MQL vs. SQL: What is the Difference?

by Susan Perez in Conversion Optimization

Every sales and marketing team focuses on lead generation and ways to bring highly qualified leads into their funnel.

Whether lead generation comes from inbound or outbound marketing, ad campaigns, landing pages, or social media, it’s important to have a unified marketing strategy and understand the differences between MQLs (Marketing Qualified Leads) and SQLs (Sales Qualified Leads).

What is an MQL?

An MQL, or Marketing Qualified Lead, is a potential customer who has interacted with your marketing content (i.e., visited your website, downloaded product information, etc.) and is likely to become a paying customer.

Different marketing teams may have different ways of identifying an MQL, but commonly a marketing qualified lead is qualified as such based on the following factors:

Web pages visited or the number of times a web page was visited
Content offers downloaded
CTAs clicked
Social media interactions
Demographic information
Whether or not they match a buyer persona
Fit the right profile, but are not quite ready to buy

Once a lead is determined to be an MQL, their information is then passed on to the sales team to further engage that lead and (hopefully) convert them to a customer.

A mattress company probably wouldn’t classify a lead as an MQL if they were a first-time visitor to the company’s website and read a blog called “Best Mattresses for Side Sleepers”. However, someone who is a repeat visitor to the website follows the company on social media, and has downloaded an eBook titled “How to Know When It’s Time to Purchase a New Mattress” can be deemed an MQL.

What is an SQL?

An SQL, or Sales Qualified Lead, is a lead who is highly likely to convert into a customer and is qualified by the sales team versus the marketing team.

Again, what qualifies an an SQL differs from sales team to sales team, but generally SQLs meet the following criteria:

Having a need for the product or service
Expressing interest in the company or its offerings
Repeatedly visiting the website, downloading content, and engaging on social media
Possessing the budget to make a purchase
Having the authority to make buying decisions
Operating on a timeline that aligns with the company’s sales cycle

SQLs are typically vetted and ready to talk to somebody in sales. An MQL will not become classified as an SQL if they are not showing interest in speaking to the sales department.

The MQL for the mattress company in our example above may be classified as an SQL once they download even more content, likely bottom-of-the-funnel content that shows they are serious about making a purchase. This could be content like “5 Mattresses That Fit Your Budget” or “Your Mattress-Purchasing Checklist: Everything to Know Before You Buy”.

When visitors have already made a decision to purchase a product or service like yours, they are likely to download bottom-of-funnel content or click on CTAs that will help them engage with a sales department.

SQL vs. MQL

So, is it actually important to know the difference between an MQL and SQL? Yes, it is, because it all comes down to buyer intent and if you can distinguish between a lead’s intention, then you can nurture them properly and increase your chances of closing a sale. Classifying a lead correctly can have a significant impact on your sales funnel.

The lead nurturing process will vary for an MQL versus an SQL. You will serve up different content at different times, depending on where the lead is in the marketing funnel.

Serving the right content can increase your chance of converting the lead into a customer faster. Not only will correct lead categorization help your pipeline, but it also makes marketing and sales teams more efficient because they won’t be wasting resources on creating nurturing campaigns that are irrelevant.

The chart below explains how you can go about categorizing your leads.

Use it to tighten up your sales and marketing processes and increase your ROAS.

Aspect	SQL (Sales Qualified Lead)	MQL (Marketing Qualified Lead)
Definition	Ready for direct sales contact	Potential interest identified by marketing
Buying stage	Late stage; close to purchase	Early stage; needs nurturing
Intent to buy	High	Low to moderate
Handled by	Sales team	Marketing team
Next steps	Sales calls, demos, negotiations	Content marketing, email campaigns
Lead score	Higher	Lower
Main focus	Closing the deal	Nurturing and educating

When to transition a lead from MQL to SQL?

The marketing to sales handoff is a critical part of the process. Transitioning a lead from MQL to SQL correctly ensures that the most qualified leads are handed off to the sales team, increasing the likelihood of a conversion.

Marketing and sales teams should be aligned on what they define as an MQL and an SQL to maximize efficiency and effectiveness.
The following set of criteria should be evaluated when transitioning a lead from MQL to SQL:

Engagement level

Engagement level refers to how actively a lead interacts with your content and marketing efforts. High engagement levels typically indicate a strong interest in your product or service. Metrics to consider include:

Email open and click-through rates
Downloads of gated content like whitepapers and eBooks
Participation in webinars and events
Social media engagement

Monitoring these interactions and aligning on their importance helps identify leads who are more likely to move further down the sales funnel.

