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Home / Analytics / SQL vs. MQL: What’s the Difference?

SQL vs. MQL: What’s the Difference?

November 22, 2022 By John Lincoln

Not all leads exist equally. While all pose some value to your company, assuming each is equally likely to convert is naïve.

Consequently, you need a system for deciding which leads to dedicate time to. That’s why marketers invented the Marketing Qualified Lead (MQL) and Sales Qualified Lead (SQL) metrics.

What’s an MQL?

MQL, or marketing qualified leads, are leads with an expressed interest in becoming customers. They’re typically generated through marketing campaigns and activities and move on to the sales team for further qualification.

MQLs immediately proceed SQLs in the sales funnel. They haven’t revealed in-depth information, but the information they’ve already expressed indicates clear interest in your product or service.

In other words, MQLs have raised their hand.

They’ve signed up for something, whether that’s a piece of content, a webinar, or a newsletter. Your marketing has intrigued them, and they want to know more.

MQLs have a need your product or service can address. They wouldn’t be interested in learning more about your business if they didn’t believe you could help them somehow.

Why Are MQLs Important?

39% of marketing decision-makers define MQLs as their most crucial marketing KPI.

Why? Because every MQL is a serious potential customer.

The ultimate sales outcome is far from certain. Still, your systems have determined they deserve the time and attention necessary to move them forward.

Differentiating MQLs from lower-quality leads lets sales teams use their scarce time effectively. This removes the bad apples from your basket, leaving sales with a tasty basket of Granny Smiths (SQLs, in this case) to enjoy.

What’s an SQL?

SQLs are leads your marketing team has fully vetted.

They contacted them, asked questions, explored their needs, and determined their budget. The need and requirements are there, and it’s time to send them to sales.

Why Do SQLs Matter?

Most marketers define generating more SQLs as their top priority.

That’s not surprising—an SQL is the fruit apple in the basket. They’re interested and ready to buy, and your marketing and sales teams have done the necessary work to get them there.

An SQL is the finish line for companies with an effective lead management strategy. But for others, it may only be the beginning.

Even if a lead is “ready” to buy, it may not be the right time for them.

They may need to consult with other decision-makers. Perhaps their budget is tight this quarter.

The point is, an SQL isn’t always a sure sale. But if you’ve done your job well, they’re far closer to becoming a customer than any other lead in your system.

How Differences Between MQLs and SQLs Affect Funnel Transitions

Moving a lead from MQL to SQL is easier said than done. The vast majority of MQL sales never move forward, in large part because of misclassification.

Your marketing team may believe a lead is further down the funnel than they really are. Or perhaps your sales team is too eager to get their hands on a “hot” lead and pounces too early.

To avoid these mistakes, you need to understand the exact differences between MQLs and SQLs. Here’s how they’re different:

Lead Behavior

The primary difference between MQLs and SQLs is lead behavior. MQLs have expressed varying interest in your product, while SQLs are ready to buy.

The easiest way to understand the difference is with an analogy. Imagine you’re at a party and see someone you’d like to meet.

You introduce yourself, shake their hand, start talking to them, and the conversation goes well. Now imagine you’re at that same party, but that same person comes up to you and says, “I want to talk to you about your product.”

In the first scenario, the person showed enough interest for you to want to talk to them. In the second, they showed up and immediately started discussing a sale.

The same’s true of leads. An MQL expresses interest in your product, while an SQL is ready to buy.

Conversion Rate

The second difference between MQLs and SQLs is the conversion rate. MQLs have a lower conversion rate than SQLs because they’re at the top of the funnel.

They may be interested in your product, but your team hasn’t vetted them. MQLs may not have the budget, the need, or the authority to make a purchase despite their expressed interest.

On the other hand, SQLs are fully vetted. Your marketing and sales teams have done the work to ensure they’re a good fit for your product.

They’re fully qualified for your product and have a clear intent in making the sale. As a result, their conversion rate is much higher.

Referral Channel Difference

The third difference between MQLs and SQLs is the lead source. MQLs come from a range of sources, while SQLs come from narrower, higher-quality sources.

MQLs come from low-effort sources like:

  • Content downloads
  • Sign-ups for webinars or other events
  • Form submissions
  • Newsletter signups
  • PPC campaigns
  • Inbound calls

SQLs, on the other hand, come from narrower, higher-quality sources.

Your marketing team has already vetted these leads, and they’re ready for your sales team to close the deal.

SQLs may come from:

  • Referrals from current customers
  • Inbound calls from marketing-generated leads
  • Form submissions from targeted landing pages
  • Purchase intent research

This isn’t an exhaustive list, but it shows how the referral channel frames dramatic differences in intent.

Contact Requests

Generally speaking, the most obvious difference between the two is how they meet with your sales team.

If your sales team asks to set up a call or demo with a lead, they’re an MQL. But if the lead requests the meeting, they’re an SQL—just like the party analogy mentioned above.

You’ll only need to pay attention to who’s requesting the meeting. The meeting-maker might not have the authority to make a buying decision.

For instance, your sales teams might receive a demo request from a marketing team employee without a management title.

Before committing to the demo, your team should ensure they’re the appropriate person to meet with.

Lead Demographics

MQLs and SQLs may have different demographics, but that’s not necessarily a good indicator of a lead’s stage in the buyer’s journey.

There are cases where a company may have a particular target market. In this scenario, it’s likely your leads will fit this mold.

For example, say a marketing agency specializes in customer acquisition for legal SEO firms. In this case, their target market is pretty well-defined, and a lead’s demographic is a good indicator of whether they’re an MQL or SQL.

At the same time, in some industries, there are other qualities like job title, geographic region, or even the topics they’re searching for that are better indicators of readiness.

