Attention

Lead routing that matches each buyer to the right rep

Sent each new lead to the rep most likely to win it, based on deal history and shared background; win rates rose 30%

  1. The problem

    Leads were routed by segment or territory, to the enterprise, mid-market or SMB team. That logic ignored whether a specific rep was a good match for a specific buyer, even though Jacob kept seeing calls go better when the rep and buyer had something in common, like a favorite football team, a hometown or a university.

  2. What they built

    A routing model built from Attention's own deal history. Jacob and his team combined CRM records with call transcripts and enriched company data to find where each account executive wins and where they struggle, by region, segment, industry and shared interests. One finding: the rep with a UK passport closes international deals at a higher rate than the rest of the team. When someone books time with Attention, the lead is now routed to the best-fit rep.

  3. What changed

    +30% win rate since routing to the best-fit rep

    Jacob reports a 30% lift in win rates and 25% faster time to close since routing opportunities to the best-fit rep. He also says reps enjoy selling more because they talk to buyers they have more in common with.

  4. So what

    Leads go to the rep with the best record for that kind of buyer, based on the team's own wins and losses rather than gut feel or territory alone.

Under the hood

For GTM engineers

Salesforce deal data (firmographics, amount, stage, win/loss, closed-lost reasons) joined with the Attention API, which mines call transcripts for champions, economic buyers, competitors, personas and geography, and Deepline for account enrichment. The analysis and new account scoring models were built in Claude Code after a historical rerun of all Salesforce data, with Deepline re-enriching the CRM. Best-fit matching is embedded in the live booking workflow.

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