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MQLs vs. SQLs: Breaking Down the Differences

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In the process of becoming customers for a business, people go through a few different stages.

One of those stages is becoming a lead, which is what you call someone who has an interest in a company but isn’t yet ready to buy right then and there. To turn a lead into a customer, both your marketing and sales teams have to engage with them.

But even leads go through multiple stages before they become customers, and we’re here to talk about two of the most important such stages—MQLs vs. SQLs, or marketing qualified leads vs. sales qualified leads. But what are MQLs and SQLs, and what’s the difference between them?

In this blog post, we’ll break down the distinction, as well as why both types matter. Keep reading to learn more!

What are MQLs and SQLs?

To effectively compare MQLs and SQLs, we first have to establish what each one is. SQLs and MQLs are similar, but they’re not the same thing.

What are MQLs?

MQL stands for marketing qualified lead. An MQL is a lead that is ready to be targeted by your marketing campaigns. They’ve expressed a base-level interest in your products, services, or company, but they haven’t engaged too much with you beyond that, nor have they revealed much detailed information about themselves.

When you identify someone as an MQL, you’re identifying that they’re a good lead to start marketing to. You can send marketing materials their way, target them in ad campaigns, and more.

An MQL is handled by your marketing team as you nurture them toward being ready to make a purchase. Once they reach that point and start thinking about buying, they become an SQL.

What are SQLs?

SQL stands for sales qualified lead. A lead becomes an SQL when they show a strong enough interest in your company—and a willingness to buy—that indicates it’s time for your sales team to start engaging with them directly. When a lead transitions from an MQL to an SQL, your marketing team hands them over to the sales team.

SQLs are usually handled by direct consultations. So, where an MQL might warrant ad targeting or email marketing, an SQL warrants direct follow-up in the form of a phone call or meeting.

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MQLs vs. SQLs: How to tell them apart

Now that we’ve established that MQLs are ready to be marketed to while SQLs are ready to be sold to, let’s look at how you can tell them apart from one another. This will help you figure out the appropriate time to transition leads from one to the other.

Take a look at these three characteristics to determine whether a lead is MQL or SQL:

1. Lead behavior

One of the most reliable ways to distinguish SQLs and MQLs is by how they engage with your brand online. If leads are only just starting to interact with you, they’re probably MQLs, whereas a lead who routinely visits your site may be ready to move to the SQL stage.

To judge lead behavior, you can look at factors like how often someone visits your website and how long they spend there. If someone’s only been to your site once and only visited a couple of pages there, they’re definitely an MQL. But if they’ve been there 10 times and routinely browsed your service pages, it may be time to consider them an SQL.

The same goes for the way leads engage with your marketing elsewhere online, like opening emails and engaging with you on social media.

2. Lead score

To help you determine where leads are in the marketing and sales funnels, you can assign them each a lead score. A lead score is simply a number that represents how valuable they are to your company.

Your lead score can be based on various things, including many of the same components that are included in lead behavior, like site visits. Whatever criteria you use, though, the idea is to help you identify which leads are the furthest along in the funnel.

An MQL can have a decent lead score, but it won’t be on the upper end of the spectrum. On the other hand, you can identify SQLs by finding leads with extremely high scores. These are the leads who are just about ready to convert.

Bear in mind that lead scores can and will change based on changes in user behavior—if a lead begins engaging with you more, their score will go up, while if they start engaging with you less, it will go down.

3. Likelihood to buy

Finally, you can distinguish between MQLs and SQLs based on how likely they are to become customers.

Let’s say you have a lead who’s visited your site 10 times. By itself, that seems promising. And maybe it is promising if those visits have continued to demonstrate an interest in buying from you.

On the other hand, maybe the visits declined in frequency near the end, and after the last visit, the lead unsubscribed from your emails. Not so promising anymore.

Depending on the version of the above example, the lead might be more or less likely to buy. If a lead demonstrates an interest in buying from you and their interest seems to only be going up over time, that shows a strong likelihood to buy, meaning they probably qualify as an SQL. If not, they’re probably still an MQL.

Why MQLs and SQLs matter

You might be wondering why you need to keep track of MQLs and SQLs. Why bother categorizing your leads?

The answer is that using SQLs and MQLs helps you determine when your leads are ready to move from marketing to sales. That’s a huge step in the customer journey, as it marks a transition from middle-of-funnel content like emails and ads to a bottom-of-funnel approach involving personal outreach.

The last thing you want is to make that transition at the wrong time. Doing so would result in you spending too much—or too little—time on the marketing process, which would certainly drive leads away. Trying to push an MQL into a purchase right away probably won’t end well.

By categorizing each lead as an MQL or SQL, though, you can ensure you market to them in the most effective way. That will help you convert more of them in the long run, earning you more revenue.