The point is, demographic information can be useful (or not useful) in determining which leads should be moved to your sales team. Work with your sales and marketing teams to determine the characteristics that matter most.

Likelihood to Buy

Last but not least, MQLs are less likely to buy than SQLs. That’s not to say MQLs never buy, but they’re less likely to do so.

For instance, a lead who fills out a form to download a piece of content is an MQL. 

They’re interested in your product but are not ready to buy. They may have only wanted whatever you gated behind the download form.

In contrast, SQLs are highly likely to buy. It’s not guaranteed, but it’s the marketing equivalent of standing on third base—all you need to do is hit a single.

After all, it takes an SQL to make a sale. They’ve discussed their needs and budget, and they’re ready to purchase.

Online retailers, for instance, can’t make a sale without someone adding an item to their cart, entering a shipping address, and paying for the product.

The BANT System

The BANT (Budget, Authority, Need, and Timeline) system is a lead management process used by sales teams to qualify leads. You can use it to precisely decide how qualified—and thus likely to buy—a lead is.

Leads meeting all the criteria below are fully qualified and ready for a meeting with sales:

  • Budget: Do they have the budget to make the purchase?
  • Authority: Do they have the authority to make the purchase?
  • Need: Do they have a clear need for your product?
  • Timeline: Do they have a timeline for making the purchase?

The main benefit of the BANT system is that it helps your sales team prioritize their time.

Your sales team could request a demo from three prospects this week.

Unfortunately, they can’t meet with all three. So, the sales team uses BANT to choose the most qualified leads.

How Lead Scoring Can Help Qualify Leads

Qualifying your leads with a hunch is a losing process. While your instinct still plays a huge role in valuing leads, failing to quantify them as precisely as possible makes massive inefficiencies inevitable.

That’s where leading scoring comes in.

What is Lead Scoring?

Lead scoring is the process of assigning a numerical value to your leads. This allows you to determine how qualified a lead is and how likely they are to convert with infinitely higher precision than your gut feeling.

In other words, it’s a system that takes the guesswork out of lead management by breaking down leads into two groups: those who are ready to buy and those who are not.

Why is Lead Scoring Important?

Lead scoring comes with its own set of benefits. It allows sales and marketing teams to:

  • Align on the criteria used to determine whether a lead is ready to buy
  • Justify the budget for marketing campaigns to executives and stakeholders
  • Have measurable goals to achieve with their campaigns
  • Prioritize their time efficiently with those measurable goals
  • More precisely utilize their marketing efforts and budget

The takeaway is that while lead scoring seems like a lot of work upfront, it pays off.

How Does Lead Scoring Work?

Lead scoring is a complex process, but you can break it down into three main phases:

  1. Create buyer profiles
  2. Score Leads according to Activity
  3. Assign Lead Scores manually

Create Buyer Profiles

The first step is to create buyer profiles. These are semi-fictional representations of your target customers.

Each buyer profile should include the following:

  • Demographics: Who is your target buyer, and what do they look like?
  • Value Driver: What common problem do they have?
  • Decision Stage: What does their decision stage look like?

A buyer profile helps you understand who your lead is. This is the foundational step in determining their quality.

Score Leads According to Activity

After deciding on criteria, you can start assigning lead scores according to their completed activities.

For instance, you might assign a higher lead score to a lead based on the following criteria:

  • Document downloaded: +5
  • Created an account: +5
  • Subscribed to a blog post: +7
  • Signs up for newsletter: +3
  • Signs up for email course: +5
  • Purchased a product: +35

Lead scoring is about quantifying what you know about a lead and using that information to determine how likely they are to convert. 

The goal is to use activity to understand a lead’s “interest” in your company. The more qualified a lead is, the higher their lead score should be.

Assign Lead Scores Manually

Even though you can automate the process of assigning lead scores, it’s best to start by scoring leads manually. Then, once you’ve manually scored a few hundred leads, you can begin to automate the process using specialized software.

The benefit you get from starting with a manual process is having something to compare your automated results to. This makes it massively easier to fine-tune your system.

Effective Lead Qualification is a Game-Changer

Lead qualifying is a crucial step in the sales process.

As emphasized throughout this post, failing to qualify leads causes your sales team to waste time on leads that have no intention of buying. They could better spend that time on prospects who are ready to buy.

The only way to achieve true success with lead qualifying is by identifying those prospects most likely to convert and then prioritizing them over the others. With lead scoring, qualifying your leads is easier—and more accurate—than ever before.

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About John Lincoln

John Lincoln (MBA) is the CEO of Ignite Visibility, a top performance marketing agency backed by Mountaingate Capital. A digital marketing strategist and keynote speaker, Lincoln has managed over 1,000 marketing programs for brands like DoorDash, HBO, Tony Robbins, and Experian. Under his leadership, Ignite Visibility has been named a leading digital marketing agency in the U.S. and made the Inc. 5,000 list six times. Lincoln also spearheaded the development of CertaintyTech, a cutting-edge media mix modelling and forecasting platform. An award-winning marketer, Lincoln has authored three books, including Advolution (2022), and produced films such as SEO: The Movie. Recognized as a Top Business Leader, he has been featured in Forbes and The New York Times and spoken at global events like Web Summit and SMX. Lincoln's mission is to empower businesses through innovative digital strategies while reinvesting in clients, employees, and the community.

About Ignite

Ignite Visibility is a premier full-service digital marketing agency. We were founded in San Diego, CA but are now a 100% remote-first company with Igniters and clients around the globe.

Ignite Visibility is one of the highest awarded digital marketing agencies in the industry, works with some of the biggest brands in the world and is a 6x Inc. 5000 company.

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