Lead scoring for small businesses: the three-question version

Lead scoring for a small service business is not a model. It is three questions: is this lead ready to buy soon, is the job worth a person's time, and can you actually do it? Answer them from the first conversation, mark the lead hot, warm or cold, and let that decide who gets a human call this morning. Anything more elaborate is time spent on scoring instead of on leads.

Why enterprise scoring does not fit

Enterprise lead scoring assigns points for job title, company size, pages visited and emails opened, then trains a model on which leads closed. It works with thousands of leads and a sales team to route them to. A dental office gets a few dozen leads a month and one front desk. The question is not "which of these 3,000 should we prioritise" but "which of these six do I call before 10am".

The three questions

Timing: are they ready? "I need this done this week" is hot. "Thinking about it for next year" is cold. Most leads say this in their first message, and a qualifying question catches the rest.

Value: is it worth a person's time? A full-mouth restoration, a new HVAC system, a kitchen remodel, a family law matter: hot, and worth a call. A single cleaning, a filter change, a trim: warm, and the AI can book it without anyone's time.

Fit: can you do it? In your service area, a service you offer, a patient you can see, an insurance you take. If not, cold, however keen they are, and the kind thing is to say so quickly.

Hot, warm, cold

Hot: ready, valuable, and a fit. A person calls this morning, at a time agreed by text.

Warm: ready and a fit, but routine. The AI books it; nobody needs to call.

Cold: not ready, not a fit, or not worth a call. The AI captures the details, sends anything useful, and the lead sits in the record for when things change. No sequence, no calls.

The point of the labels is a morning list: hot leads at the top, with the conversation and the answers to the three questions already there.

Where the answers come from

The first conversation. The AI asks the qualifying questions for your industry and records the answers on the lead. Timing and fit are usually explicit; value comes from the service they named and your price list. No behavioural tracking, no email opens, no scores that nobody can explain.

Keeping it honest

Review the hot list weekly. If half the "hot" leads were not, tighten the definition. If a warm lead turned into a large job, look at what the first conversation missed. The labels should change as you learn, and a lead's label should change as the conversation does.

The one enterprise idea worth borrowing

Speed. Enterprise teams learned that a hot lead reached in five minutes is a different lead from one reached in an hour. That applies with more force to a homeowner with a leak. Score fast, and act on hot within the hour.

Frequently asked questions

Should the AI assign the score?

It can propose hot, warm or cold from the answers, and a person confirms in the first weeks. Once the rules are settled, let it label and review weekly.

What about leads from paid ads?

Same three questions. The source is worth recording so you know which ads bring hot leads, but the source is not the score.

Do cold leads ever get followed up?

Not by sequence. If they gave a reason ("next spring"), a single message when spring comes, from a person, is reasonable.

What Frontiva does here

Frontiva's lead management scores every lead from three signals (source, service value and urgency) and always shows the breakdown, can auto-assign to the teammate with the fewest open leads, and keeps follow-up tasks with an overdue view. AI qualification is on the roadmap. Analytics show which sources produce leads and customers. See qualifying questions by industry.