MQL vs SQL: What’s The Difference and Tips on Increasing Your Conversion Rates

Every SaaS business wants qualified leads. But what should you do once you have them? That’s where you need to understand the difference between MQL vs SQL.

They are both leads, but really understanding the nuances can help you scale your product growth efficiently.

In this article, we’ll go over our best tips on how to better qualify your leads and optimize your marketing and sales strategy. Let’s dive in!

What is a marketing qualified lead (MQL)?

Marketing qualified leads (MQL) are essentially site visitors who are likely to become customers. In other words, an MQL fits your buyer persona and thus, is a prospective customer.

However, MQLs are situated at the top of your sales funnel. So they are still not ready for direct attention from your sales team.

What is a sales qualified lead (SQL)?

The sales qualified lead (SQL) is a prospect your sales team has identified as being worth pursuing. The next stage in the sales process for SQLs is a direct sales push.

SQL contacts are situated near the bottom of the sales funnel. So they have an intent to buy and meet the necessary criteria that make them a good fit for your product or service.

MQL vs SQL: What’s the difference?

An MQL is a lead situated near the top of the sales funnel. But they lack the intent to buy, so you require more effort from the marketing team before the sales team can push them for a direct sales offer.

An SQL, on the other hand, is already in the buying cycle and ready for a direct sales offer. Both the sales and marketing teams have deemed them to be potential buyers. As a result, they should be your priority when managing leads.

The hidden metric: Product qualified leads (PQLs)

If you run a SaaS company, MQLs and SQLs might not be enough. You should be looking for PQLs.

A Product Qualified Lead (PQL) is someone who has experienced value from your product through a free trial or freemium model. They may have used the software and reached an “Aha!” moment, realizing the product helps them solve their pain points.

PQLs often convert at a much higher rate than MQLs because they already understand the value. If you are tracking product usage metrics, you can identify these users easily. For example, in a project management tool, a PQL might be a user who created a project and assigned tasks to three other people.

How do you differentiate between MQL and SQL?

There is a significant gap between the MQL vs SQL designations. Studies show that less than 10% of MQL ever convert to SQL, which happens because many SQLs get classified as MQL too early.

Here are four factors that you should look out for when differentiating between MQL and SQL:

• Lead behavior
• Lead score
• Types of conversion
• Referral channel

Lead behavior

Lead behavior includes how visitors behave on your website and how they engage with your team. Users who visit your website repeatedly and browse through your products are interested in your company.

So, you can categorize them as MQLs and SQLs depending on the pages they visit, how long they spend on the site, and how often they return.

Lead score

Lead scoring is a widely used method for differentiating between MQL and SQL. Before lead scoring was implemented, sales teams relied on gut feelings to determine MQL vs SQL designations. But using memory or feelings is an ineffective way to evaluate sales opportunities.

Lead scoring relies on data from both sales and marketing teams to assign weights to each action a visitor takes. As a result, you get quantified leads that can help you assign better MQL vs SQL designations. Marketing and sales teams need to figure out a lead score threshold that will move a lead to the next stage of the funnel.

Type of conversion

Conversions can be categorized just like leads. For example, someone who downloaded a free eBook would be an MQL. On the other hand, someone who requested a free demo of your product would be an SQL.

The general rule of thumb is that the more effort a contact puts into interacting with your campaign, website, and product, the more likely they will be classified as SQL.

Referral channel

Most Saas businesses have multiple channels to acquire leads. But you might notice that the majority of the leads come from a select few, like email and paid marketing. Over time, you’ll be able to identify the more effective channels with a high lead conversion count.

Since all engagements with clients are opportunities to make sales, leads that come through such referral channels will naturally get priority. As a result, you can differentiate MQLs and SQLs from their referral channel.

Practical tips for lead qualification (with Userpilot)

I mentioned earlier that product signals are often stronger than marketing signals. Here is how I use Userpilot to identify high-quality leads based on what they actually do in the product.

