# Build a lead scoring model my sales team will trust

A fit-plus-intent lead scoring model with thresholds, decay, and a validation plan tied to actual closed-won outcomes.

- Topic: Sales
- Framework: Few-Shot
- Level: Standard
- Tags: Sales, Fill-in Template
- Source: https://www.thinkwithprompt.com/prompts/build-a-lead-scoring-model-my-sales-team-will-trust

## Prompt

```text
Help me design a lead scoring model.

**Our ideal customer profile:** [industries, company size, roles, regions, tech used]
**Behavioral signals we capture:** [e.g. pricing page visits, demo request, webinar attendance, product sign-up and usage, email clicks]
**Historical data available:** [e.g. which leads converted to opportunities and closed-won, if any]
**Current definition of an MQL or SQL:** [paste, or "none"]
**Sales feedback on lead quality:** [what reps complain about]
**Tools:** [marketing automation, CRM]

Build the model in two parts:
1. Fit score (who they are): firmographic and role attributes, with points and negative scores for poor fit (students, competitors, wrong region, personal email).
2. Intent score (what they do): behaviors weighted by buying intent, with time decay so old activity fades. High-intent actions such as demo requests should route straight to sales regardless of score.

Then:
- Set thresholds for MQL and for sales-ready, and explain how to pick them using historical conversion rates.
- Show 3 example leads scored end to end.
- Describe how to validate the model: compare conversion rates by score band after 60-90 days, and adjust.
- List how sales should give structured feedback on leads (accept, reject with reason).

Return:
- A scoring table: Attribute or behavior | Points | Reason.
- Thresholds and routing actions.
- A validation and review plan.

Don't claim point values are proven; label them as starting assumptions to test.
```

## What to fill in

- industries, company size, roles, regions, tech used
- paste, or "none"
- what reps complain about
- marketing automation, CRM

Free to copy and use. From ThinkWithPrompt (https://www.thinkwithprompt.com/), a library of 2,663 curated AI prompts.