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Writer's pictureJanna Coleman

MQL vs. SQL: How They Differ

Regardless of how big or small your business is, proper lead nurturing is key to increasing win rates and growing revenue. But in today’s digital age, where buyers have access to widely varying amounts of information and purchasing options, sales and marketing teams need a unified strategy to market to each individual lead effectively. 


MQLs and SQLs offer marketing and sales teams a streamlined way to engage with leads at different points in the sales funnel. And though many businesses use varying strategies to differentiate between the two, it's clear that they both serve a useful and necessary purpose in the sales cycle. 


In this article, we’ll dive into MQLs vs. SQLs, explore options for qualification processes, and outline the necessary organizational structures needed for a streamlined sales process. 


Jump right to: 

What is an SQL?

A sales-qualified lead (SQL) is a prospective customer who has demonstrated an intent to purchase your service or product. SQLs are leads that have already moved through the awareness and education stages of the buyer’s journey and into the consideration stage. 


Typically, an SQL has been vetted by a member of the sales team and meets most or all of the following BANT characteristics: 

  • Budget. The lead has the financial means to purchase the product or service. 

  • Authority. The lead has the decision-making power necessary to authorize the purchase. 

  • Need. The lead has a problem your product or service could solve 

  • Timing. The company or lead can make a purchase within a reasonable time frame.  


There’s no universally approved way to qualify leads, and the process can vary depending on industry, product, or service. However, the BANT method is a common criterion used to determine the sales readiness of a lead and can be an effective starting point.


Next, let’s look at a few examples of activities that may indicate an SQL. 


  1. Demo requests. Prospective customers who request a product or service demo are likely already familiar with your business and are interested in purchasing. 

  2. Contact forms. On average, 90% of the buying process is already completed before a buyer is willing to speak to a sales representative. If a prospect seeks contact with your sales team, they are likely in the consideration phase, and the intent to purchase is high. 

  3. Bottom-funnel content. Prospects who have already been educated on your offerings and are interested in purchasing will likely download or interact with bottom-funnel content such as webinars, case studies, and testimonials or reviews. 


SQLs exist at the bottom of the sales funnel. They’ve received or interacted with marketing content and have expressed interest in the product. For example, consider the process of purchasing a car. Prospective buyers who already know which car they want to buy and are shopping for the best price or specific features would be considered SQLs.  


Tracking SQL metrics is key for sales teams to refine strategies and ensures marketing and conversion tactics are effective. A few common SQL metrics to observe are: 

  • Average deal size

  • Customer acquisition cost

  • Number of qualified leads

  • Close rates 

  • Average sales cycle time 

What is an MQL?

A marketing qualified lead (MQL) is a lead that your marketing team deems likely to become a customer but isn’t ready to purchase yet. Marketing teams can develop buyer personas to help them determine whether or not a lead is a likely potential customer. The criteria for scoring leads usually include demographic data like the prospect’s company size, job title, industry, or other relevant information. 


MQLs are prospects that:  

  • Fit your target demographic

  • Visit your website 

  • Click an advertisement or CTA 

  • Interact on social media 

  • Subscribe to newsletters 


MQLs are just beginning their buyer’s journey and are still in the early interest or consideration phases of the sales funnel. Tracking MQLs helps your marketing team understand where the lead sits in the buyer’s journey and how successful their marketing efforts are at moving them into later stages of the funnel. 


Key MQL metrics to track are: 

  • Number of MQLs

  • Conversion rate to SQLs 

  • Cost per acquisition (CPA)

  • Engagement scores

  • Lead velocity 

  • Click-to-conversion rates 

SQL vs. MQL

You might be wondering why it is so important to differentiate the two. After all, MQLs and SQLs are both leads that are interested in your product or service. While that may be technically true, differentiating between the two is key to offering the right content and properly nurturing them until they’ve purchased. 

Why Does it Matter? 


To help answer this question, Luc Purdy, head of marketing Nimbler’s parent company Inunity, shared his thoughts on the debate: “There’s no one-size-fits-all answer because it depends on the business’ sales cycle, its buyer’s journey, and the organizational resources available.”


