MQL vs SQL comes down to who has checked the lead: a marketing qualified lead (MQL) has shown interest and fits your target, while a sales qualified lead (SQL) has been checked by sales and is ready for a direct sales conversation. The MQL comes first, and the move from MQL to SQL is the moment marketing hands the lead to sales.
This article is part of our guide to inbound lead generation in B2B. It covers clear definitions, the conversion rates you can expect, the criteria to write down with your sales team, and the mistakes that make good leads wait.
What is an MQL?
An MQL, or marketing qualified lead, is a contact that marketing considers worth following up. HubSpot describes it as a contact who has engaged with marketing content and shows potential interest (HubSpot).
In practice, a lead becomes an MQL when two things are true:
- Fit: the company matches your target (size, industry, country, the tools they use).
- Interest: the person has done something that shows curiosity, such as reading several product pages, downloading a guide or attending a webinar.
An MQL has not asked to talk to sales. That is the important part. Most MQLs are still researching, and many will never buy.
What is an SQL?
An SQL, or sales qualified lead, is a lead that sales has checked and accepted as a real opportunity to pursue. Salesforce defines it as a lead who has expressed enough interest to be ready for the sales process (Salesforce).
What turns an MQL into an SQL is not more clicks. It is information that only a direct exchange gives you:
- the problem the buyer wants to solve;
- the timing, even approximate;
- who is involved in the decision;
- whether your offer can actually solve it.
Our guide on how to qualify leads covers these criteria and the frameworks (BANT, CHAMP, MEDDIC) that structure them.
MQL vs SQL: the main differences
The easiest way to see the difference is to look at who decides, on what basis, and what happens next.
- Who qualifies: marketing qualifies the MQL, usually with rules or a score. Sales qualifies the SQL, usually in a conversation.
- What it is based on: an MQL is based on behavior and fit. An SQL is based on a stated need, timing and a decision process.
- What the buyer did: an MQL consumed content. An SQL talked to someone, or asked for a meeting.
- What happens next: an MQL goes to nurturing or to a first contact. An SQL gets a meeting, then becomes an opportunity in your pipeline.
HubSpot's default lifecycle stages show the order clearly: Subscriber, Lead, Marketing Qualified Lead, Sales Qualified Lead, Opportunity, Customer, Evangelist (HubSpot Knowledge Base). The MQL always sits before the SQL.
Where does the SAL fit?
Many teams add a step between the two: the SAL, or sales accepted lead. Sales reviews each MQL and either accepts it or rejects it with a reason. That small step does two things. It stops MQLs from sitting unread in a queue, and it gives marketing a reason for every rejection, which is the only reliable way to improve the MQL definition.
What is a good MQL to SQL conversion rate?
There is no single benchmark, because every company draws the MQL line in a different place. Even the same research firm uses different definitions in different reports. Keep that in mind when you compare.
With that caveat, here are published figures:
- First Page Sage reports MQL to SQL rates by industry ranging from 10% (legal services, real estate) to 26% (business insurance, HVAC), with B2B SaaS and IT and managed services at 13% (First Page Sage).
- Salesforce cites Gartner research finding that only 21% of MQLs convert to SQLs (Salesforce).
Read these numbers the right way round. A low MQL to SQL rate does not always mean marketing sends bad leads. It can also mean sales follows up too late, or that the MQL rule rewards activity that has nothing to do with buying, like reading a blog post.
The most useful comparison is your own rate by channel, month after month. If one channel's rate drops, look at what changed in the source, the rule or the follow-up time. Since the speed of your first response weighs heavily on whether a lead ever reaches sales, measure the delay between MQL and first contact at the same time. And remember that most visitors never become leads at all: you can estimate what your lost visitors cost before you tune the bottom of the funnel.
When should marketing hand a lead to sales?
Hand off when sales can do something useful that marketing cannot. In practice, that means one of three situations:
- The buyer asks for it. A demo request, a meeting booked, or a question like "can we start in January?" is a sales conversation. Do not route it through nurturing first.
- The buyer asks a buying question. Questions about pricing, security, integrations, contracts or rollout mean the buyer is evaluating. They deserve an answer from someone who can commit.
- The fit and the timing are confirmed. The company matches your target and you know they want to act in the coming months.
Activity alone is not a reason to hand off. Ten blog visits from a student do not make an SQL. One visit to the pricing page followed by a precise question often does.
