MQL vs. SQL: How to define lead types in marketing and sales
The buyer’s journey has never been more complex. With new technologies are drastically revolutionizing the way we market and purchase products, it’s no longer as simple as a customer walking into your store and buying something they need.
Nowadays, consumers are inundated with ads on their phones, laptops, TVs, and, of course, billboards. More choice for them means more competition for you. To stay competitive, businesses need to be highly strategic about how they identify and interact with their prospects.
That’s where MQLs (marketing-qualified leads) and SQLs (sales-qualified leads) come in. It’s highly probable that you’ve heard of these two acronyms before. But what differentiates the two? And why do they even matter?
Throughout this post, we’ll also explore why lead qualification and lead scoring are such critical business practices, the nitty-gritty criteria which set MQLs and SQLs apart, and how to nurture an MQL into an SQL.
What are MQLs?
If you haven’t already, read our detailed guide to MQLs here. But if you’re short on time, here’s the gist of it.
Marketing-qualified leads have demonstrated an interest in your company and your products. They’ve usually intentionally interacted with your brand by taking part in some sort of quid pro quo exchange — they leave their contact details in exchange for promotional emails, a resource download, or a webinar sign up.
But not everyone who demonstrates an interest in your company automatically becomes an MQL. In some instances, they’re not the right leads to be going after (more on this later).
However, if they do fit your lead qualification criteria, then they can be accepted into the sales funnel and classified as a marketing-qualified lead.
Once a marketing-qualified lead has been identified, it’s now the marketing team’s job to lead them further down the funnel until they’re ready to speak directly with the sales team (and hopefully purchase).
What are SQLs?
SQLs are further down the funnel than MQLs — they’ve usually been nurtured by the marketing team’s efforts and are now closer to purchasing than they were previously.
Once they’ve demonstrated a significant interest in your products, it’s now the sales team’s job to close them. Simple as that.
Of course, not all SQLs are created equal. Someone who fills out a form immediately requesting a demo is probably a hotter lead than another prospect who visited your website multiple times but over a long period of time.
It’s also useful for a salesperson to know which particular pain-point their leads are trying to solve. Usually, this information can be gathered by analyzing the lead’s interactions to date with your organization.
Which of your social media ads did they click through on? Which of your marketing emails did they open? Which website pages did they visit? Which forms did they fill out?
This, provided with some general lead qualification data (industry, age, position, etc.) should give the salesperson all they need to contact the prospect with confidence.
Differences between MQLs and SQLs
Essentially, MQLs and SQLs aren’t all that different — they describe a prospect who’s shown interest in your company, but for whatever reason hasn’t yet become a customer.
The main difference between them is how far along their buyer’s journey they are, and which of your teams are responsible for handling them.
As you might imagine, the marketing team is in charge of MQLs. These are top- or middle-of-funnel prospects who aren’t very far along in their buyer’s journey. They require a softer, more generalized approach than prospects who are further along the sales funnel.
At this stage of the sales funnel, you need to steadily raise their awareness of your organization and pique their interest in your products. You’re also acquiring data so that you can work out what precisely they need and tweak your marketing outreach accordingly.
Once a prospect has shown enough continued interest to be classified as a bottom-of-funnel SQL (we’ll delve into more detail later on about how to properly make this distinction), they’re then passed over to the sales team to complete the sale.
The principle of lead qualification
Before you can classify a lead as an MQL or an SQL, you need to first make sure they’re worth pursuing. As a business, you don’t want to waste time, money, and effort going after people who won’t actually end up purchasing anything — this is where lead qualification comes in.
Lead qualification refers to the strategy that businesses have in place for identifying potential leads and nurturing them into becoming customers.
You basically want to work out whether or not:
- The prospect is in the right industry or company for your product
- They have pain points which your products can solve
- They’re in a position to make buying decisions
If prospects don’t meet these criteria, then you should automatically disqualify them. Sure, it feels good to have lots of people interested in your products. But if they’re ultimately never going to purchase, there’s little point in trying to convert them.
Ineffective (or nonexistent) lead disqualification can have a worrying impact on organizational morale. You don’t want your marketing and sales teams constantly coming up against people who simply won’t ever become buyers.
Not only is it a waste of resources, but it also prevents your team members from succeeding at their roles.
