MQL vs. SQL: What Are They How Do They Help You Sell

Turning prospects into customers is a bit like a relay race. Imagine the marketing team as the first runner. They've sprinted hard, nurturing each lead with care and precision, and now they're holding the baton of customer interest. Next up is the crucial moment: passing the baton to the sales team, set to dash to the finish line, er, close.

This is the thrust of converting marketing qualified leads to sales qualified leads (MQL vs. SQL). If handled poorly, the lead can slip right through your fingers and you lose the deal. That's why it's so important to get the handoff right. Fortunately, knowing the right strategies and a few expert tips will help ensure sales success.

What you'll learn:

What is a marketing qualified lead (MQL)?

An MQL is a lead that has shown interest in your brand and that marketing has deemed likely to become a customer based on preset criteria, like product-need fit and budget. MQLs are like the first stage in a lead's journey towards becoming a customer. They've shown some interest and likely engaged with your marketing content or visited your website a few times. But they're not quite ready to make a purchase. They need more information and guidance before they'll be ready to make a purchase decision.

What is a sales qualified lead (SQL)?

An SQL is a lead that has expressed enough interest in your brand that they're ready to move into your sales process. They've interacted directly with your marketing efforts, indicating they're serious about your product or service, and they're ready to start speaking with your sales team.

MQLs vs. SQLs

MQLs and SQLs represent different stages in a potential customer's decision-making journey. Here's a straightforward breakdown:

• MQL: A lead that shows interest but isn't ready to buy.
• Example: Consider selling CRM software. A first-time visitor who downloads a general guide like "Best CRMs of 2023" is exploring options. They're an MQL, just starting their journey and gathering information.

• SQL: A lead that demonstrates a clear intent to buy.
• Example: If that same visitor frequently returns to the CRM website, engaging with detailed content like "Things to Know Before Purchasing CRM Software," they're evolving into an SQL. This shift indicates a readiness for more in-depth discussions about your product.

Moving MQLs to SQLs - after careful vetting - ensures your sales team focuses their energy on the leads most likely to convert, which is not only more efficient but also respects the pace of the customer's journey. It's all about engaging potential customers with the right message at the right time.

Where does an MQL vs. SQL fall in the sales funnel?

Let's think back to our relay race. Knowing where MQLs and SQLs sit in the sales funnel is crucial, as it guides how you interact with them and move them toward the finish line (aka a successful purchase).

MQLs in the sales funnel

An MQL is located at the top of the funnel, still gathering information and evaluating their options. At this stage, the focus should be on nurturing these leads with educational content like blog posts, reports, or guides; building trust; and gradually increasing their interest in your product or service. This approach ensures that when these leads are ready to move forward, they are well-informed and have a positive perception of your brand.

SQLs in the sales funnel

SQLs are at the bottom of the funnel; they are ready to make a decision. Recognizing a lead as an SQL means your sales team can adopt a more direct approach, providing specific product information like datasheets, whitepapers, comparison guides, or demos tailored to the lead's needs, addressing their concerns and guiding them through to close.

Why knowing the difference between MQLs and SQLs is important

Understanding the distinction between MQLs vs. SQLs is key for optimizing your sales process and approach. When your team can differentiate between someone who's just starting to show interest (an MQL) and someone who's seriously considering a purchase (an SQL), they can tailor their tactics accordingly.

For example, an MQL wouldn't take well to a hard sales pitch, pushing product features and pricing. They don't entirely know what their needs are yet! In all likelihood, an MQL that gets a hard pitch would disappear or go to a more helpful competitor. However, if that same lead gets a follow-up from a marketing rep with more information about their industry and challenges they might be facing, trust is built and interest piqued. Slowly, as the lead understand their needs and how a specific product can help, they become a pitch-ready SQL.

Capturing data is a big part of it. The right insights, gathered in research, tell you what leads need at any given moment. Data also is a key part of tracking what's working and what's not during the sales process so you can fine-tune your strategies.

Tips for converting an MQL to SQL

Research from Gartner shows that just 21% of MQLs convert to SQLs. To improve this conversion rate, marketing teams must improve lead qualification and routing, while sales teams must ensure consistent follow-through on highly qualified leads. Beyond those baselines, there are some key areas of focus to effectively transition a lead from MQL to SQL and improve sales outcomes:

Identify demographics of leads likely to buy

When you look at a lead's demographics, like their job, industry, company size, and role, it helps you understand if they're a good match for what you're selling. This information helps you talk to them in a way that makes sense for their specific needs. For instance, if you know their industry, you can show them how your product has helped similar businesses. Or, if you know the size of their company, you can recommend solutions scaled to their needs.

Track behaviors suggesting deeper interest

To identify when a lead is ready to transition from marketing to sales, watch for actions that indicate a deeper interest. For instance, if a lead frequently visits pricing or detailed product pages, uses interactive features like cost calculators, or engages in in-depth queries about your offerings, these are strong signs they're seriously considering a purchase. Such focused activities suggest the lead is moving beyond initial interest and could be ready for a more direct conversation with the sales team.

Focus on B.A.N.T. (Budget, Authority, Needs, Timelines)

Using B.A.N.T. - budget, authority, needs, timelines - as a framework helps you assess a lead's potential to become an SQL in a more definitive way. Does the lead have the budget for your product? Do they have the authority to make purchasing decisions? Does your product meet their needs? And, what's their timeline for making a decision? These factors are essential in determining the lead's readiness to buy.

Invest in lead-scoring software

Lead scoring assigns numerical values or points to leads based on their interactions with your brand and the likelihood of them making a purchase. It's not just about tracking website visits or email opens. You also give points based on who they are (their job title or company), their actions online (like visiting your website or clicking on emails), and how they interact with your brand on social media (likes, comments, saves, clicks). When a lead earns a certain score, it suggests they're potentially ready for a sales conversation, indicating a closer step to purchase.

The good news is you don't have to keep track of all this manually. There are automated tools that handle lead scoring for you, tallying up points based on your criteria. When a lead reaches a certain score, it suggests they might be ready to have a conversation with your sales team, indicating they're possibly closer to making a purchase. This process helps you focus on the most promising leads, saving time and making your marketing and sales efforts more targeted and effective.

Ready to win: Perfecting the MQL vs. SQL handoff

When converting prospects to customers, the handoff from MQL to SQL is where the race really heats up, and a smooth transition relies on understanding each lead's unique needs. Do your research and lean into data to ensure that each handoff is perfectly timed and personalized so your sales team can carry more sales across the finish line.

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