Mr. Purdy added, “MQLs help marketing teams identify early interest and focus on what resonates with potential buyers, while clearly defined SQLs enable sales teams to prioritize closing the most qualified leads. Without these distinctions, there’s a risk of wasting resources on unqualified leads, which can impact efficiency and ROI.” 


Think of it this way: If you’ve identified a lead ready to purchase, the content you share with them should be specific to the product they’re interested in rather than generally educating them on a wide array of offerings. This solution can lead to choice overload and decision fatigue, decreasing the chances of closing the sale. 


Conversely, you don’t want to press a lead to purchase if they’ve just begun their buyer’s journey and don’t understand their needs or how your products could provide potential solutions. 


Properly categorizing leads as an MQL or SQL allows you to personalize your outreach to prospective customers, build a trusted relationship, and generally educate them on your services or products. 

Utilizing Data to Differentiate MQLs vs. SQLs


While there aren’t any hard and fast rules around differentiating between MQLs and SQLs, your strategy should rely heavily on customer data. Relying on tracking metrics to qualify leads removes the guesswork. It provides your teams with clear, data-driven insights into customer behavior and allows them to offer relevant content to leads. 


Within the regular metrics your marketing and sales teams are already tracking, you can regularly measure engagement such as: 


  • Content downloads. A good qualifier of MQLs vs. SQLs is the funnel stage content they’ve downloaded or viewed. If the lead views top-of-funnel content, such as podcasts or blogs, they’d likely be qualified as an MQL. 

  • Frequency. Track how often a lead interacts with your brand or views your website and which pages they visit to indicate their position in the buyer’s journey. 

  • Social Media. Monitor customers who regularly interact with your brand on social media through actions such as likes, shares, or comments. 


Along with engagement and behavior metrics, leverage customer data to examine demographics to differentiate leads further. Common demographics to track include job title, geographic location, age, and company size. 

Qualify MQLs and SQLs with Lead Scoring


It can be difficult to identify the point at which an MQL becomes an SQL. A general rule of thumb is that a lead becomes an SQL when they are ready to speak with someone from the sales team. But how do you know exactly when that moment is? Sales and marketing teams must align on a shared strategy to differentiate and transition leads. 


Leveraging engagement metrics and demographics, your marketing and sales teams can implement a lead-scoring strategy to assign numerical values to each lead. Scoring leads based on engagement, behavior, and demographics can help your sales team: 

  • Prioritize leads 

  • Send relevant content

  • Qualify MQLs and SQLs

  • Improve lead handoff

  • Increase win rates


As an added benefit, lead scoring also gives your sales and marketing leaders insights into which strategies are working and how successful they are at finding and closing new customers. Plus, it ensures your reps are having meaningful conversations with prospects. 

Intent and Engagement Qualification


The primary difference between an MQL and an SQL is intent to buy. Intent can be signaled by the engagement (or behaviors) of the lead. 


While an MQL may be interested in your product or service and might engage indirectly with your brand, an SQL is someone who has expressed buying signals and is ready to meet with a sales representative. Essentially, their behaviors suggest that they have an intent to purchase. 


This doesn’t necessarily mean it’s a guaranteed sale, as the SQL could be weighing options or comparing products. But there should be a reasonably clear indication that they intend to make a purchase. 


One key aspect to note is that much of the MQL qualification process happens via software and is generally automated. Your customer relationship management (CRM) tool will ideally track engagement levels, behavior, and demographic data as the lead is nurtured. 


SQLs, on the other hand, are typically qualified on a call with a salesperson. Once they’ve been moved from an MQL to an SQL, the sales rep can further qualify the readiness of the lead by collecting information such as: 

  • Purchasing timeline

  • Size of the potential purchase

  • Prospect’s budget

  • Buying authority

  • Needs and possible solutions 

Aligning Marketing and Sales Teams

Companies with strong marketing and sales alignment are 67% more effective at closing deals. In terms of generating leads and winning sales, the benefits of alignment are undeniable: 

  • Increased conversions

  • Improved collaboration

  • Better win rates

  • Higher customer satisfaction


Let’s look at a few key strategies to ensure sales and marketing alignment within your organization. 