This is where a conversation on the website changes the picture. When a visitor can ask their question during the visit, the line between MQL and SQL becomes visible in what they write, not in a score. An AI agent such as the Nudge Website Agent answers during the visit and offers a meeting in the chat when the need is clear, so a sales ready visitor does not wait for a scoring rule to fire.
A concrete example
A visitor from a 200-person logistics company reads your pricing page twice in a week. In a classic setup, the score crosses a threshold, the contact becomes an MQL, and a nurturing email goes out two days later.
With a conversation on the page, the same visitor asks: "Does it work with our existing scheduling tool, and can we roll it out to three sites before March?" That single question gives the fit, the problem, the timing and the scope. It is an SQL in everything but name. The right move is to propose a meeting now and pass the question to the rep who will take it.
How to define MQL and SQL with your sales team
Definitions that live only in marketing's head create the classic argument: "your leads are bad" against "you never call them". Write them down together, on one page.
- List your disqualifiers first. Students, competitors, job seekers, countries you do not serve. Excluding them is easier than scoring everyone else.
- Define the MQL with fit plus one strong signal. Prefer a few high intent actions (pricing page, comparison page, a question asked) over many low intent ones.
- Define the SQL with what sales must know before a meeting. Usually the problem, the timing and the decision process. Nothing more.
- Add the accepted or rejected step. Every rejected MQL needs a reason from a short list.
- Set a response deadline. For example, sales contacts each new SQL the same business day.
- Review every month. Look at the rejection reasons and the MQL to SQL rate by channel, then adjust one rule at a time.
The handoff itself, what sales receives and how, is covered in our guide to the sales handoff process.
Common MQL and SQL mistakes
- Counting MQLs as a goal. A marketing team rewarded on MQL volume will lower the bar. Track SQLs and meetings instead.
- Scoring content consumption too high. Downloading an ebook is research, not buying intent.
- Sending hot leads to nurturing. Someone who asked about pricing should not get a welcome sequence.
- Losing the context at the handoff. If the rep calls without knowing what the buyer asked, the buyer repeats themselves and the first call feels like a form.
- Never closing the loop. Without rejection reasons, marketing cannot improve its definition.
Buyers spend little time with sellers. Gartner found that B2B buyers spend only about 17% of their buying time meeting potential suppliers (destinationCRM, reporting Gartner, 2018). Every day an SQL spends waiting is taken from that small window.
How Nudge handles the MQL to SQL handoff
Nudge does not add a scoring step between your visitors and your sales team. The Website Agent answers visitors during their visit, from your website and documents, and each answer cites the page it comes from. The questions buyers ask show their need, their context and their timing, which is most of what an SQL definition requires. When the need is clear, the agent books the meeting in the conversation, without a form.
The Handoff Agent then prepares the meeting for the closer: what the prospect wants, what they asked and the objection already raised are in the brief. Sales starts from the buyer's own words. To see how it would handle your leads, ask the agent on our site.
Frequently asked questions
What comes first, MQL or SQL?
The MQL comes first. A contact becomes a marketing qualified lead when they fit your target and show interest, for example by reading your pricing page or downloading a guide. They become a sales qualified lead once a salesperson has checked the fit and the need. Some teams skip the MQL stage for leads who ask for a meeting directly, which is the right call.
What is a good MQL to SQL conversion rate?
There is no universal number because each company defines an MQL differently. First Page Sage reports rates from 10% to 26% depending on the industry, with B2B SaaS at 13%. Salesforce cites Gartner research finding that 21% of MQLs convert to SQLs. Track your own rate by channel every month and look at the trend rather than the benchmark.
How do you convert an MQL into an SQL?
Answer the MQL's questions quickly and in context, then check the few points sales needs: company fit, the problem, the timing and who decides. A conversation does this faster than a sequence of emails, because the buyer's own questions tell you most of it. When the lead meets your SQL criteria, book the meeting and pass on what they said.
What is an SAL?
An SAL, or sales accepted lead, is a lead that sales has reviewed and agreed to work, between the MQL and the SQL. Adding this step forces sales to accept or reject each MQL with a reason. It is the simplest way to stop arguing about lead quality, because rejected leads come back to marketing with an explanation.
Is an MQL more qualified than an SQL?
No. An SQL is further along than an MQL. The MQL has shown interest in your marketing; the SQL has been checked by sales and is ready for a direct sales conversation. In HubSpot's default lifecycle stages, for example, Marketing Qualified Lead comes before Sales Qualified Lead, then Opportunity and Customer.
