on January 24, 2023 • 23 minute read
If you’re among the folks who rely on your marketing team to generate demand by providing your sales teams with marketing qualified leads (MQLs), your first step should be defining what you consider an MQL.
This task isn’t simple, though, since there are a lot of elements you might want to include in your marketing qualified lead definition — from demographic and firmographic data to intent and urgency measurements.
Then, you need to think about whether to develop a scoring system (or not), figure out how to get buy-in from your marketing, sales and executive teams that you got the definition right, figure out how often you should revisit your definition, and more.
So, if you’re struggling to define MQLs and set up your process of handing over leads to your sales team, this guide will give you some answers. We asked over 40 professionals how they define and handle marketing qualified leads— read on to get practical, first-hand advice from experts like Kamil Rextin, Peter Caputa, Karien Pype and others.
There’s been some controversy about whether or not MQLs are dead or not. Drift has argued that because prospects don’t fit into neat buckets, that accounts (and not leads) buy, that MQL definitions need to be updated to maintain close rates and because some leads are ready to talk to sales right away, that MQLs are dead. Lots of other marketers have taken this stance and ran with it.
However, according to the 46 people we surveyed, over 82% of them said MQLs are alive and well. 39.13% of our respondents are agencies or consultants in the marketing, digital, or media space, 36.96% are B2B companies, 21.74% are B2C companies and 2.17% are ecommerce businesses.
Wondering why this might be the case? According to Jack O’Carroll of Honest SEO, marketing qualified leads are evolving rather than being dead.
“MQLs were created to help make marketing more efficient, but now they are being used to find the best leads,” says O’Carroll.
“Leads that have the most potential for conversion are now being prioritized [by sales]. This is because it is important to spend time and resources on leads that have the best chance of converting instead of wasting time on leads that will not convert”.
Kamil Rextin, general manager of 42 Agency, believes that not only MQLs are not dead, but they’re critical in longer sales cycles.
“I think MQLS are a leading indicator, especially in a longer sales cycle. It’s very hard to connect marketing to revenue if your sales cycle is 6-12-18 months long and you have multiple stakeholders. So, an MQL is basically defining a ‘qualified buyer’ who may or may not end up closing, so you have an earlier sign for whether your marketing is working or not.” explains Rextin.
Ok, so now that we have that settled, let’s talk about how to do this right…
Lead scoring systems help marketing and sales teams determine whether a lead is worth their time.
There are two main ways to score leads: using explicit and/or implicit information. Explicit information is the information that leads share with you directly, usually on forms on your website. Implicit information is information you glean from tracking leads, such as what pages they viewed on your website.
When defining your MQLs, it’s important to use both explicit and implicit data.
52.17% of our survey respondents combine both explicit and implicit data to score leads.
Next, it’s important to involve everyone when defining your marketing qualified leads.
When it comes to the ways companies built their scoring systems, half of the respondents stated that marketing mapped everything out, then worked together with sales on assigning values, and finally, got the approval from executives.
Short version: get everyone on board with your MQL definition.
Lastly, use negative values to disqualify bad leads.
More than half of the respondents apply negative values in their scoring system. This allows them to eliminate low-quality leads who, for example, leave invalid phone numbers or non-existing email addresses, so the sales team doesn’t waste their time on them.
Karien Pype, VP of Marketing at ONTOFORCE, shares what factors you should consider when scoring leads: “Based upon the (high) intent they show, combined with their demographics,” Pype highlights as the starting point. However, young companies can be less restrictive in scoring their leads as it’s important to get as many as possible when you’re at the beginning.
“You still need to learn and fine tune messaging while you gain PMF. The more mature the organisation, the more criteria you include in your scoring. In any case, at any stage, it’s an ongoing exercise that marketing and sales jointly need to review and improve – based upon quantitative feedback (conversion rates all the way down to the bottom of the funnel) as well as qualitative feedback from the sales.”
VP of Marketing at ONTOFORCE
A strong scoring system helps you convert leads faster and ensure they’re the right fit for your company. If you evaluate your leads correctly, you can speed up your sales cycle and have more time to bring in more clients.
Samuel McGraw of DesignHub shares that his team aims to close deals within a month, but their sales cycle can vary depending on the project and the client. McGraw shares what their entire sales process look like, from identifying a potential client to evaluating the lead and starting the project:
“The first step of our sales cycle is identifying potential clients, which we do through online research, cold-calling, networking, attending trade shows and conferences, and building our brand presence through digital marketing,” explains McGraw.
