Lead Scoring

Lead Scoring

When to Use

Activate when a founder needs to evaluate inbound prospects against ICP criteria, build a systematic qualification workflow, score and route leads, establish MQL/SQL definitions, or design pipeline stages. Also use when the user says "which leads should I focus on," "how do I qualify inbound leads," "define my ICP," "set up lead scoring," or "how do I route leads to the right person."

Context Required

From startup-context or the user:

• ICP definition — Who is the ideal customer (company size, industry, stage, geography, use case)
• Lead sources — Where inbound leads come from (website, events, content, referrals)
• CRM and tooling — Current stack for managing leads and deals
• Current customers — Who are the best existing customers and why
• Pipeline data — Existing deals, active customers, prior contacts
• Sales capacity — Who handles leads and what is their bandwidth

Work with whatever the user provides. If they have a clear problem area, start there. Do not block on missing inputs.

Workflow

1. Load ICP and configuration — Read startup-context if available. Establish the qualification criteria across company attributes, person attributes, and use case fit.
2. Parse the lead data — Accept leads in any format (CSV, list, CRM export, single name). Identify data gaps and flag what needs enrichment.
3. Check pipeline overlap — Before scoring, check for existing customers (route to upsell), active deals (flag for sales coordination), and prior contacts (note history). Pipeline overlaps are routing flags, not disqualifiers.
4. Score company fit — Evaluate against company size, industry, stage, geography, and use case alignment. Weight each dimension based on what predicts closed-won deals.
5. Score person fit — Evaluate title, seniority, department, and decision-making authority. A perfect company with the wrong contact still needs routing, not rejection.
6. Score use case alignment — Connect the lead's inferred intent to specific product capabilities. Inbound signals (demo requests, pricing page visits) tip borderline cases toward qualification.
7. Generate composite score and verdict — Produce a 0-100 composite score and assign a routing recommendation.
8. Export structured output — Deliver results in a table or CSV with all qualification data, scores, and routing.

Output Format

Deliver these documents:

1. Scored lead report — Each lead with composite score (0-100), sub-scores by dimension, verdict category, and routing recommendation
2. ICP definition — Firmographic and demographic criteria with priority tiers
3. Scoring model — Complete point-value table for company, person, and use case dimensions with threshold definitions
4. Pipeline routing rules — How each verdict category gets handled

Frameworks & Best Practices

Verdict Categories

Assign every lead to one of these routing buckets based on composite score:

Handling Unknown Data

Score unknown dimensions at 30 points (out of 100 for that dimension). This acknowledges data absence without automatically rejecting leads. A lead missing company size data is not the same as a lead with the wrong company size. Flag unknowns for enrichment rather than penalizing them.

Inbound Intent Premium

Prospects who initiate contact demonstrate genuine interest. For borderline cases (scores 50-74), inbound signals should tip the scoring decision toward qualification. A borderline lead who requested a demo is a better prospect than a slightly-above-threshold lead who has never engaged.

Pipeline Overlap Routing

Before scoring, check for overlaps and route accordingly:

• Existing customer — Route to account management for upsell/expansion conversation
• Active deal in pipeline — Flag for the assigned sales rep to coordinate, do not create a duplicate
• Prior contact with no deal — Note history and score normally, but include context for the sales rep
• Competitor employee — Auto-disqualify and log for competitive intelligence