Announcing $1.1M Pre-Seed Round
Helping marketing managers scale their sales pipelines with AI
Service
AI Agents
Lead qualification image ilustration
Lead Qualification
Evaluates leads, connects to sales.
Retargeting image ilustration
Lifecycle
NEW
An agent to proactively manage leads through your funnel.
Industries
Automotive
Education
Finance
Healthcare
Insurance
Real Estate
Retail
SaaS
Telcos
Travel & Tourism
Case StudiesPricing
Resources
Blog
AI insights for Marketing and Sales
ROI Calculator
NEW
Calculate your ROI with AI-driven lead qualification.
English
English
Spanish
Portuguese
Login
Let’s Talk
Blog
Data

What Is a Lead Qualification Matrix and Why Use It?

Mariano Rey
By
Mariano Rey
June 6, 2025
6
minute read
Share this post
Copied to clipboard
lead-qualification-matrix-abstract-image

Generating leads is only half the battle. To truly maximize your investment, it’s important to understand which leads have the highest potential as quickly as possible so that your salespeople have a high chance of success.

In today’s article, we’ll discuss what a qualification matrix is, how it can help you prioritize leads, focus your Sales team’s efforts, and inform your Marketing team about the quality of the leads they are generating.

What is a Lead Qualification Matrix?

It’s a simple yet powerful tool that allows you to prioritize and manage leads more efficiently. It consists of variables that carry specific weights and help define a score, typically ranging from 0 to 1 (or 0 to 100).

This score will help you identify which prospects have the highest potential—those that the Sales team should focus on and the Marketing team should continue generating in the future.

How to Create a Qualification Matrix?

Let’s explain it with an example:

Patagon Motors sells affordable cars (both used and new). When qualifying a customer, they know certain variables are important:

  1. Type of vehicle: Whether the user is looking for a new or used car.
  2. Budget: They expect a minimum budget of USD 5,000.
  3. Urgency: They want to know the urgency of the purchase to decide whom to put extra effort into bringing to the dealership for a test drive.
  4. Financing: Whether the user requires financing or already has the money to make a purchase.

With this in mind, they defined specific weights for the answers within each variable:

  1. Type of vehicle (25% of the total): If the user is looking for a new car, the value will be 25 (or 0.25). If they are looking for a used car, it will be 75% of the variable’s value, that is, 25 x 0.75 (or 0.25 x 0.75). They decided on this because, in their case, the profitability of a new car is higher than that of a used one.
  2. Budget (35% of the total): A minimum budget of USD 5,000 is required (since it’s the price of their cheapest car). If the user has that amount, they will be assigned 75% of the variable’s value, that is, 35 x 0.75 (or 0.35 x 0.75). If the user has more than USD 5,000, they will be assigned the full value, i.e., 35 (or 0.35). If the user has less than USD 5,000, the variable will not score any points.
  3. Urgency (25% of the total): If the person wants to buy within the next 30 days, they are given the full value of the variable, i.e., 25 (or 0.25). If they want to buy within 30 to 90 days, they are given 75% of the value, i.e., 25 x 0.75 (or 0.25 x 0.75). If the user has no urgency, the variable will not score any points.
  4. Financing (15% of the total): If the potential customer does not require financing, they will be assigned the full value of the variable. If they do require financing, they will be assigned 75% of the value of the variable, i.e., 15 x 0.75 (or 0.15 x 0.75). They decided this because financing often slows down the sale and can make the process more cumbersome.

With each specific weight defined, they set the threshold above which salespeople should prioritize customers: a score equal to or greater than 65.

So, let’s suppose a customer arrives who wants a new car, has USD 5,000 to buy, wants to do so within the next 30 to 90 days, and requires financing. Based on the previous matrix, it would look like this:

  1. Type of vehicle: New. So, 25 points (or 0.25).
  2. Budget: USD 5,000. That would be 26.25 points. This is because it’s 35 (total variable weight) x 0.75 (weight of the customer’s response).
  3. Urgency: Within 30 to 90 days. Here it’s 18.75 points. That would be 25 (total variable weight) x 0.75 (weight of the customer’s response).
  4. Financing: Yes. Points: 11.25. The user chose that they need financing, so it’s 15 (total variable weight) x 0.75 (weight of the customer’s response).
  5. Final score: 25 (or 0.25) + 26.25 (or 0.2625) + 18.75 (or 0.1875) + 11.25 (or 0.1125) = 81.25 (or 0.8125).

