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As of 13 August 2026, AI can prioritise your best leads.
Most people should hand this to a purpose-built tool.
Can you do it?
15 minutesto a draft.
30 minutesto something you’d act on.
Cost, all in£0
Skill neededchat-fluent
Who has to check ityou
What the alternative costsA sales colleague or CRM specialist can prioritise the list manually; no comparable price is supplied here.
If this goes wrong: your team spends time on weak leads while a promising lead receives no timely attention.
What to actually do
Use a tool built for this
The route this page recommends
Do it yourself
Second choiceA chat interface, chat-fluent skill, and roughly 30 minutes until you can act on the result.
How to actually do it
- Open your CRM or spreadsheet and export the current lead list with each lead's company, role, sector, location, account status, source, recent activity and any stated need.
- Write down your ideal customer profile, including target sectors, company size, decision-maker roles, UK regions served, disqualifiers and the problem your offer solves.
- Add your sales rules, such as existing-customer exclusions, territory limits, minimum deal requirements, recent contact limits and any signals that justify urgent follow-up.
- Remove unnecessary personal data from the export, then paste the ICP, sales rules and lead table into the prompt.
- Ask the model to produce the ranked table, evidence, unknowns and recommended next action without filling gaps with guesses.
- Compare every top-ranked lead's score and evidence with the original CRM record and your actual eligibility rules, correcting any unsupported or outdated entry.
- Check the top leads in your CRM for duplicate ownership, recent contact, opt-outs and current account status, then send only the approved next actions through your normal sales process.
Prompt
Prioritise the leads in the data below for sales follow-up. Use only the information provided and do not invent missing facts. First extract the criteria from the ideal customer profile and sales rules, then score each lead against those criteria. Separate confirmed facts from assumptions and mark missing information as unknown. Produce: 1) a ranked table with lead name or ID, score, evidence, risks, missing information and recommended next action; 2) a short explanation of the scoring method; 3) a separate list of leads that should not be deprioritised solely because data is missing; and 4) three checks I should complete before contacting the top leads. Do not infer personal characteristics or sensitive information. Do not claim that a lead will convert. If the criteria conflict, show the conflict instead of resolving it silently. Ideal customer profile: [paste ICP]. Sales rules and exclusions: [paste rules]. Available lead data: [paste CRM export or table].
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
Hand it to a person
The distant thirdA person who owns the outcome does this end to end, worth it when the failure is dear.
What it gets wrong
- It cannot know whether a buying signal is genuine unless that evidence is present and current in the supplied data.
- It cannot replace your judgement about strategic accounts, relationships, timing or unwritten commercial priorities.
- It cannot verify that a company, contact or job change is still current without an appropriate live data source.
- It cannot predict conversion reliably from a tidy score, so the ranking remains a decision aid rather than a sales forecast.
Even on a YES, the friction has a name: judgement under ambiguity, context depth and stakes of error.
How we scored this
Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.
| Axis | Score (0–2) |
|---|---|
| Output | 2 |
| Inputs | 2 |
| Verification | 1 |
| Liability | 1 |
| Effort delta | 2 |
| Total | 8 / 10 |
The methodology and its thresholds are published in full.
FAQ
- Can AI score and rank my sales leads?
- Yes. Give it your lead data, ideal customer profile and sales rules, and it can produce a ranked list with reasons and missing information. Check the evidence against your CRM before acting on it.
- What data does AI need to prioritise leads?
- It needs the fields that affect your decision, such as company type, role, location, account status, recent activity, stated need and source. It also needs your exclusions and a clear definition of a good-fit customer.
- Can AI tell me which lead will convert?
- No. It can identify leads that match the supplied criteria and signals, but it cannot establish that a lead will buy. Treat the result as an order for research and follow-up, not as a forecast.
- Is it safe to let AI prioritise my leads?
- It is suitable for an initial ranking when you minimise personal data and keep a person responsible for the decision. Do not upload information you are not authorised to share, and check for stale records, duplicate ownership and opt-outs before contacting anyone.
Nearby answers
Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.
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