When I first got into sales, I thought every new form fill was something to get excited about. I quickly learned the hard way that not all leads are created equal, and that for every great lead that came into the CRM there would be many more spam drops (looking at you, office cleaners), college students researching for papers, or even competitors poking around trying to collect information and emulate our content strategy.
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That’s when I realized how important it is to differentiate between marketing qualified leads (MQLs) and sales qualified leads (SQLs). If you don’t, you end up wasting time chasing the wrong people — and that can clog up your pipeline and cost you your sanity, fast.
In this post, I’ll walk you through what SQLs and MQLs are, how they’re different, and how I’ve seen companies (including some of my own) move leads from one stage to the next.
Table of Contents
- What is a sales qualified lead (SQL)?
- What is a marketing qualified lead (MQL)?
- SQL vs. MQL
- Moving a Lead From MQL to SQL
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What is a sales qualified lead (SQL)?
A sales qualified lead is someone who’s been vetted and deemed ready for a direct conversation with sales. They’ve moved past the “just browsing” or information gathering stage and demonstrated a strong enough intent to buy that it makes sense for a salesperson to actively engage with them.
In my experience, SQLs usually:
- Fit your target persona or ideal customer profile (ICP).
- Have shown buying signals like inquiring about pricing, asking for clarification of features, or requesting a demo.
- Have authority, budget, and need.
I’ve always thought of SQLs as the people you’d be comfortable putting on your meeting list today. If I’m going to block time for a one-to-one conversation, it should be with someone who has a shot at becoming a customer.
What is a marketing qualified lead (MQL)?
A marketing qualified lead is someone who’s engaged with your marketing content and shows potential interest but isn’t ready for a sales pitch yet. They’re curious, but they’re still in the education and research phase.
For example, someone who downloads an ebook, attends a webinar, or regularly clicks through emails might qualify as an MQL. They’re raising their hand to say, “I’m interested,” but they’re not yet demonstrating that they’re ready to buy.
At my agency, I see MQLs as the ones you nurture — send them more resources, answer their questions, engage with them on social media or in your preferred channel, and keep building trust and authority until they cross that line and warrant a conversation with sales.
SQL vs. MQL
Assuming you have the good fortune of a slew of inbound leads, let’s review how to categorize them. The following graphic shows the common path leads take in HubSpot’s inbound sales methodology.
As you can see, qualified leads can either be in the connect or explore columns depending on what specific type of qualified lead they are.
The Difference Between an MQL and SQL
- MQLs are potential buyers in the research phase, showing interest through marketing engagement.
- SQLs are vetted prospects who’ve shown enough intent to justify a sales conversation.
In other words, an MQL is someone looking through the proverbial shop window, while an SQL is someone walking in and asking how much the product costs.
Why Differentiating Between MQLs and SQLs Is Important
I’ve seen teams treat every lead the same (and even had management decree this approach) with pretty predictable results: Sales reps waste hours calling people who just wanted to download some free resource or lead magnet.
On the flip side, I’ve seen strong leads languish in the MQL stage for too long, allowing competitors to swoop in.
According to an Agency Analytics analysis across industries, around 10–20% of MQLs convert to SQLs. If your numbers are much higher or lower than this, it might be an indication to rethink the processes you use to generate, qualify, and hand off leads, but do some industry-specific research first.
Some sectors, like enterprise SaaS, are able to convert around 40% of MQLs as reported by Powered By Search, but these companies are relying on highly sophisticated funnels to generate very valuable leads. Your mileage may vary.
Personally, I’d rather risk talking to a lead a little early than miss them entirely, but the real key is alignment between departments, or systematizing how and when a lead “graduates” from MQL to SQL. When marketing and sales agree on what an MQL and SQL look like, you avoid the finger-pointing and instead focus on nurturing prospects and moving them smoothly through the funnel.
Lead Generation: The Importance of Lead Nurturing
Moving a Lead From MQL to SQL
So how do you know when an MQL is ready to become an SQL? I still rely on a mix of tools and gut instinct. Instinct is fuzzier and harder to explain, so let’s focus on the tangible signals.
Lead Score
Lead scoring is a common starting point when companies are trying to determine how leads should be qualified. A lead score is a numerical value that tells you a) how closely a lead matches your ideal customer profile (ICP) and b) how engaged they are.
For example, your best customers might most often have 50–200 employees, so a prospect matching that criteria could be assigned 15 points while companies with less than 20 employees lose 5 points. In terms of engagement, downloading a pricing sheet might add 25 points to a lead’s score, while opening your email newsletter might add just one or two.
At one company I worked with, we set thresholds — a lead over 75 points went to sales. It wasn’t perfect, but it gave us a consistent, objective way to prioritize who deserved the limited attention of the sales team.
Lead Behavior
I pay close attention to actions that suggest both buying intent and a sense of urgency:
- Requesting a demo or consultation.
- Visiting the pricing page multiple times.
- Replying to nurture emails with specific questions.
These behaviors often tell you more than any demographic data ever could. If someone is actively seeking answers from your organization, they’re moving closer to a final decision. Are they asking about implementation timelines? They’re moving, and quickly.
Leading Indicators
Particularly in the world of SaaS, it’s a good sign when a lead is coming to your organization when they’ve historically used a competitor’s technology. If they’re knocking on your door, it probably means their solution isn’t cutting it, and it’s your chance to swoop in and save the day.
In these instances, armed with a baseline degree of knowledge about the prospect, I’d recommend you fast-track the lead through the qualification process and get it in front of your sales team. Speed is key here.
Likelihood to Buy
Some CRMs (HubSpot included) now use AI to predict the likelihood that a lead will close. I’m a big fan of using these tools as a directional signal. They won’t replace human judgment, but they’re a useful nudge to help you allocate limited human capacity.
Give them a shot and test their efficacy in your own organization and workflow. You might find they yield no insights, or they could end up working about as well as much more complicated lead scoring algorithms. There’s only one way to find out.
Incorporating Leads Into Your Sales Process
Once an MQL makes it over the line, you need a clear process for how sales picks them up. In my teams, we’ve used automated workflows so that the moment a lead hits SQL status, they get routed to the right rep (often based on territory, domain expertise, or a combination of other factors) and logged as an active opportunity.
The worst thing you can do is let a newly qualified lead sit untouched, which is why I always try to reach out within 24 hours (and often much faster). Speed shows commitment, and I’ve been told by more than one of my own customers that they chose my company simply because we were the quickest to respond.
Following the (Sales Qualified) Lead
At the end of the day, the difference between MQLs and SQLs isn’t just a marketing exercise — it’s about respect for everyone’s time. Marketing needs to focus on generating interest, while sales needs to focus on closing real opportunities.
In my experience, the most successful companies are the ones where both teams actually talk to each other and agree on what “qualified” looks like.
I’ve wasted plenty of time chasing the wrong leads, but I’ve also closed some of my biggest deals by engaging with the right SQLs at just the right moment. If you get the distinction between MQL and SQL right, you’ll save yourself a lot of frustration and set yourself and your team up for a stronger, more productive pipeline.
Free Guide: 101 Sales Qualification Questions
101 Questions to Ask Contacts When Qualifying, Closing, Negotiating, and Upselling.
- Budget Questions
- Business Impact Questions
- Competitor Questions
- And More!
Download Free
All fields are required.
Sales Qualification
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