February 10, 2023

MQL vs. SQL: Differences & Comparison in 2024

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Key takeaways

  • Now more than ever, sales and marketing need cross-discipline support, and they need quantifiable proof of the value of their efforts. MQLs and SQLs can offer a lot in this regard.
  • When the two teams work together to define their qualification criteria, both benefit from better leads, and both avoid the frustrations of wasted efforts. 

Some industry terms have definitions with precise, universally agreed meanings. Others are more linguistic guidelines than actual rules. And some are listed in the dictionary under “it depends.” Marketing Qualified Leads (MQL) and Sales Qualified Leads (SQL) fall into the latter category. 

SQLs and MQLs are metrics that can be either meaningful or meaningless depending on how they’re used. And missteps or masterstrokes for either begin with what the term actually means.

What Are MQL & SQL?

Here are the best general-purpose descriptions that can be offered for MQL vs SQL:

A lead is a potential sale, especially in B2B. A “qualified” lead is one marked as heightened interest, and thus more likely to convert to a customer/client for the brand. In other words, it’s a label instructing the marketing and sales teams to track, nurture, and follow up with the lead.

If the lead was vetted by the marketing team, it’s labeled as an MQL. If it was qualified by sales, it’s marked as an SQL.

That’s it. Those are the only commonalities that apply across the board. Anything more granular or specific will vary by organization, team, strategy, and a host of other factors. 

ALSO READ: Finding B2B Sales Leads That Don’t Suck 

Common Threads

Some of those factors are popular enough to merit mentioning, however, and may help organizations that want to set their own MQL vs SQL standards. 

Lead Priority

Most teams that have defined criteria for one type of qualified lead will usually have criteria for the other as well. SQLs and MQLs tend to go hand in hand. However they are not the same, and in some organizations one will have primacy over the other.

Differences in department functions are the main reason for this viewpoint. Marketing teams are tasked with increasing brand visibility and reach, but typically don’t see the end of the process (where a sale is made).

Conversely, sales teams interact with leads more directly, but usually on a one-on-one basis. They can see what concerns and details contribute to a lead’s final decision, but often don’t see the beginning of that journey for any customer they contact.

The divide-and-conquer approach can either be a strength or a weakness here (more on that below), but either way it tends to create a hierarchy between the two lead types, whether that’s part of the official process or not.

A more formalized sales funnel may have MQLs serve as a handoff point. Once a lead becomes an MQL, their information is passed on to the sales team for follow-up. If they respond to further sales outreach, they’re upgraded to an SQL, and sales reps work to determine if a deal can be reached.

For organizations that are more siloed in their approach, SQLs and MQLs may not be part of a sales funnel at all. Instead, it may be more a matter of interdepartmental politics. If marketers send along MQLs that don’t convert well, sales staff may instead prioritize their internally generated leads whenever they can.


Qualifiers are the benchmarks used to separate the warm leads from the cold. When discussing SQLs and MQLs, this is the aspect that makes them impossible to define concretely. Different organizations—and different teams—will use different benchmarks in their qualifying process.

That said, the majority of qualifiers are tied to specific engagement metrics, both for sales and marketing. Below are some examples of popular qualifiers.

Marketing might qualify leads that:

  • Sign up for a newsletter.
  • Engage with the brand on social.
  • Share brand content on their own social account.
  • Download an ebook or other digital asset.
  • Click on CTA buttons in emails, on landing pages, or on ads.
  • Visit a set number of site pages (e.g. blogs or product pages) or return to the site a set number of times.

Sales might qualify leads that:

  • Respond to email outreach.
  • Sign up for a demo or free trial.
  • Call the company directly.
  • Engage with the website chatbot.
  • Connect with sales reps on social platforms, or respond positively to messages there.

Marking a lead as qualified may happen after just one benchmark has been reached, or it may require crossing multiple thresholds before the lead is tagged for follow-up. Qualifiers may prove more or less effective over time if leads tied to them are consistently resulting in the same outcomes.=

Making the Most of MQL vs SQL

Marketing and sales both bring important insights and expertise to the table, but when the two teams don’t work in concert, that ineffectiveness can result in frustration and wasted efforts. MQLs and SQLs, regardless of how leads are classified or what the process does with them, are only valuable as metrics when they are calibrated to accurately gauge a lead’s interest.

Below are some guidelines on how to achieve that cooperative calibration, and some common mistakes that complicate the process.

ALSO READ: Defining Qualified Leads: What Marketing and Sales Need to Agree On

Effective Lead Qualifying Strategies

Leads, even qualified leads, are just a metric—a key performance indicator (KPI). Ultimately, it’s a value in a spreadsheet cell, and doesn’t mean anything beyond its numerical value. As a result, many teams find that the metric fails to measure or promote real success.

The ones that do see success recognize that the leads metric is a placeholder; one that represents actual human beings.

The Human Factor

Leveraging MQL vs SQL to build an effective sales funnel is an exercise in psychology and empathy. These aren’t numbers or email addresses moving down the funnel. They’re people. They have agendas and interests all their own. So, benchmarks need to indicate alignment between the lead’s use case and the brand’s offerings.

