Marketing Qualified Leads (MQL) vs Sales Qualified Leads (SQL)

Not every business has a process in place to evaluate and differentiate between leads. For those that do, understanding the difference between a marketing qualified lead (MQL) and a sales qualified lead (SQL) will help you differentiate between someone who’s interested in your content and someone who has intent to buy. 

Not having clear distinctions between MQLs and SQLs can have a detrimental impact on the bottom line. For example, sales might consistently receive low-quality leads that waste reps’ time or hot leads may not get handed off immediately, resulting in lost business to more attentive competitors. 

Of course, sending all leads directly to sales to qualify for themselves isn’t always practical — in fact, it’s often a huge waste of resources. 

That’s why it’s important to understand the difference between MQLs and SQLs and the roles they play in your funnel.

MQL vs SQL Definitions

The exact definition and terminology for MQLs and SQLs will be different for every organization. But here are generally accepted definitions: 
 

Sales qualified lead: A lead that has been qualified, vetted, and expressed intent to engage in a sales cycle. 

Criteria for each will vary depending on your business and your unique customer journey. But there’s usually a key distinction between the two — their readiness to buy. 

Why Differentiate  Between MQLs and SQLs?

Understanding the difference between MQLs and SQLs is important for managing your business’ resources effectively.  

Consider this: Marketing qualified leads don’t require direct, one-on-one attention from a sales rep. Instead, they’re nurtured through self-service (via your website) or efforts by the marketing department such as email marketing campaigns, webinars, etc.  

Involving sales too early in that nurturing process isn’t the best use of your organization’s resources. Their expertise would be better reserved for SQLs, leads that have a stronger possibility of converting. 

Businesses with closely aligned marketing and sales teams understand the difference between MQLs and SQLs and devote resources accordingly. It’s part of why they’re 67% more efficient at closing deals.

How They Work Together in the Sales Process

When there’s consensus for what constitutes an MQL vs. SQL, leads follow a more natural progression through the sales funnel. They aren’t rushed through the process — instead, they are nurtured through education and qualification until they reach the agreed-upon criteria for the handoff to sales. 

Having a process in place allows marketing and sales to leverage what each respectively does best — nurturing and closing.  

How to Identify MQLs and SQLs

This process begins with establishing criteria for MQLs and SQLs for your business. Yours will be influenced by factors specific to how your company engages with potential buyers. 

Here are some common MQL and SQL interactions to consider as you develop your own:

Marketing qualified leads (MQL) demonstrate an interest in learning about your solution through actions such as: 

• Provides basic contact information
• Downloads gated content
• Attends a webinar 
• Subscribes to your email newsletter

Sales qualified leads (SQL) demonstrate an intent to purchase a solution through actions such as: 

• Downloads trial software
• Requests a demo
• Visits your pricing page 
• Asks to be contacted by sales

It’s important to point out that SQL behaviors are indicative of someone in an active buying cycle. 

The earlier you establish a relationship with someone in that stage, the better your chance of positioning your solution as the best possible choice. 

In fact, 78% of buyers select the first vendor to respond to a high intent action taken, according to Salesforce.

How Does an MQL Become an SQL?

Sometimes the transition from MQL to SQL is seamless and straightforward, like when a marketing qualified lead requests to speak with a sales rep. 

However, the shift from an MQL to an SQL is often more subtle, occurring over time through numerous interactions with your business. 

That’s why it can be challenging to pinpoint the right time for handoff. 

Still, timing is everything.  If you involve sales too early you risk getting flak for wasting their time. Involve sales too late and risk becoming a footnote in the prospect’s research because you failed to respond quickly enough.  

As a result, most B2B companies incorporate other elements to determine when an MQL becomes an SQL. 

Here’s what that may involve:

Lead Firmographics

Comparing a new lead’s firmographics to your current install base those that completed the customer journey is another way to distinguish between MQLs and SQLs. 

In other words, consider whether a lead fits your ideal customer profile (ICP) before you decide on the resources you’ll invest.

Here are some firmographics that may be important to consider when evaluating a lead: 

• Industry
• Whether the company is public or privately held
• Company revenue
• Number of employees
• Percentage of remote workers
• Lead’s organizational role
• Technology stack details
• Lead source

Lead Behavior

Evaluating a lead's behavior on your website can reveal whether a lead is an MQL or an SQL. 

Here are some things to consider when determining a lead’s level of interest.  

• Number of visits — first time or repeat
• Types of conversions — downloading a guide vs requesting a demo 
• Pages viewed — careers or blog vs pricing 

Lead Scoring

Lead scoring is the process of assigning a weighted value to a lead based on specific actions they take on your website. A lead scoring strategy may also consider how they’ve engaged with your brand on third-party sites, such as G2 Crowd or Capterra. 

Here are some example actions with associated values: 

• Downloaded a technical white paper, +5 points
• Visited the pricing page, +10 points
• Clicked on a paid ad to find your website, +5 points
• Accessed the knowledge base (for customers), -5 points
• Visited the “We’re Hiring” page — and little else, -10 points

Assigning negative values to interactions that don’t reflect a genuine interest in your solutions is essential for gaining an accurate picture of a visitor’s intent. The aim is that the overall score will reflect a lead’s value, allowing you to prioritize resources and develop the sales strategy going forward.

Lead Qualification Criteria

An MQL that meets BANT criteria would qualify for the SQL distinction and handoff to sales in most organizations. 

BANT is a sales qualification process that indicates a lead’s likelihood to purchase by demonstrating:

• Budget: The price of your solution is within their budget
• Authority: Decision-making ability or an influencer role
• Need: A pain that your solution could address
• Time: A sense of urgency or targeted date to purchase

 Sales should engage with leads that meet BANT or other lead qualification criteria immediately. 

The Bottom Line 

B2B companies expend a lot of resources trying to attract leads to their sites. 

Implementing criteria for what qualifies as an SQL vs MQL will help you to figure out which leads are ready to be handed off to sales and which ones are merely in education mode. 

Not only is handing off unqualified leads to sales a waste of resources, it can also be a really frustrating experience for a potential buyer. 

Now that you’re armed with a baseline understanding of MQLs vs SQLs, you’re ready to start converting leads to revenue for your business.