In this case, the customer will be prioritized by the sales team since their score is above the defined threshold. The Marketing team will also signal the algorithms of the various advertising tools they use to bring in more users like that and optimize other strategies to attract more users of that type.

How to Think About a Qualification Matrix?

Although the example makes it seem “easy” to understand how a qualification matrix works, some questions or doubts may arise when putting it into practice. For example: How do you define the variables? How do you assign specific weights? How many variables should you include?

To create something like this, it’s important to consider:

  • Who is the ideal customer? If we had to describe in our own words who the ideal customer is, what traits do they have? This is important for thinking about the variables and optimizing Marketing strategies. Reaching a definition may require talking to valuable customers, the Sales team, or others who interact with customers.
  • What variables are important? That is, what should we ask the customer to understand if they have potential or not? In the case of our example, they asked about the type of vehicle because new cars had greater profitability potential.
  • Are there variables beyond the customer’s characteristics that could be included? Yes, of course. For example, interaction with the website, type of interaction with the website, credit score, etc. Any variable that can help better understand the customer’s potential, and that is beyond their personal characteristics or what we can ask them, can also be added.
  • What weight should be assigned to each variable? There is no magic formula for this, but it’s important to understand the importance of each variable within the suite of available variables. For example, if you work in a B2B SaaS company that sells/charges per user, the company size variable or the team size that will use the tool may take on greater importance.
  • Where is the score threshold set? Again, there is no 100% established formula. The cut-off should be made when the potential customer meets the minimum requirements that justify the time and investment of a salesperson. Of course, this depends on each business.
  • What do you do with those below the minimum threshold? Of course, you shouldn’t discard them. Instead, understand what type of users they are and what experience is best. Perhaps it’s worth having a salesperson take over, perhaps they can be provided with information because they are not yet ready to buy, or perhaps they are not a target and not worth following up on. Again, this will depend on the characteristics and dynamics of each business.

With this answered, you can start drafting your first matrix. It’s worth noting that this is not something that remains fixed but evolves over time (depending on how your product/service, positioning, etc. evolves).

In Conclusion

A qualification matrix is a tool that can greatly help focus the efforts of Sales teams and provide better insights to Marketing teams. The former makes more efficient use of their time, meeting only with the highest quality leads. The latter better understands the type of traffic they are buying or generating with their acquisition strategies.

To create something like this, it’s important to have visibility into who the ideal customer is, which variables are most important when qualifying, the weight of each variable, and how to interpret and act on the score.

‍

Table of contents

Heading 2
Heading 3
Heading 4
Heading 5
Heading 6

Subscribe to our Newsletter

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Blog

Our latest news

Stay updated with our latest blog posts.

See All
Sales

The Real Cost of Slow Response: How Minutes Impact Your Bottom Line

Slow responses hurt conversions, every minute counts. Leads contacted within 5 mins convert 100x better. Combine AI for instant replies and humans for empathy to maximize sales and customer trust.

Mariano Rey
By
Mariano Rey
June 6, 2025
3
minute read
AI

Why We're Ditching Our Website Form and Going All-In on WhatsApp

AI transforms marketing automation into personalized customer engagement through WhatsApp. Discover how ditching website forms for AI agents has improved our conversion rates and why leading companies are adopting this approach for better results.

Mariano Rey
By
Mariano Rey
June 6, 2025
3
minute read
Marketing

The Untapped Potential of AI-Driven Lifecycle Marketing

AI turns basic marketing automation into intelligent customer engagement. Data shows dramatic improvements in sales and ROI. Learn how new AI algorithms create unique experiences for each customer.

Mariano Rey
By
Mariano Rey
June 6, 2025
3
minute read

Ebook

2025 Automotive Marketing Report

Discover how to boost demand and conversions using AI, WhatsApp, and real dealership data from across Latin America.

Get the Report
ServiceAgentsAbout usCase StudiesPricingBlog
Let’s Talk

Industries

SaaS
Insurance
Finance
Travel & Tourism
Telcos
Retail
Education
Healthcare
Real Estate
Automotive
Subscribe to our newsletter
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
© 2025 PatagonAI. All rights reserved.
Privacy PolicyTerms of Service