“Once we identify a potential client, we evaluate their needs and develop a pitch accordingly. We provide potential clients with insights into our process, portfolio, and client testimonials. Depending on the project, the client can provide us with a formal RFP or a detailed project brief. We then submit a proposal that outlines our project process and timeline, as well as our fees and payment structure.
We also provide a detailed project timeline and manage the client expectations throughout the process. After the proposal is accepted, we usually begin the project with a kick-off call or meeting. During the project, we stay in constant communication with the client, providing regular updates and feedback. Once the project is completed, the client is presented with a final deliverable that meets their expectations and goals,” concludes DesignHub’s Samuel McGraw.
PRO TIP: In this episode of Metrics and Chill, Mark Thomas, Head of Growth at Powered by Search, walked us through how they drove the strategy that led to an increase in SQLs by 142% quarter-over-quarter. Hint: the turning point was improving their lead qualification process.
Some of the biggest mistakes companies make is to assume that they don’t need to review their MQL definition or that any generated lead is a marketing qualified lead. Defining your MQLs properly takes time and requires a personalized approach rather than adopting another company’s definition just because it’s working for them.
The importance of properly defining a marketing qualified lead is also reflected in a data point from our survey – when we asked companies about their MQL to SQL Conversion Rate, the answers varied significantly — from 2% to 70%. Our assumption is that the values are so different due to companies having many differently defined MQLs and lead-scoring systems in place. Also, for more than 50% of the companies we surveyed, the definition itself is susceptible to change from quarter to quarter (or even more often).
Here are some examples of how companies define their MQLs:
“We use a really in-depth customer journey mapping process to help us define our MQLs. I work with my marketing team to create visual heat maps that show all the points that someone interacts with our brand. Those consumers that have multiple points are used to build our customer personas, and then we try to match those personas with our prospecting,” says Brian Clark of United Medical Education.
In most cases, these reviews will help you generate higher-quality leads for your sales team. Deirdre Scully of Teamwork is currently reworking her team’s MQL definition to eliminate “passive free trial users” and correlate better with purchase intent.
“Currently, our definition includes firmographic (company size) and demographic (location, business email address) criteria and they must also be on a free trial. We have iterated on this in partnership with Sales, mostly on location criteria based on ability to convert,” says Scully and adds that this definition has its shortcomings.
The challenge with this, as a definition, is [that] it doesn’t have a close correlation with intent, wasn’t really fit for routing ICP leads to Sales, and only delivers one type of lead (trial users). We are in process of changing our definition to include demographic, firmographic but also behavioral criteria (such as downloading a piece of content, attending a webinar) and product-related actions (we have different layers of PQLs). We’ll be doing this with Sales, Marketing and Product.
This will be V1. It can get very complicated very quickly and will be a work in progress, continually optimizing so that both Sales and marketing are bought in. We’ll also continue to have auto MQLs such as hand raisers from our ICP,” shares Teamwork’s senior demand generation manager.
And what happens after the MQL is generated? According to our research, most companies keep on nurturing the lead with marketing, while 36.96% pass them to sales immediately.
Our recent collaboration with the team from 42 Agency generated an insightful conversation with valuable advice from experienced marketing professionals. One of the discussion points was: how does your company define marketing qualified leads? Here are some hot takes from the discussion:
Nooruddin Abbas Ali of Sell my SaaS shared an interesting point of view: true MQLs aren’t only informed of the product or service’s value, but they’re educated about it.
“For me, the definition of an MQL is a lead that has been educated (not just informed) about the value that the product/service offers and the pain points it resolves. It’s the sale’s job to go over all the how’s, when’s, where’s, and why’s. It’s our job to know the whom and establish the what,” says Abbas Ali.
“Let’s look at the following examples:
Conversion Pathway of Lead X:
LinkedIn Ad (Non-Retargeting) –> Lead Magnet Page (eBook, calculator, freebies) –> Form Filled
This is NOT an MQL. The lead has not been educated enough about the brand, product/service, and the value it offers.
Conversion Pathway of Lead Y:
LinkedIn Ad (Non-Retargeting) –> Lead Magnet Download Page –> Form Filled –> Email Sequence (brand intro + pain points acknowledgment + value establishment + FOMO + comparison) –> Goes to Features Page OR Pricing Page –> Books a Demo
This is an MQL. High five to the marketing team!”
Nooruddin Abbas Ali
CMO at Sell My SaaS
Dan Lawrence of Wrk confirms the importance of your leads being aware of how you can help them solve their issue. “In the SaaS world, you see leads take a few different routes to get to the MQL stage, but it’s primarily a qualified lead (based on certain criteria) who recognizes your product as a solution to the problem they are experiencing and provides you with their contact info to learn more,” says Lawrence and adds that marketing and sales teams should work together to define MQLs in a way that’s suitable for everyone.