1. Track feature engagement

Not all features are equal. Some features indicate a user is getting deep value. I use tracked events to monitor these “power actions.” For example, if you sell project management software, creating a project is good. Integrating with Jira is better. The integration suggests they are embedding your tool into their workflow. This way, you can easily recognize qualifying leads.

2. Segment your users

You cannot treat all users the same. I create user segments based on behavior. I might create a segment called “Highly Engaged Free Users.” The criteria could be:

• Started the onboarding
• Engaged with the checklist
• Used a key feature at least 5 times.

This segment represents sales-ready leads.

3. Ask them directly

Sometimes the best way to know if someone is ready to buy is a direct conversation. I use microsurveys during onboarding to collect qualitative data. You can ask: “What are you looking to achieve with our tool?” If they select “Just browsing,” nurture them. If they select “Evaluating for a purchase,” fast-track them to sales.

4. Visualize user path

Use funnels to see where users drop off. If you see a lot of MQLs entering the product but failing to reach the activation point, you have an onboarding problem, not a sales problem. You can fix this with interactive flows that guide users to value. When you fix the leaky bucket, you deliver more qualified leads to sales.

How to transition MQLs to SQLs and increase MQL to SQL conversion rate?

A company’s MQL to SQL conversion rate is directly related to its close rates. So any company would be looking for ways to increase their MQL to SQL conversion count. But how exactly can they do this?

Here are some tips for anyone looking to convert more MQLs into SQLs:

• Determine the reasons for the low MQL/SQL conversion rate
• Send personalized lead nurturing emails
• Equip your sales team with success stories
• Collect feedback from your existing clients

Now let’s take a deeper look at these suggestions.

Define your Ideal Customer Profile (ICP)

You cannot qualify a lead if you don’t know what a good customer looks like. You need to filter based on firmographic data: company size, industry, role, and budget.

If a student downloads your guide, they are an MQL based on behavior, but they will never be an SQL because they have no budget. You can automate this filtering using customer segmentation tools. By setting up exclusion lists, you ensure your sales team never sees leads that don’t match your ICP.

Determine the reasons for the low MQL/SQL conversion rate

To improve your MQL to SQL conversion rate, you will first need to identify the reasons behind the low lead conversion count. Start by asking yourself the following questions:

• Why are your MQLs not converting?
• What do you think is preventing your MQLs from purchasing your product?
• Does it have to do with your service/product, price, or the quality of leads?

A good place to start is looking into why your MQLs fail to generate sales. There might be a problem with the way your marketing and sales departments classify MQLs and SQLs. Whatever the case, you can expect higher lead conversions once you make the necessary improvements.

Next, you should look at the obstacles that prevent customers from purchasing the product. Are you targeting the right audience? Is the pricing too high? Are there issues in your product/service that you may have overlooked?

Make sure you check for these issues from time to time to understand where the problem lies.

Set up in-app content that walks the user through the buyer’s journey

For tools with a free trial or freemium version, in-app messaging plays a crucial role in converting MQLs to SQLs.

Set up a detailed onboarding flow optimized for each user persona and their JTBDs. Apart from the initial walkthrough, it’s worth setting up a resource center so that the user has constant access to educational content, as well as triggering nudges that would get the user back on track or show them more advanced features. The goal of such a flow is to walk the user from sign-up to activation, and finally to the purchase.

Userpilot, for example, lets you set up onboarding flows made of multiple interactive elements, such as modals, tooltips, or slideouts, hyper-targeted to each user thanks to segmentation and trigger settings.

Send personalized lead nurturing emails

Personalized lead nurturing campaigns can help you manipulate buyer behavior. Email marketing campaigns usually have a high impact on potential customers, and they are easy to automate.

Email automation allows marketing teams to schedule various high-impact campaigns for potential customers. These include welcome, educational, promotional, and renewal campaigns. Based on user interaction, new subscribers will automatically receive these emails from time to time.

The most significant advantage of lead nurturing emails is that they offer personalized content. When a company notifies leads about offers and giveaways, they feel like the company is invested in them.