How to score MQLs and SQLs
Qualified your leads as valid prospects? Great. Now it’s time to engage in a lead scoring process to figure out exactly how far along the funnel they are.
As the name suggests, lead scoring involves giving each lead a score (usually out of 100). In general, the higher the score, the further down the funnel — and the closer to purchasing – they are.
Lead scoring gives you a quantifiable, standardized measurement for classifying each lead as an MQL or SQL.
Leads can be scored on a variety of potential actions: the number of times they’ve visited a website, the percentage of marketing outreach emails that they’ve opened, if they’ve downloaded a whitepaper, or if they filled out a form asking for a demo.
This list is by no means exhaustive. For example, a prospect attending an event is also an indication that they’re interested in your products. It’s up to each individual company to decide which specific actions would affect a prospect’s lead score.
Before creating your lead scoring process, it’s important that you deeply analyze your company’s customer history.
For example, do you find that people who click on LinkedIn ads are more likely to purchase than those who come via Facebook? Do event attendees more readily convert than those who download your whitepapers?
This is where your company data is vital. The more you know about your prospects, the better. For B2B businesses, you’d ideally know which company they work for, how large it is, where it’s located, and which industry it’s in.
Once you have a tangible measurement outlining where a prospect is in their buying journey, you can then classify them as either an MQL or an SQL — and pass them off to the marketing or sales teams.
What you need to decide
It’s critical that sales and marketing come together to determine what makes an MQL/SQL, and how to approach each of them. It might even be worth drafting up an SLA (service level agreement) which provides answers to the following questions:
- What’s each team’s objective? Is the marketing team focused on the number of SQLs but the sales team on revenue? Keep your team’s overarching goal in mind — this will help when fine-tuning both your lead generation and lead qualification processes.
- What precise lead score makes an MQL? Or is an MQL any qualified lead that hasn’t yet converted?
- How do you follow up with an MQL? How quickly do you follow up on any new leads, and how do you get in touch with them?
- How many follow-up attempts do you make before an MQL is downgraded back to being a prospect?
- What precise lead score makes an SQL? What does an MQL need to do to become an SQL?
- How will you maintain ongoing communication between sales and marketing teams? Sales needs to let marketing know what makes a good prospect, and marketing needs to alert sales as to each prospect’s pain points, the content they’ve consumed, and what their buyer journey to date looks like.
How do you know when an MQL becomes an SQL?
Working out how and when MQLs turn into SQLs is a complex process. If you send leads across before they’re ready, they probably won’t end up converting — and you’ll incur the wrath of your sales team.
However, if hot leads are left languishing for too long without speaking to a sales representative, then they may start to look elsewhere.
This is an ongoing process that requires constant dialogue between marketing and sales teams. Ideally, marketers should pique a prospect’s curiosity, increase their interest in the company and products, and get them to confirm themselves that they’d like to be passed over to sales (by filling out a demo form, for example).
There should also be a clear cut-off in your lead scoring process where MQLs become SQLs. For example, an MQL might have a score of 40+ (out of 100), and anyone who has a score of 80+ becomes an SQL.
Each time that an MQL visits the site, their score increases by five points. Each time they click on a link from a marketing email, their score increases by 10 points. If they fill out a demo form, they are automatically passed over to sales.
Once you’ve decided how you’re going to weigh each touchpoint, map this out in your CRM (or marketing automation software) and let it automatically take care of the rest.
By assigning a numerical score to your leads, you avoid having to rely on sentiment. It’s hard to know how ready someone is to purchase according to how you feel — it’s far more accurate to use a standardized, agreed-upon, organization-wide measurement.
Why do MQLs and SQLs matter?
Without clear parameters outlining who’s an MQL and who’s an SQL, the entire sales process would be a messy melee with different teams bombarding the same prospects from different angles.
You don’t hire marketers to close sales. Sure, if they do then that’s great — but their job is to raise awareness of your brand, pique your prospects’ interest, and get them excited about potentially buying your products.
Likewise, you don’t hire salespeople to raise awareness or interest. Salespeople are there to aggregate all the information you have on a prospect, tailor their pitch accordingly, and close a sale.
Simply put, lead qualification ensures that marketing and sales teams have clear boundaries — that they know which prospects to go after and at which stage of the buyer’s journey. By properly scoring and assigning MQLs and SQLs, you’ll keep your sales and marketing engine organized and effective.