# Lead Scoring: How to Decide Who to Email First

> A plain explanation of lead scoring for small teams doing outreach, with a worked example, the mistakes to avoid and a simple way to start this week.

Lead scoring is a way of ranking your leads by giving each one points for traits and actions that suggest they are a good fit and likely to buy. The total score tells you who to contact first, who to nurture, and who to drop.

## Why it matters when you do outreach

Your time and your sending capacity are limited. A Gmail account can only send so much per day before you hurt your [email deliverability](https://getclient.pro/learn/email-deliverability), and you can only make so many follow-up calls in an afternoon.

Scoring stops you spending that capacity evenly. Without it, a dentist with no website and a closed listing gets the same attention as a busy practice with a named owner and a direct email. With it, your best-fit leads get your most personal emails and your phone calls, and weaker ones get a lighter touch or nothing.

It also makes you honest about who you actually sell to. Writing down what earns points forces you to define your ideal customer instead of guessing.

## The two kinds of signals

Most scoring models mix two types of points.

### Fit signals

These describe the business itself, before you ever contact it. Think [firmographics](https://getclient.pro/learn/firmographics): category, location, size, whether they have a website, how many reviews they have. For local businesses, a well kept [Google Business Profile](https://getclient.pro/learn/google-business-profile) is a useful clue that someone there cares about getting customers.

Data quality counts too. A lead with a verified email and a named owner is easier to work than one with only a generic contact form.

### Engagement signals

These come from how the lead responds to you: opening an email, clicking a link, replying, visiting your pricing page. They change over time, so the score should too.

## A worked example

Say you run a small web design agency that builds sites for trades businesses. You pull a list of roofers and plumbers in three cities. Here is a simple model. The point values are your own choices, not a standard.

| Signal | Points |
|---|---|
| Category is roofer, plumber or electrician | +10 |
| In a city you already serve | +5 |
| Website exists but looks outdated | +15 |
| No website at all | +5 |
| 20 or more reviews | +10 |
| Owner name found | +10 |
| Email verified as valid | +10 |
| Opened your email | +5 |
| Clicked a link | +15 |
| Replied | +30 |
| Email bounced | -50 |
| Unsubscribed | Remove |

A roofer with an old site, 40 reviews, a named owner and a verified email scores 55 before you send anything. A plumber with no site, three reviews and only an info@ address scores 15.

You might then set simple bands:

- **50 and above:** personalised first email, then a phone call if they open but do not reply.
- **25 to 49:** standard sequence with follow-ups.
- **Below 25:** hold back, or skip entirely.

After the first send, the roofer clicks your portfolio link and climbs to 70. That is your signal to pick up the phone, using something like a [cold call script after email](https://getclient.pro/resources/cold-call-script-after-email).

## Common mistakes

**Too many criteria.** A 30-line model is hard to keep updated and hard to trust. Start with five to eight signals you can actually check.

**Treating opens as strong intent.** Opens are unreliable because some mail apps load images automatically. Give them a small weight and save big points for clicks and replies.

**Never adjusting the weights.** Your first point values are guesses. Look at the leads who became customers and ask what they had in common, then shift the points.

**Scoring bad data.** A high score on an address that bounces is worthless and damages your sender reputation. [Verify emails before a campaign](https://getclient.pro/blog/verify-emails-before-a-campaign) so a dead address cannot outrank a real one.

**Ignoring negative signals.** Bounces, unsubscribes and clear "not interested" replies should lower a score or remove the lead. Anyone who unsubscribes must stop receiving email, full stop. Check the rules that apply where you and your recipients are.

## How to start this week

1. Write down your ideal customer in two or three sentences.
2. Pick five fit signals you can see in your lead data and give each a point value.
3. Add a few engagement signals with bigger points for clicks and replies.
4. Score a small batch by hand in a spreadsheet to see if the ranking feels right.
5. Split leads into bands and treat each band differently.
6. Revisit the points after your first few deals.

In GetClient, a Google Maps search returns the fit signals you need for the first pass, such as category, reviews, website, emails found and the owner's name with a confidence score. You can sort leads into folders by band, as covered in [organize leads in folders](https://getclient.pro/blog/organize-leads-in-folders). See [conditional email branching](https://getclient.pro/learn/conditional-email-branching) for how that works. New accounts include 100 free credits, details on [plans and credits](https://getclient.pro/pricing).

## Frequently asked questions

### Do I need special software for lead scoring?

No. A spreadsheet with a column per signal and a total column works fine for a few hundred leads. Software helps once you have more leads or want engagement data to update automatically.

### What is the difference between lead scoring and lead qualification?

Scoring gives each lead a number so you can rank them. Qualification is the yes or no decision about whether a lead is worth pursuing, and a score threshold is often what you use to make it.

### How many points should a reply be worth?

There is no correct number. Set it high enough that any reply pushes a lead into your top band, because a reply is the clearest sign someone is paying attention, even if it is a question or an objection.

### Should a lead's score ever go down?

Yes. Bounces, unsubscribes and explicit refusals should lower or remove a lead. Some people also let scores decay if there has been no activity for a few weeks, so old interest does not keep a lead at the top forever.

Source: https://getclient.pro/learn/lead-scoring