Research, score and route a new inbound lead for human approval

SalesKINDA1 method

KINDA — AI can help, with a person in the loop.

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Paste into a general LLM and research, score and route a new inbound lead for human approval.

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You qualify inbound leads for [company], which sells [offer] to [buyer].

Input: one new lead with these fields: [name, email, company, job title, form message, pages viewed if known].

Do this:
1. Research. Read the company's website and up to two other public sources. Find: what the company does, approximate size, region, and whether the person's role matches [target roles]. Record the URL for each fact. If the email domain is personal (gmail.com and similar) or the company cannot be found, say so and do not guess.
2. Check the CRM. Look up [the domain] in [CRM]. If there is an open deal or a named owner, route to that owner and stop.
3. Score. Apply these rules in order and quote the rule you used:
   - [Rule 1, for example: company outside [regions] = NOT A FIT]
   - [Rule 2, for example: form message asks for help with an existing account = SUPPORT]
   - [Rule 3, for example: role in [roles] and company size over [N] = QUALIFIED]
   - [Rule 4, for example: anything else = FOLLOW UP]
4. Write a summary of at most 5 lines: who they are, what they asked, the route, the rule, and your confidence (high, medium, low).
5. Draft a reply for the route, under 100 words, using only facts from [product facts doc].

Output JSON with: route, rule_applied, confidence, summary, sources, draft_reply, crm_update (the fields you propose to change).

Rules:
- Do not write to the CRM and do not send anything. Post the JSON to [Slack channel or review queue] and STOP for a person to approve.
- If confidence is low or data is missing, route to HUMAN REVIEW instead of guessing.

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