Let’s say you run a linens brand (like Brooklinen) and want to sell to major hotel chains. You go after potential clients with targeted marketing campaigns and nurture leads by providing valuable information about your sheets, pillowcases, and duvets.
This work brings in many leads, but they vary widely in their profile and likelihood to convert. Your marketing team is able to identify leads who show promise (these are called “marketing qualified leads” or MQLs), but they may not be ready to buy. Your sales team works to further vet these leads, transforming the most promising MQLs into sales qualified leads (SQLs) who are primed for a sales push.
Understanding the difference between these groups can help you focus on the right prospects at the right time with the goal of increasing conversion rates—and revenue. Here’s how marketing qualified and sales qualified leads differ and the factors to consider when transitioning a lead from one stage to the next.
What is a marketing qualified lead (MQL)?
A marketing qualified lead (MQL) is a prospective customer who has engaged with your marketing efforts and seems to have an interest in your product. How do you know they’re interested? MQLs reveal their interest by clicking your ads, downloading content, attending webinars, or, at the very least, repeatedly visiting your website. Despite all this, they still need to be vetted by your sales team to determine their readiness to purchase.
What is a sales qualified lead (SQL)?
A sales qualified lead (SQL) is a prospect who has been vetted by the sales team and is deemed ready for direct sales engagement. SQLs start as MQLs identified by the marketing team, but they are then further evaluated by sales.
SQLs meet specific criteria: having a defined need for your product or service, possessing the budget and authority to make a purchase decision, and demonstrating urgency. SQLs show strong buying signals, like repeatedly viewing pricing pages, downloading case studies and white papers, or filling out a contact form indicating their budget range. While they haven’t yet spoken to a sales rep, their digital behavior suggests they’re ready for a conversation.
MQL vs. SQL: What’s the difference?
Clearly defining MQLs and SQLs helps streamline the handoff between marketing and sales teams. When aligned, marketing generates a broad pool of qualified leads, from which sales identifies and further qualifies those showing high interest, budget authority, and clear need. When misaligned, resources are wasted pursuing lukewarm prospects, and high-potential leads may be overlooked, leading to missed opportunities and low conversion rates.
Here are the key differences between MQLs and SQLs:
Lead score
Marketing teams and sales teams use lead scoring to assign numerical values to prospects based on their behaviors and characteristics. A predefined score threshold typically separates MQLs and SQLs. MQLs have lower lead scores, indicating they’ve shown interest but need further nurturing. SQLs, on the other hand, have higher lead scores, reflecting stronger buying signals like multiple high-value interactions and alignment with your ideal customer profile.
Sales readiness
MQLs have shown interest in your brand by engaging with your content or attending events. But their level of engagement may not necessarily indicate a readiness to buy. By contrast, SQLs meet specific criteria for sales-readiness, like inquiring about pricing or requesting a free trial or demo.
Funnel stage
MQLs represent the top of the marketing funnel, where prospects are just starting to learn about your brand and its offerings; their buying intent may not be clear or immediate. SQLs are closer to the bottom of the funnel and are more likely to convert into customers; they’ve expressed a clear intent to make a purchase in the near future. They have a well-defined need and are actively seeking a solution.
5 factors that move a lead from MQL to SQL
Deciding when to transition a lead from MQL to SQL can impact the success of your sales efforts. Too early and you risk alienating potential customers with overly aggressive sales tactics; too late and you may miss the opportunity to convert a lead while their interest in your product or service is at its highest.
Here are five factors to consider when determining whether a lead should be moved from marketing to sales:
1. Behavioral indicators
Look at lead behavior like website visits, content downloads, and online event attendance—anything that shows your prospect has an interest in your product. Identify patterns that indicate a higher level of engagement, like repeated visits to pricing pages or requests for product demos, which can signal a lead is ready to move to SQL status.
If a lead has requested a product demo and visited the pricing page multiple times, it’s high time they receive some outreach from the sales team. However, if the lead has only subscribed to the monthly newsletter and viewed a few product pages, they can probably remain in the nurturing stage.
2. Demographic fit
Assess whether the lead fits your ideal customer profile based on demographic factors like company size, industry, and job title. Prioritize leads that align with your target audience, as they’re more likely to be receptive to your sales efforts.
For a B2B furniture company specializing in stylish office design, a lead that fits their ideal customer profile might be, say, a facilities manager at a medium-sized fashion retailer. If the lead is looking to renovate their corporate headquarters and create a modern, collaborative workspace, they’re almost certainly a fit.
On the other hand, a local government office looking to update their employee workspaces might not align with the ideal customer profile. Despite having a genuine need for new furniture, the government office’s limited budget and more complex procurement guidelines might make the sales cycle longer, taking away attention from more suitable (and lucrative) corporate clients.
3. Lead score threshold
You can use lead scoring systems to monitor your potential buyers’ digital footprints. This means you assign value to actions leads take on your website, like watching a product demo video or crunching the numbers on your site’s ROI calculator. As these interactions accumulate, the lead’s score rises, pushing them from “window shopping” to “ready to talk.” The tipping point—when a lead goes from an MQL to SQL—is the green light for your sales teams to start a conversation.
Establish your threshold based on a combination of behavioral and demographic factors, as well as historical data on successful conversions. You can automate this process using software with lead-scoring features like Marketo, HubSpot, or Salesforce.
Once you’ve done this, route leads that reach the threshold to the sales team for follow-up. For example, you might transition a lead from marketing to sales under one of these hypothetical lead score thresholds:
- A combination of website visits, content downloads, industry event attendance, and expressed interest in a free trial.
- A mix of engagement with marketing emails, multiple visits to pricing pages, and a job title indicating decision-making authority.
- A blend of product demo requests, engagement with social proof, and an ideal customer profile match.
4. Lead response time
Pay super close attention to the lead’s responsiveness to your marketing efforts. If a lead fills out a “Contact us” form after reading a blog post or registers for a webinar mentioned in an email campaign, you can be pretty sure they’re ready to engage with sales. Leads who are unresponsive or slow to engage may require additional nurturing before you transition them to SQL status.
5. Sales team capacity
A lead’s willingness to buy doesn’t mean much if your sales representatives don’t have the capacity to sell. If your team is constantly overwhelmed with qualified leads, it might be time to expand your team. Conversely, if your sales team is wasting time on leads that don’t convert, tighten your SQL criteria. This approach keeps sales reps zeroed in on high-potential prospects, boosting both deal closure rates and revenue.
MQL vs. SQL FAQ
What is an example of MQL?
An MQL may be a prospect who downloads a whitepaper from your website and subscribes to your email newsletter.
How do you determine MQLs and SQLs?
You determine MQLs and SQLs using specific benchmarks that match your company’s goals, ideal customers, and sales process. Every business’s approach to this will be slightly different, but consider focusing on behavioral indicators and lead response time for a start.
What comes first, MQLs or SQLs?
MQLs come first in the sales process, as they represent leads that have shown initial interest but require further qualification before being passed to the sales team as SQLs.
