pipedrive

Prospect → enrich → AI-score → route into Pipedrive

Find prospects, enrich them, run an AI Column to score 0-100 against your ICP, and route only the top tier into Pipedrive as MQLs.

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The goal

Filter out the low-fit leads before they hit Pipedrive — your reps only see ICP-matched, scored, enriched contacts.

🟡 Standard~12 min to first value~12–16 per scored contactrevopsgtm-engineer

What you provide.

  • Target accounts list

    Domains or company names.

  • ICP prompt

    Define what a "great-fit lead" looks like for your scoring AI Column.

The action chain.

Each step uses a real TexAu actionKey. Click the step to read the action's full reference.

  1. 1
    Findapollo-enrich-person

    Find decision-makers at target accounts.

  2. 2
    Enrichfullenrich-work-email-enrichment

    Waterfall email + company enrichment.

  3. 3
    Scoretexau-find-technographic-data

    AI Column scores each row 0-100 against the ICP prompt with full row context.

  4. 4
    Syncpipedrive-create-person

    Only rows scoring 80+ are routed to Pipedrive.

What you get back.

  • Scored MQLs

    → Pipedrive

Why this works.

Most teams discover scoring AFTER they have a polluted CRM. Front-loading the AI Column score before the CRM write means your reps never see junk leads. The AI Column passes the entire row context — title, company size, tech signals, recent funding — into a single prompt, not one cell at a time. This is the difference between "score by job title" (low signal) and "score by job-title × ARR × hiring-velocity × competitor-mention" (real signal). Pair with a HubSpot or Salesforce list view filtered to score >= 80 and your SDR queue stays high-fidelity. Common variant: route 60-79 to a nurture sequence and 80+ to the AE.

Deploy this workflow in your TexAu workspace.

Every workflow in the library is one click to deploy. Edit any step, swap providers, or fork it for a new ICP.

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