“In terms of deciding what these criteria are, this starts to only gain clarity and buy-in when you include Sales leadership in the conversation and make sure the definitions for each stage are collectively decided. I do believe that the definition of an MQL is starting to move from lower-intent actions such as, “Email form submission” to more clearly defined actions such as “Meetings booked. We are starting to move away from the pure MQL definition and beginning to pay significant attention to including “Meetings booked” as a primary metric for qualification.”
Richard Muscat Azzopardi of Switch agrees that passing the lead to the sales team at all costs doesn’t generate results. Azzopardi explains what it looks like from the lead’s point of view.
“I don’t know you, I don’t know what your product is, I don’t even think that I need it but suddenly you’re emailing me daily to give you 30 minutes of my time for you to sell it to me? In what way is that meant to entice me? And does it actually work?
We believe in bringing leads to a client once the lead is ready to buy, ideally someone who’s primed, knows the brand, and has had enough time to interact with it to know what to expect – the values of the brand, the kind of services and the approximate price range.”
Is a lead marketing qualified if they don’t demonstrate a clear intent to buy your product or service? Yisrael Segall of floLIVE says “considerable intent to purchase” is included in his definition of an MQL.
“This can be, and should ideally be, explicit, meaning like a high intent form,” Segall comments. “I typically use engagement scoring and scoring decay models on key pages like product pages, contact us pages, solutions pages, to gather implicit high intent or by downloading or looking at a product brief,” explains Segall and adds that some popular beliefs are not necessarily true in practice.
“The theory that when they’re ready they’ll reach out, is not true. People can reach out before they are ready, and a lot of times the best time to reach out is at a slightly earlier stage, as it can deal with objections and position yourself as a sales consideration earlier.”
Not all MQLs are the same: they may have different levels of understanding of your product or service or be at different stages of the buyer’s journey. This is why Daniel Malgran of Capitol Canary from Quorum takes a “No MQLs left behind” approach and defines two MQL categories:
“Overall, I find it takes a good relationship between your marketing and sales teams to get the right flow,” concludes Malgran.
Kamil Rextin has a similar way of categorizing MQLs.
“For our clients, we split the MQL into 2 parts. Account Fit / Demographics – which basically means this person is from an account that fits our ICP & this person is also the right kind of person & we then layer activity data which indicates who ‘active’ they are in the buying cycle,” explains Rextin.
Jason Bradwell of B2B Better also divides MQLs into two categories:
“I keep it simple – Engagement Fit and Customer Fit,” reveals Bradwell.
“Latter is pretty static and based on demographic/firmographic data. Does the individual fit our ideal customer profile? Once a threshold is reached based on a simple scoring model, the box is checked.
Former is dynamic. Moves up and down based on how much the contact is engaging with our marketing materials – website, content, social, etc. Same as above, we’re looking to hit a score threshold.
Once both have been reached the contact is qualified as an MQL,” Bradwell comments and adds that most companies make a mistake when “an MQL is handed to sales for a 1:1 follow-up before any kind of intent has been measured.”
A better way to handle the MQL, according to Bradwell, is to put the contact into an intent qualification sequence to identify their readiness to buy. If readiness is high (e.g. contact has clicked the ‘talk to sales’ button) we’re golden. If readiness is low they get tagged appropriately and left alone (by sales). For me, it doesn’t have to be more complicated than that. The main thing to remember is – an MQL is not necessarily a prospect. The customer needs to tell you that.”
“An MQL is not necessarily a prospect. The customer needs to tell you that.”
Founder and Fractional CMO at B2B Better
The firmographic & demographic data approach also works even when you don’t work with traditional MQLs, like the Databox team. Peter Caputa, Databox’s CEO, explains how his team defines product-qualified leads (PQLs).
“At Databox, we use a PQL definition that includes the typical stuff you’d include in an MQL definition.
The reason why we don’t have an MQL definition is because we don’t currently do any gated content (ebooks, webinars, etc) to capture information before someone signs up for our product. Instead, we offer a free version of our product & free dashboard/reporting templates that get new leads right into our free product.
Since we get people right into the product, product usage is the best determinant of whether they will buy. It accounts for 50% of our PQL formula.
But, we also append firmographic data (business size, type, industry) & demographic data (person’s title) from Clearbit to each signup/lead we get. (And we also try to capture some of this info in our new Benchmark Groups app.)
This firm/dem data allows us to prioritize our first email so that we’re focused on better fit customers, even if they haven’t set up the free product yet. But, instead of defining a very specific profile, we have a formula that weights each lead based on the criteria.
