Lead Scoring Is Broken - Here's the 3-Part Fix

Bad lead scoring usually isn't a model problem. It's a data problem. Here's what's actually going wrong, and what the fix looks like.

The coverage crisis: Most databases work off a single source. If there's no direct match, that lead disappears. The solution is a waterfall approach: query a second source, then a third, until you get a hit. Done right, this takes your effective market coverage from under 50% to 80-90%. Explorium handles this natively, querying across multiple providers automatically so fewer leads fall through the cracks.

The identity crisis: A lead score is only as good as the record it's attached to. If your system treats Google and Google Cloud as separate companies, you're already working with fragmented data. Canonical identity - one stable, permanent ID per entity across all your sources - fixes this. It's what makes enrichment trustworthy.

The delivery crisis: Great data that stays in a spreadsheet does nothing. Scores need to move into the tools your team actually uses: CRMs like Salesforce and HubSpot, orchestration layers like n8n, or direct developer APIs. That's where scoring turns into action.

Fix all three and you stop reacting to the market. You start predicting it.

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