Overview
Inbound leads decay fast. This pipeline enriches and scores each one within seconds of creation, so the right rep gets the right lead with context already attached rather than a name and an email.
It is fully automated by design — the judgement lives in the scoring rubric, which a human owns and tunes.
Business value
Cuts lead response time from hours to seconds and removes manual research from every rep's day.
Expected outcome
Every lead scored, enriched and routed with a briefing note, within seconds of arriving.
Problems it solves
- Reps spend the first ten minutes of every lead researching the company
- Hot leads sit in a queue behind cold ones
- Scoring is inconsistent between reps
- CRM records stay thin, so reporting is unreliable
Who it is for
- Sales teams with meaningful inbound volume
- RevOps teams standardising qualification
- Founders handling their own pipeline
Benefits
- Response time measured in seconds
- Consistent scoring against one rubric
- Reps open a lead with context already there
- CRM data quality improves as a side effect
Limitations
- Enrichment quality depends entirely on the data provider
- The scoring rubric needs periodic retuning as the ICP shifts
- Enriching personal data has real GDPR implications — check your lawful basis
- Junk in, junk out: bad form data still produces bad scores
Success metrics
- Median time from lead creation to routed
- Percentage of leads correctly routed first time
- Meeting booked rate versus the manual baseline
- Cost per enriched lead
Flow diagram
Every step in order, colour-coded by how much of it runs without a human.
Scroll to pan · use the controls to zoom, expand or export.
Steps
6 steps from trigger to result.
Normalise and deduplicate
- Merge rather than create when a duplicate is found, or reporting drifts immediately
Enrich from public sources
Score against the ICP
Score this lead against our ideal customer profile.
ICP:
{{icp_definition}}
Lead:
{{enriched_lead}}
Return JSON:
{
"score": 0-100,
"tier": "hot|warm|cold",
"reasoning": "two sentences on why",
"disqualifiers": ["any hard blockers"],
"talking_points": ["three specific angles for the first message"]
}
Be strict. A lead that only partially matches is warm, not hot.
- Ask for the reasoning, not just the number — it is what lets you debug a rubric that has drifted
Write the briefing note
Route to owner
AI tools
Each tool records the role it plays and whether it is required.
Integrations
Services this workflow connects to, and how each authenticates.
Prompt library
Every prompt in the workflow, in chain order. Swap the highlighted placeholders for your own values.
Score this lead against our ideal customer profile.
ICP:
{{icp_definition}}
Lead:
{{enriched_lead}}
Return JSON:
{
"score": 0-100,
"tier": "hot|warm|cold",
"reasoning": "two sentences on why",
"disqualifiers": ["any hard blockers"],
"talking_points": ["three specific angles for the first message"]
}
Be strict. A lead that only partially matches is warm, not hot.
Prerequisites
Have these ready before you start.
Use cases
Inbound demo requests
Route demo requests to the right rep with account context already gathered.
Faster first responseEvent lead follow-up
Process a conference list overnight so outreach starts the next morning.
Same-week follow-upPartner referrals
Score referred accounts consistently rather than by relationship.
Consistent qualificationMetrics
Author estimates — treat them as a starting point and measure your own runs.
Accepts
Produces
FAQ
Is this GDPR compliant?
What if the scoring is wrong?
Can it work without a paid enrichment provider?
Reviews
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