If certain leads, actions, or outcomes are missing from the data, the same gaps can continue to appear in the AI’s scoring patterns. To avoid such a scenario, our team regularly goes back and manually reviews old leads and missed opportunities.

AI can make lead scoring smarter, but human review helps make sure the system is not learning from its own blind spots.

How does your team handle this?

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Sergey Kargopolov27d ago

I guess we are old school with our project 🤔. We created a formula and then hard coded its business logic in the code.

Problem with AI lead scoring

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