This all starts with questions. Why did they read the blog, download the ebook, or sign up for the newsletter? What questions do leads ask on sales calls? Who’s choosing not to convert, and were there quantifiable reasons for their decision?

Some of this can be accomplished internally, via empathy mapping, consulting experts among the staff, and looking back on previous experiences and data. Getting those answers directly from the target audience, however, is the more reliable strategy in the long run.

Surveys, solicited customer feedback, focus groups, social media polls, the list of possible tactics here runs pretty long. Regardless of how the information is gathered, the goal is to understand three things:

  1. How users discover your brand.
  2. Why they interact or engage with a given touchpoint.
  3. What do they find compelling or repulsive?

As this information is gathered, it should provide guidance toward benchmarks that are stronger indications of interest and alignment, allowing those to be used as the qualifiers for leads. The process can then be repeated as more leads and new touchpoints start to add to the stack. It’s a feedback loop that ensures conversion rate optimization efforts actually optimize anything.

Done right, this data will aggregate into concrete answers regarding who is being qualified as a lead that shouldn’t be, and how to prevent those false leads from moving down the funnel.


Sales funnels that struggle to find value in their lead generation efforts typically suffer from a sales-marketing segregation. Siloing the departments prevents either side from being bolstered by the insights of their counterpart. The result is poor lead gen, poor conversion rates, and often, poor retention rates for sticky business models.

Marketing professionals are trained to reach a broad audience. They look for ways to broadcast the brand message so that it will find more of the right people, so that anyone who might find the brand’s offerings beneficial will know how and where to get those offerings.

Sales professionals are trained to help people weigh the costs and benefits of a purchase. Where marketers are usually one-to-many, salespeople are more practiced in having a direct dialogue with their audience. They hear the feelings and concerns of their audience straight from the source, and usually have a better idea of what benefits or features are real linchpins.

With a little collaboration, marketers can leverage the expertise of sales teams to refine branding and messaging. If an experienced sales pro knows exactly what to say, an experienced marketer gives them the right megaphone and points them in the right direction, metaphorically speaking.

Sales can help marketers know what details to focus on, while marketers can build processes that effectively pre-screen leads. Done properly, sales can focus on only the most valuable leads, and marketers can minimize efforts spent on ineffective tactics.

When the two teams work together to define their qualification criteria, both benefit from better leads, and both avoid the frustrations of wasted efforts. 

Lead Qualifying Pitfalls

Much of this has already been pointed to, but these missteps bear repeating, at least in summary.


  • Define MQL vs SQL standards in isolation.
  • Set qualifying benchmarks at random.
  • Assume the other department just doesn’t know what they’re doing.
  • Ignore customer/lead feedback.


  • Plan metrics around direct audience insights.
  • Measure lead performance and optimize over time.
  • Build sales funnels via marketing-sales collaboration.
  • Prioritize methods that produce brand evangelists.
  • Leave room for mistakes that can be lessons learned.

Unless carefully crafted, lead generation processes struggle to produce a measurable impact on long-term growth.

Reaping the Rewards

Current economic situations have prompted many brands and organizations to cut back on spending. In most cases, the first budget cuts are assigned to marketing and sales teams.

Now more than ever, sales and marketing need cross-discipline support, and they need quantifiable proof of the value of their efforts. The MQL vs SQL debate can offer a lot in this regard.

When done right, MQLs can:

  • Prove the value of marketing investments.
  • Those writers, SEO pros, and social experts are more than just another line on the HR budget sheet, and MQLs can help prove it.
  • Help sales pros focus their time on more profitable leads.
  • Weed out the false leads (like the story above).
  • Provide a system of measuring and optimizing demand- and lead-generation efforts.

Ultimately this can lead to improved conversion rates, sales numbers, and customer retention.

SQLs, when done right, can:

  • Align sales and marketing priorities, so everyone knows which green flags for which to be on the lookout.
  • Connect marketing efforts to sales wins, so the whole team succeeds together.
  • Set benchmarks for marketing, so they know when to pass leads on to sales, and when to let them incubate a little longer.
  • Identify methods, tactics, strategies, and efforts that are providing reduced ROI.

Done together, lead quality can be improved dramatically, providing a catalyst for accelerated growth in the market (without leaving a bunch of unhappy former customers in the wake).

The bottom line is that progress is easier to achieve when it’s measured accurately. Improvement is easier to achieve when results are quantifiable and attributable. The right processes can give us those numbers, and can validate our efforts to those in the company responsible for deciding what budget items are “indispensable.”

But these numbers still represent people. Management may not always be intimately familiar with the humans behind the figures, but those of us in sales in marketing should be. It’s our job to make sure the brand is offered to the right people.

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What are Marketing Qualified Leads?

A marketing qualified lead, or MQL, is a lead identified by standards established by a marketing team.

What are Sales Qualified Leads?

A sales qualified lead, or SQL, is a lead identified by standards established by a sales team.

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