Illustrative scenario — not a client result.

AI lead qualification: prioritise with evidence

Design a reviewable process for sorting inbound enquiries without inventing buying intent.

The key idea

Use AI to organise information people have actually provided. Qualification criteria should be explicit, relevant to the offer and easy for a reviewer to challenge.

Our method

Start with consented enquiry records. Extract the stated problem, company context and missing information into a fixed format. Route uncertain cases to a person. Keep the original text beside the summary and never treat inferred budget or urgency as fact.

How to assess progress

Check false exclusions, missing facts and reviewer agreement. Measure whether the shortlist improves useful conversations, not merely the number of contacts marked as qualified.

Decision

Decide whether an enquiry needs a sales conversation, a clarifying question or a different destination. Define those routes before designing a score. A contact can fit the offer while providing too little information for a sales handoff; preserve that distinction.

Exercise

Take twenty anonymised enquiries, including short messages, students, existing customers and ambiguous requests. Ask two colleagues to route them independently using stated need and service fit. Give the same records to the proposed workflow, require an exact supporting quotation for each classification and compare disagreements before changing the rules.

Deliverable

Produce a routing sheet with enquiry identifier, stated need, supporting passage, missing information, proposed destination and reviewer decision. Add one neutral clarification question for each incomplete record. Keep an exception queue that an assigned person can review without reading every accepted enquiry again.

Pitfall

Do not reward confident prose or penalise a person for a brief message. If the system treats missing budget as disqualification, measure how many potentially relevant conversations that rule removes. Review excluded records as carefully as shortlisted ones; otherwise the most costly errors remain invisible.

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