> For the complete documentation index, see [llms.txt](https://docs.limecall.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.limecall.com/ai-receptionist/lead-qualification.md).

# Lead qualification

Teach the assistant what a good lead looks like and how to grade it.

Open **AI Receptionist → Lead Qualification**.

Qualification is what makes the assistant more than an answering machine. It decides which calls deserve your attention.

## What counts as a good lead

Describe your ideal customer in plain language. Be concrete — "a good lead" means nothing; the specifics mean everything:

> A good lead is a homeowner, not a tenant, within 20 miles of Leeds, with a job worth over £2,000, who wants work done within three months and is the person who makes the decision.

That gives the assistant five things to establish, and a clear basis for grading.

## Qualifying questions

The questions it asks to work this out. Templates give you a starting set for your industry — a home services assistant asks how urgent the job is; a B2B assistant asks about team size and whether the caller is the decision maker.

Typical dimensions:

* **Authority** — are they the decision maker?
* **Need** — what is the actual problem?
* **Timing** — how urgent is it?
* **Budget** — can they afford it?
* **Fit** — are they the kind of customer you serve?

Ask three or four, not all of them. A caller subjected to a full interview hangs up.

## Asking without interrogating

Set the questions to be woven into the conversation rather than fired in sequence. A caller should feel they had a conversation, not filled in a form out loud.

The assistant can also infer answers it was not told directly — if a caller mentions "our office manager will need to approve it", authority is established without asking.

## Lead score

The assistant assigns a score from your criteria. Scores appear on the lead in **Leads** and can be filtered and sorted.

Use the score to triage, not to discard. A low score means "do not interrupt someone for this", not "this is worthless".

## Not qualified

Decide what happens to callers who do not qualify. They should still be handled courteously — a tenant who cannot buy today may be a homeowner in two years, and rudeness to them shows up in reviews.

Usually the right behaviour is to answer their question helpfully, take the details, and simply not flag it for follow-up.

## Where it goes

Qualification data lands on the lead record: the score, the answers to each question, and the assistant's reasoning.

Your team sees this before they call back, so the first human conversation starts from what is already known instead of repeating the same questions. See [Leads & scoring](/inbox-and-leads/leads-and-scoring.md).

## Tuning it

Review the scores against what actually converted, after a few weeks. If high-scoring leads are not closing, your criteria describe the customer you want rather than the customer you win — adjust them to match reality.