Good Communication Drives Alignment


When aligned with sales goals and outcomes, marketing strategies become more effective at generating qualified leads. And vice versa; alignment results in more effective sales enablement content, clearer ideal customer profiles (ICPs), and better-defined buyer personas. 


Establish live, recurring meetings between both teams to align on strategies, share updates, analyze metrics, and set goals. Meetings can be utilized to determine MQL and SQL qualifications and modify current strategies. Further, establishing a shared line of communication dedicated to alignment keeps both teams regularly informed and creates a dedicated space where teams can share feedback or suggestions and clarify confusion. 


Without communication between your sales and marketing teams, especially in the lead generation and nurturing process, businesses and customers experience: 

  • Missed opportunities

  • Inconsistent messaging

  • Missed revenue opportunities

  • Clumsy lead handoffs 

  • Unreliable metrics 

Shared Goals and Metrics for Success


While it’s crucial to align on strategies and processes, ensuring both teams are working toward shared goals and are relying on the same tracking metrics is equally important.


Setting unified KPIs, milestones, and goals is key to ensuring your strategies work. Shared goals streamline your team’s ability to track results, make adjustments, and build more effective customer acquisition tactics. 


In the case of qualifying leads, aligning goals and metrics provides your teams with the data needed to qualify MQLs and SQLs and decide when to conduct the lead handoff. 

Streamlining Lead Handoff 


Once communication channels, shared goals, and lead qualifications have been established, your sales and marketing teams can decide how to transition leads through the sales funnel. Consider the following five steps as an outline as you build your strategy. 


  1. An MQL is identified. Once a lead has qualified as an MQL, they should be enrolled in personalized lead nurturing campaigns. 

  2. The MQL takes action. As the MQL receives more information and exposure to your brand (downloads more content, watches a webinar, signs up for a newsletter, etc.), further qualifying demographic data can be collected. 

  3. MQL transitions to SQL. When the MQL takes an SQL action (requests a sales call, signs up for a demo, etc.), utilize your CRM to transfer the prospect’s information over to the sales team. 

  4. Sales team contacts SQL. Ideally, the sales team will contact the SQL within 24 hours of the last conversion action to engage with the lead and qualify them as an SQL. 

  5. Further nurturing. If the sales member finds that the lead is not ready for the decision-making stage, the lead should revert to an MQL and continue to be nurtured until further action indicates otherwise. 

Digital Collaboration Tools 


Your CRM is a powerful tool that can assist in lead scoring, task management, data storage, automated lead nurturing, and more. Integrating additional tools can optimize your sales funnel by automating repetitive sales tasks, allowing your team members to focus on person-to-person selling. 


Other key tools that assist in alignment and MQL/SQL qualification are:

  • Pipeline management tools 

  • Engagement tracking tools 

  • Performance management tools 

  • Content management tools 

  • Sales automation platforms 


Certain sales automation tools, such as Nimbler, can streamline your alignment process by unifying customer data, enriching data, automating outreach, and identifying purchasing intent signals. 

Streamline Your Lead Qualification Process with Nimbler 


The primary difference to remember between MQLs and SQLs is their intent to buy. Once a lead expresses or performs an action that indicates they are ready to engage with a sales representative, they become an SQL. 


Distinguishing between MQLs and SQLs can improve the success of your sales and marketing strategies and lead nurturing workflows. 


Utilizing intent and engagement data to perform lead scoring and aligning your sales and marketing teams are the best ways to increase MQL-to-SQL conversions. And finally, taking advantage of powerful digital tools to enrich your existing data, personalize your outreach strategies, and automate lead nurturing will ensure no missed opportunities. 


Nimbler is an all-in-one sales automation platform that can revolutionize your business’ current sales approach. It offers sales and marketing teams the tools they need to convert leads into paying customers.


Try Nimbler for free today and start building your pipeline of MQLs and SQLs.

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