So, for example, if a mid-sized marketing agency owner signs up, they will get a higher score than if an intern at a F500 customer signs up,” shares Caputa.
We also asked marketing professionals for tips on ensuring a high likelihood of buying for their MQLs. Here’s what they do to achieve that.
Like most marketers and marketing managers, you want to know how well your efforts are translating into results each month. Which sources generate the most leads? How well are your landing pages converting? Are you going to hit your lead generation goals for the month? You might have to scramble to put all of this together in a single report, but now you can have it all at your fingertips in a single Databox dashboard.
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Other than revisiting your MQL definition and adapting it to your product or service and the type of clients you work with, it’s recommended to keep it narrow. This way, you’ll ensure that the leads you pass on to the sales team are truly qualified.
“We keep the definition of MQL narrow and refine it quarterly,” says Bill Balderaz of Futurety Digital.
“For example, we want regulated industries, $50 million+ in revenue, with an engaged stakeholder. When we see other factors impact close rates positively or negatively, we integrate those factors in.”
Automation and AI can facilitate your job if you have clearly defined MQL criteria—software can categorize your leads faster and leave you more time to do meaningful work to convert them.
Chris Gadek of AdQuick advises relying on AI to select and prioritize leads.
“We use AI machine-based algorithms to select and prioritize leads based on patterns from behavioral data. When you expose AI systems to large amounts of user interaction data, machine learning has the capability to identify patterns often missed by sales teams. And as AI computes more of the whens, hows, and whys of visitor interaction with your website, the more accurate the predictive lead scoring becomes for your team,” explains Gadek.
Mapping out your customer’s journey to understand where your leads currently are gives you a better idea of how ready they are to buy, which further informs your next moves, according to Andrew Tsionas of Kaizenzo Inc.
“To increase the likelihood of MQLs buying, we map out and assess the customer’s journey. This gives us a better idea of where they’re at in the sales pipeline and allows us to better analyze and segment them into buying categories. It also helps us evaluate which parts of the sales pipeline can be improved upon to increase conversions,” explains Tsionas.
Rextin gives a few examples of what an MQL could be looking at on your website to be considered a high-intent lead.
“We base [the high intent] off a mix of signals. For example they have been viewing a bunch of PM content, viewed the pricing page multiple times, and they have a good account fit they are more likely to buy. If it’s a low account fit and low engagement, then there’s a lower likelihood they’ll buy.”
General Manager at 42 Agency
Lynne McNamee of Lone Armadillo Marketing & Learning says historical patterns of lead behavior help them understand which MQLs could become SQLs. Here’s what their team does:
“These will help us understand what should count as MQLs and what makes it a SQL,” concludes McNamee.
Related: 11 Expert Tips for Driving More Sales Qualified Leads
Drip campaigns can help you build a relationship with your lead, educate them about your product or service, boost future engagement, and—qualify them as an MQL if they fit your definition.
Natalie Slyman of BenchmarkONE uses personalized drip campaigns to address specific pain points in leads and move them toward purchase.
“These campaigns deploy based on content they download or industry/business type they’re in. These campaigns cater to their specific needs based on these activity/qualifying factors and they provide them with content that is educational and helpful,” says Slyman.
“We find that the more educated a lead is, the better customer they become down the line. We also make sure we walk them through a demo of our software with one of our sales reps so they can see first hand how our software can help them.”
Most companies we surveyed include the following in their MQL reports:
Number of MQLs, MQLs Conversion Rate, MQLs by Status, Targets, Comparison to previous periods and Number of days between lead created date and MQL date.
Most survey participants report on their MQLs to their upper management: CEO, founder, owner, but also VP of Sales, Marketing and Growth.
However, one respondent stated that this data is transparently available for the whole company to review.
No matter what your definition of MQLs is, you need a simple way to stay on top of the number of leads you’re able to generate through your marketing efforts.
Data analysis and reporting can take away a lot of your precious time if you do it manually, use complicated tools, or chase your data through different spreadsheets and tools instead of keeping it all in one place.
Wouldn’t you wish for a simple, easy-to-set-up tool to unite all your data sources, provide you with customization options, and allow your whole team to have insights into your progress?
Search no more because you’re in the right place—Databox can help you streamline your lead monitoring and reporting process, no matter the number of metrics tracked and data sources used. Get all of your important data in one place, through an easy-to-understand dashboard, with automated reports that are sent to your team to keep them up-to-date.
Sounds like something you would like to learn more about? You can get hands-on experience by creating a forever-free Databox account with no strings attached. Start exploring our tool today!
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