The importance of marketing to generate MQLs vs SQLs

Marketing is crucial to working with both MQLs and SQLs. Generally speaking, MQL marketing shares similarities to top-of-the-funnel and middle-of-the-funnel marketing, while SQL marketing involves a more personalized bottom-of-the-funnel approach. 

Let’s look at marketing strategies to use for generating MQLs and converting SQLs.

Marketing strategies for MQLs

Marketing strategies for generating MQLs involve identifying your ideal customers and attracting them to you using a wide-net approach. 

Effective MQL-generating strategies include:

  • Content marketing: The most accessible form of marketing for all businesses and industries, content marketing involves offering leads useful information in the form of blog posts, whitepapers, podcasts, videos, etc. This information is usually available to all, but you can offer selected information (usually a whitepaper or case study) in exchange for the visitor’s email address or phone number.
  • Email marketing: This is where you nurture your lead (who usually comes from your content marketing) in a slightly more intimate setting — their inbox. Email marketing allows for more personalization and lets you track interest through metrics such as open and click-through rates.
  • Webinars and industry events: Hosting an event, whether online or in person, is a great way to capture MQLs. Depending on the type of event you host, the people and companies who attend are more likely to be ideal customers for your business.
  • Paid advertising: A good paid advertising campaign can help you attract MQLs who are searching for specific solutions online that your product can solve.

Marketing strategies for SQLs

SQL marketing techniques are usually personalized approaches to individual SQLs to encourage them to make a purchase.

Communication between the sales and marketing teams is crucial to SQL marketing since, at this stage, the sales team is engaging the lead. 

Good SQL marketing strategies include:

  • Offering a live demo: A mainstay strategy for a good reason, a live demo is arguably the most effective SQL marketing strategy for getting the lead to take action. It helps you connect the dots for the lead, gets them to visualize using the product, and strengthens your relationship through personal interaction with the salesperson or host.
  • Offering a free trial or free version of your product: Free trials are a great way to convert MQLs by giving them an all-access pass to try the product out for themselves for a limited time. Some companies prefer to offer a free version of their product that has basic features, with more desirable features available only if the lead upgrades to a paid version.
  • Ad retargeting: This involves keeping your brand top-of-mind for your SQL through online advertising on their favorite social media platforms or search engines. 
  • Giving discounts to selected leads: This is not a tactic you want to rely on too often, but sometimes, you meet the perfect ideal SQL: those who are on the cusp of making a purchase and have long-term potential to become valuable customers but are kept back by their hesitation over your pricing.

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How to turn MQLs into SQLs

Now that you’ve learned strategies to attract MQLs and convert SQLs, let’s look at how to bridge the gap and turn your marketing-qualified leads into sales-qualified leads.

While you can’t control how a lead will respond to your efforts, there are a few strategies you can use to turn MQLs into SQLs:

1. Know your audience

Whether you’re in marketing or sales, it’s crucial to understand your audience. When transitioning an MQL to an SQL, you need to be able to read the lead’s level of engagement to determine your next steps.

For example, if someone signs up to receive your email messages, you know you can target them with other marketing efforts. That person has gone beyond cursory interest in your product and has demonstrated that they want to receive more information or promotions. 

However, that doesn’t necessarily mean it’s a good time to send them to your sales team. You need to be able to read a lead’s behavior — and understand what actions people typically take before speaking to the sales team at your company — before targeting them with your sales efforts.  

2. Track the right data

You’re likely tracking various metrics as you work toward turning MQLs into SQLs — but are you tracking the right ones? Data is helpful when determining when to hand a lead over to sales, but only if it provides the answers you really need.

As mentioned above, a lead’s level of engagement with your company’s social media feeds isn’t by itself a good indicator of how likely they are to buy. 

3. Improve your sales process

When you decide that an MQL has become an SQL, the efficiency of your sales process can make or break your success. You need a streamlined process for nurturing leads that breaks down silos and keeps your sales and marketing teams on the same page. 

Have your sales and marketing teams agree on what a sales-ready lead looks like for your company. That way, your marketing team will know what characteristics should be present before they pass a lead over to your sales reps. 

Another great way to improve your sales process is to use a customer relationship management (CRM) platform. CRMs are popular tools that organize a company’s contact information, automate certain sales and marketing tasks, provide a clear picture of your relationships with leads, and make it easy for your entire team to see which steps should be taken next to make more sales.

The best CRM has features like:

Track your SQLs and MQLs using Nutshell

Whenever you’re dealing with a lead—either MQL or SQL—you want to track them carefully to monitor their progress through the funnel. But that can be hard to do without the right tool. That’s why you need a CRM like Nutshell.

Nutshell allows you to automatically import and categorize leads based on various factors, including their status as MQLs or SQLs. Being able to categorize them that way makes your job so much easier.

Of course, you probably don’t want to jump in right away without seeing how our CRM works. That’s why we offer a 14-day free trial of Nutshell for your convenience. Get started today!

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