Outbound sales have never been harder than it is now—replies are shrinking, sales reps are booking fewer demos, missing quota, and getting overly frustrated since most of them are chasing the wrong leads who won't buy anyway. But this isn't their fault.

In fact, this is due to Sales, Marketing, and GTM leaders not putting the right systems in place.

Creating a system that ensures reps spend their time chasing the right leads requires significant time, effort, and technical expertise.

Luckily, this isn't an issue any more thanks to AI.

In this guide, I'll show you how you can create a system that automatically ranks all leads before your reps even contact them—also called a Lead Scoring system.

Here is the step-by-step process for AI Lead Scoring:

  1. Identify Your Best Customers
  2. Import your leads into Datablist
  3. Tell the AI how to score the Leads

What is Lead Scoring?

Lead scoring is a systematic approach to evaluate and rank prospects based on specific criteria and behaviors.

Systematizing this process helps sales teams prioritize their efforts by identifying which leads are most likely to convert into customers.

By implementing a lead scoring system, sales reps can focus their time on the most qualified prospects, leading to higher conversion rates and improved sales velocity.

Step 1: Identify your Best Customers

  1. Take a look in your CRM and identify the top 10 prospects you ever had.

  2. Analyze what they have in common and write it down. Here are a few factors you should consider:

    • Company characteristics (size, industry, location)
    • Contact details (job title, decision-making authority)
    • Engagement levels with your company
    • Demographic and behavioral data

  3. Create a breakdown of how each factor impacts the ranking.

For that, you should give the highest score to the important factors and the lowest to the nice-to-have but not essential factors.

For example, in most sales processes, the location doesn't have a big impact on the ranking, especially if your company sells a digital product or service, but the industry does play a crucial role.

That's why I would give 3 points for the industry but only 1 for the location.

Note: Adjust scores to match your business model and market.

Step 2: Import your leads into Datablist

First, import a CSV/Excel file in Datablist with a list of the leads you want to score.

Datablist is an AI Co-Pilot for modern GTM Teams.

One of Datablist's key features is its ability to automatically generate data manipulation scripts, making it easy for non-technical users to perform complex data operations.

All you need to do is to tell it what you want to accomplish.

Start by creating a collection and import your list as a CSV or Excel file.

Create a new collection in Datablist
Create a new collection in Datablist

This is my file. It contains:

  • website texts of the companies
  • the company sizes
  • the job position of the prospects
List of prospects with information to score on.
List of prospects with information to score on.

Step 3: Tell the AI how to score the Leads

The final step is to calculate a score for each lead. The old way would be to write a complex Excel formula. The problem with formulas is that they quickly become hard to read.

Hopefully, with AI, you won't need to write formulas anymore. You just write the score criteria, and the AI will automatically generate a script that calculates the score.

Follow these instructions to get the most accurate results:

  1. Go in the Nav-Bar, click on “Edit”

  2. Select “AI Editing”

    Open AI Editing with Edit -> AI Editing
    Open AI Editing with Edit -> AI Editing

  3. Then, write your prompt. Best Practices for prompt writing:

    • Be specific about the outcomes you want to have.
    • Use clear bullet points and commas to structure your prompts in a logical way.
    • Use variables from your collection by typing 2 brackets ({{PropertyName}} or slash /PropertyName) and selecting the property you want to use.
Prompt for Lead Scoring with AI.
Prompt for Lead Scoring with AI.

Here is my prompt for Lead Scoring with AI.

Add a column called "Persona Match?" and enter "2" for rows where the position contains any of "CEO & Founder", "Co-Founder and CEO", or "Founder and CEO" and "1" for rows with just "CEO" or "COO. 

Create then a second column called "Account Match" that shows "1" for any row where company_size falls between 15 and 100. 

Create also a third column called "Product Match?" and Add a "1" for each row where Website Texts contains one of the following terms: AI, Artificial Intelligence, KI. 

Note for Product match: it has to be the exact term, not just a part of the word. 

Finally, create a fourth column that summarizes the figures contained in the three new columns and name it "Lead Score". 

Use {{position}}, {{Website Texts}} and {{company_size}} as reference, acting based on similarities rather than specifics

Note: Replace the {{xxx}} at the end with your collection properties (use {{ or / to pick a property).

  1. Click on generate

The AI will then generate a script for you and give you a preview of the results that you're going to get. From this preview, you can improve the prompt to add more criteria if needed.

Generated preview of the lead scoring system generated by the AI
Generated preview of the lead scoring system generated by the AI

Step 4: Get Your Results

Click on "Run on items" to get your results.

Scoring Results
Scoring Results

You can send the results back to your CRM or sequencer by using one of Datablist's native integrations or the Call API/HTTP enrichment.

The script is saved, so you can access it any time from the Edit -> AI Editing" menu to run it on new leads.