Firmographics

Firmographics are the attributes that define the characteristics of a company or organization. These include:

Industry
Company size
Revenue
Location

Understanding these attributes helps ensure the lead aligns with your ideal customer profile and helps keep your focus away from profiles that would not be worth your time. If your target audience is a mid-size tech firm, then an SMB or enterprise business should not be prioritized as a qualified lead.

Behavioral indicators

How can a sales or marketing team be sure that a lead has intent to buy? Paying close attention to behavioral indicators will help as they can suggest whether or not a lead is ready to make a purchase. These can include:

Visiting pricing pages
Requesting product demos
Viewing case studies
Repeated visits to the website
Clicking a “Chat with sales” CTA

These behaviors indicate a higher level of interest and intent, suggesting that the lead is ready for a more in-depth conversation with the sales team.

Lead score threshold

Lead scoring assigns numerical values to various actions and characteristics of a lead. When a lead’s score reaches a certain threshold, they can be considered ready to transition to an SQL. Factors contributing to lead scores include:

Demographic information
Engagement level
Behavioral indicators
Past interactions with the company

Establishing a clear lead score threshold helps automate the transition process, ensuring no promising lead is overlooked and no under-qualified lead is handed off.

Steps to transition a lead from MQL to SQL?

To make a smooth transition from MQL to SQL, follow strategic steps to refine the lead nurturing process and ensure that the only leads that are passed off to the sales team are those that are most likely to convert.

Lead scoring

Lead scoring is a systematic approach to evaluating leads based on their behavior and characteristics. With lead scoring, a marketing and sales team would need to align on specific actions that indicate intent to buy and how much weight to assign to each of those actions.
For instance, points would be assigned for:

Website visits
Content downloads
Event participation

By accumulating points, leads are ranked based on their likelihood to convert. Leads that fall within a predetermined scoring range will then be prioritized and handed off to sales for further engagement.

Define clear criteria

This can’t be overstated: it is incredibly important to establish clear criteria for what constitutes an MQL and an SQL. Doing so ensures that marketing and sales teams are working optimally and efficiently as one. The criteria includes:

Engagement metrics
Firmographic data
Behavioral indicators
Lead score thresholds

Having clear criteria ensures consistency and objectivity in the lead qualification process.

Align sales and marketing teams

As we have stated, sales and marketing alignment is crucial for a seamless transition. Without regular communication and collaboration, there will be inevitable bottlenecks and lower conversion rates. Teams must continually work together to:

Define and refine qualification criteria
Share insights, feedback, and metrics
Ensure both teams are working towards common goals

Alignment helps in understanding the quality and readiness of leads, reducing friction, and enhancing efficiency.

Monitor lead behavior

Continuous monitoring of lead behavior is necessary to identify when a lead is ready to be transitioned. CRM tools, marketing automation platforms, and data analytics tools can help track:

Website interactions
Form fills
CTA buttons clicked
Downloaded content
Email engagement
Social media activity

Monitoring helps you identify signs of increased interest and intent and makes it more likely for sales teams to go after leads who are ready to take action.

Nurture leads

Especially after a lead is qualified as an MQL, nurturing remains critical to ensure the lead not only stays in the funnel but continues to move through it in an effective way. This involves:

Sending targeted content
Engaging through personalized emails
Providing valuable information
Demonstrating the product at the right time
Providing the right support for leads who have questions

Nurturing helps in maintaining engagement and moving leads closer to a purchasing decision.

Feedback loop

A feedback loop between sales and marketing teams makes the lead generation and nurturing process stronger, more effective, and more precise. A consistent feedback loop involves:

Sales providing feedback on lead quality
Marketing adjusting strategies based on feedback
Regular meetings to discuss outcomes and insights

Feedback helps in refining the qualification process and improving lead quality over time.

Example: transitioning a lead in a B2B SaaS company

Consider a B2B SaaS company offering project management software. Here’s how they might transition a lead from MQL to SQL:

Lead scoring: A lead signs up for a free eBook on project management best practices, earning them 10 points based on a predetermined scoring system. They then sign up for and attend a webinar, adding another 20 points.
Criteria definition: The marketing and sales teams have defined that a lead with over 50 points, who has also visited the pricing page, qualifies as an SQL.
Monitoring behavior: The lead visits the pricing page twice and requests a demo, signaling high interest.
Nurturing: While the lead is engaging, they receive personalized emails with case studies and user testimonials.
Transition: The lead’s score reaches 60, and they are handed off to the sales team with detailed notes on their interactions and interests.
Feedback loop: Sales provides feedback that the lead was highly engaged and prepared for a purchasing discussion, helping marketing refine their future lead nurturing strategies.

By following these steps, companies can ensure a smooth and effective transition from MQL to SQL, maximizing the potential for successful sales conversions.

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