As a result, they are more likely to trust them and make a purchase. In fact, stats show that companies that automate lead management see more than a 10% increase in revenue in the first 6-9 months.

Userpilot lets you send emails to specific user segments and automate triggers, so you can set up automated, targeted email marketing campaigns and walk your users through the whole sales cycle.

Equip your sales teams with success stories

When your prospects are down to their last few options, and you are one of the options they are considering, you can get their opinions in your favor by showing off the success stories of your existing customers.

Your marketing team is probably already talking about these stories in their campaigns, but your sales team must have full access to them and use them. That way, prospects will feel more assured about choosing your product or service over your competitors.

Collect feedback from your existing clients

Effective feedback is perhaps the most valuable resource for growth. So it is a good idea to get feedback from your existing clients on why they chose your product and whether they would recommend it to others.

One of the most effective ways to get feedback is through NPS (Net Promoter Score) micro-surveys. NPS surveys use a 1-10 scale to determine a customer’s loyalty to a product or service.

A score of 9-10 indicates that the customer is a “promoter”, i.e., someone who’s likely to spread positive word-of-mouth and refer your product to others. 7-8 is for “passive” customers, who’d stop at using your product – nothing more, nothing less.

Finally, 0-6 indicates “detractors” or dissatisfied customers who may even discourage others from using your product.

Using Userpilot, you can better understand user behavior analysis and boost in-app engagement through onboarding experiences and quantifying user sentiment, which includes NSP micro-surveys. In fact, with Userpilot’s new mobile capabilities, customers can now trigger their existing & new NPS surveys directly on their mobile devices, effortlessly gathering these valuable user insights on-the-go.

You can use the data you collect from Userpilot to segment your target audience and launch follow-up experiences to address the issues within your product. Eventually, this simplifies feedback collection by miles.

How to arrange the lead handoff process between marketing and sales?

A great handoff that assures alignment of sales and marketing efforts requires a standardized system. Here’s a quick list of steps you should perform:

1. Implement functional lead scoring

As I mentioned, lead scoring helps eliminate the guessing game from the lead qualification process. However, you first need to decide how to assign points based on the customers’ attributes or behavior. For SaaS companies, the following custom scoring models work best to determine lead quality:

Demographic Scoring: Does the lead match your ICP?

• Job title.
• Company size.
• Industry.

Behavioral Scoring: What have they done?

• Visited the pricing page.
• Opened an email.
• Downloaded an ebook.
• Requested a demo.

You can use tools to track these interactions and perform behavior analytics. For example, Userpilot helps you track product usage analytics to see if a user is engaging with your core features, which is a massive signal of intent.

2. Integrate with CRM (Customer Relationship Management) tools

You cannot manage this process with spreadsheets. You need a tech stack that talks to each other. Your marketing automation, CRM, and product adoption platform need to be in sync.

For example, you can integrate Userpilot with your CRM. With the HubSpot integration or Salesforce integration, you can push product usage data directly into the tools your sales team lives in.

Imagine a sales rep seeing a contact in Salesforce. Instead of just seeing “Downloaded Ebook,” they see “Downloaded Ebook, Logged in 5 times, Invited 2 teammates, Triggered ‘Export Report’ event.” That rep has a clear confirmation of the user’s true purchase intent and knows exactly what to say on the call.

3. Trigger the transition automatically

Do not rely on manual reviews. Set a threshold score. Once a lead hits 100 points, they automatically become an SQL and get routed to a sales rep or into an automated high-intent email onboarding sequence.

This ensures speed. Research shows that responding to a lead within five minutes increases conversion rates significantly compared to waiting 30 minutes.

Improve lead qualification and boost marketing and sales efforts with Userpilot

Understanding the differences between MQL vs SQL is crucial to your marketing and sales strategies and steady revenue growth.

Using lead intelligence and lead scoring to gauge the lead’s sales readiness will allow you to personalize your sales and marketing strategies. So we highly recommend you utilize the proper tools when making MQL vs SQL designations.

Need help with understanding user behavior and analyzing customer feedback? Get a Userpilot Demo and chat with one of our product specialists!