Intelligent Business Automations

Book A Free Consultation
Menu

Lead Scoring with AI: A Practical SMB Guide

  • What lead scoring is (in normal terms)
  • Where AI fits in (and where it doesn’t)
  • A simple, step-by-step AI build using free/low-cost tools
  • How to define your own scoring rules (without needing a data team)
  • How to QA and monitor your AI model
  • Easy metrics to track what’s working—and what’s not

Introduction: Making Smarter Sales Calls (Without Guesswork)

You’re generating leads—good start. But not every lead is made equal. Some are close to purchasing, while others are just kicking tires.

Lead scoring helps you focus on the right prospects, and using AI to do that means quicker insights based on real behavior—not guesswork or rigid rulesets.

Good news: You don’t need to be a data scientist or pay for expensive software. This guide will walk you through a lightweight, tool-neutral approach that works with what you’ve already got.

What Is Lead Scoring, and Why Does It Matter?

At its core, lead scoring is assigning a value—often a number—based on how likely a lead is to convert. Think of it as a readiness score.

For example: If you receive 15 form submissions, which 5 should your salesperson call first? With lead scoring, you can automate that decision based on patterns from past successful leads.

The Traditional Approach

  • Manual: You define rules like “downloaded a whitepaper + opened 2 emails = hot lead.”
  • Intuition: Sales reps use gut instinct to prioritize follow-up.

Why AI Is Better

  • Reviews more behavior signals across channels
  • Adjusts based on historical lead-outcome data
  • Provides consistent results without human bias

What AI Really Does in Lead Scoring (And What It Doesn’t)

AI doesn’t invent demand—it recognizes patterns from your data. To teach it, you need:

  • A list of past leads labeled by whether they became customers
  • Clear attributes for each: source, CTA clicks, job role, etc.

Once trained, AI can predict which new leads are likely to buy soon.

But remember: AI assists; it doesn’t replace your overall sales strategy or good follow-up.

Want to see how AI fits into your sales and marketing mix? Visit our AI in Marketing & Sales Hub.

How to build this in Make.com

Here’s a practical way to create an AI-powered lead scoring system using Make.com. No coding needed.

  1. Collect Lead Data

    • Use existing tools like web forms, CRM, email platform
    • Capture relevant fields: page visits, form fill date, source, industry
    • Make.com Module: Webhook trigger or connection to your CRM (e.g., Airtable, Pipedrive, etc.)
  2. Prep Training Data

    • Export 100+ past leads labeled as “won” or “lost”
    • Ensure formatting is consistent (dates, job titles, source fields)
    • Make.com Module: Iterator + Array Aggregator if needed
  3. Use AI to Predict Lead Score

    • Call OpenAI (GPT) or Claude using HTTP Module
    • Prompt style: “Here’s past data. Given [this lead’s] profile, how likely are they to convert in 30 days (score 1–100)?”
    • Make.com Module: HTTP + Text parser (JSON or Text functions)
  4. Output Score to CRM or Google Sheet

    • Update the lead’s record with the score (e.g., “Score: 88”)
    • Make.com Module: Google Sheets – Update Row or CRM – Update Record
  5. Trigger Actions Automatically

    • If score >80: Assign to rep, or send personalized follow-up
    • If score <50: Enter nurture campaign
    • Make.com Router: Route based on numeric score threshold

Need help building a Make.com flow? Our Coaching plans walk you through this step by step.

QA & Guardrails

AI is only as good as the feedback it gets. Don’t let your system operate without oversight.

  • Bias checks: Is your training data skewed toward a certain industry or sales style?
  • Sales strategy changes: Update your scoring logic if your offer or ICP evolves.
  • Manual override: Enable your reps to add notes like “High potential despite low score”
  • Validation: Keep 20% of your lead data separate for testing. Are high scores actually converting?

Metrics & ROI

Here’s how to know your AI lead scoring is moving the needle.

Key Indicators

  • Higher conversion rates among high-scored leads
  • Shorter time from lead-to-close
  • Faster follow-up for hot leads
  • More revenue with fewer leads (aka improved lead quality)

Easy Tools for Tracking

  • Use your CRM’s built-in lead status and reporting
  • Google Sheets + timestamps to visualize lead aging vs. conversion
  • Make.com run logs for volume and action history

Common Questions and Quick Fixes (QA)

What if I don’t have enough past lead data?

Start with manual scoring tied to actions (e.g., click, download, etc.). Once you have 100 labeled leads, you can introduce AI.

Can I trust AI predictions?

Mostly, yes—but treat them as directional. Always test against real-world results.

I don’t want to use Make.com. What are alternatives?

Zapier, Pabbly, N8N, and Google Apps Scripts can all apply the same logic—use what fits your stack and comfort level.

Explore AI-friendly CRMs and automation platforms in our business solutions guide.

Final Thoughts: Keep It Simple—and Actionable

AI-powered lead scoring isn’t about technology for technology’s sake. It’s about helping your sales team spend less time chasing leads—and more time closing them.

You don’t need to be a tech wizard. Start small. Score leads. Watch outcomes. Improve over time.

Next steps:

Optional Download: Free Template – Sample Lead Scoring Setup for Make.com (PDF/Airtable)