The lead scoring scorecard for small sales teams

By , Founder of LeadScore AI and SnapSuite

At SnapSuite we've sold software to contractors and service businesses for years. LeadScore AI is built around one question: which leads deserve your next call?

This scorecard is the short version of what LeadScore AI checks. It's 10 questions about how your team decides who to call next. Answer each one Yes, Partly or No. Your answers stay in your browser, and we don't store them.

The 10 questions

  1. 1.Can you describe your ideal customer in two or three sentences, based on your last ten good deals?

    Why it counts: deals you already won show a real pattern. A persona you wish you had doesn't.

  2. 2.Do you have a written list of who you won't sell to?

    Why it counts: wrong region, wrong size, industries you can't serve, competitors. Cutting those first saves the most rep time.

  3. 3.Do you check that a lead's email and phone number are valid before anyone reaches out?

    Why it counts: a great-fit lead with a dead number is a wasted call.

  4. 4.Do you judge fit (who they are) separately from intent (what they've done lately)?

    Why it counts: a perfect-fit company that went quiet and an average fit that replied yesterday need different next steps.

  5. 5.Do recent signals count more than old ones?

    Why it counts: a reply from last week tells you more than one from last quarter.

  6. 6.Does each rep start the day from a ranked list, instead of scrolling the whole spreadsheet?

    Why it counts: if picking the next lead takes ten minutes, that's ten minutes off the phone.

  7. 7.Could a rep explain, out loud and in one sentence, why the top lead on their list is at the top?

    Why it counts: reps stop using a score they can't explain.

  8. 8.When a rep disagrees with the ranking, can they override it and write down why?

    Why it counts: your rep often knows something the data doesn't, and that note is worth keeping.

  9. 9.When a lead unsubscribes or asks not to be contacted, do your sequences and automated emails to them stop, however good the lead looks?

    Why it counts: a high score should never beat consent.

  10. 10.Do you record outcomes (won, lost, wrong fit) and use them to review your rules?

    Why it counts: without outcomes you can't tell whether your scoring helps. With them, you can check.

Add up your score

Give yourself 2 for every Yes, 1 for every Partly and 0 for every No. The total is out of 20.

What your score means

  • 0 to 7Gut feel

    Who gets called next depends on memory, mood and whoever replied last. Start with questions 1 and 2. Write down your ideal customer and your no-go list this week, and you can sort any list into call, maybe and skip.

  • 8 to 13Rules on paper

    You know who you want, but the list doesn't change when leads reply, go quiet or get stale. Look at questions 3 to 6. Check contact details before outreach, split fit from timing, and let old signals count for less.

  • 14 to 17Working system

    Your team works from a ranked list it mostly trusts. The gaps usually sit in questions 7, 8 and 10: scores your reps can't explain, overrides that live in someone's head, and outcomes that don't make it back into the rules.

  • 18 to 20Tuned

    Keep recording outcomes and review your rules on a schedule. Don't chase a perfect model. A rough one that ranks your whole list today beats a perfect one that ships next quarter.

What to fix first

Go down the list and find your first No. The questions run in the order I'd fix things, so that's usually the place to start.

One exception: if you answered No to question 9, fix that before anything else, whatever your total.

Where LeadScore AI fits

If you'd rather not run this in a spreadsheet, this is the part LeadScore AI handles. It grades each lead against the ideal customer profile you set up, from A to D, and puts it in an intent band: hot, warm, cold or dormant. It writes down the reasons behind every score and gives a verdict of pursue, nurture or disqualify. Old signals cool off on their own. Reps can override a score with a reason. An unsubscribe, a complaint, a suppression-list match or a do-not-contact flag stops automated outreach to that lead, no matter the score. You can record won, lost and disqualified outcomes against the score and use them when you review your rules.

We don't promise a better close rate from a score. Start with a sample of your own leads, read the reasons, and decide if the ranked list beats what you have now. Self-service plans come with a 7-day trial.

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About this scorecard

The questions follow what LeadScore AI looks at when it scores a lead: fit, contactability, engagement and timing, plus overrides, do-not-contact and outcome review. The score bands are a self-check we wrote, not an industry benchmark.

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