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What is a Marketing Qualified Lead (MQL)?

Definition, Lead Scoring, and Nurturing Tips

Genrate Leads on LinkedIn

Illustration of an individual standing on a ladder with a reverse funnel and stack of coins on the side.

Sales teams rely heavily on B2B marketing teams to help them generate more high-quality leads. That’s why it’s essential to understand how to properly define, attract, and score a marketing qualified lead or MQL.

This guide provides an in-depth marketing qualified lead definition and describes how to qualify and nurture a marketing qualified lead vs sales qualified lead (SQL). Additionally, we’ll explain how the MQL sales progression into an SQL works and provide efficiencies around measuring cost per marketing qualified lead (CPMQL) and conversion rates.

Select a topic to explore further:

What is a marketing
qualified lead (MQL)?

Why are MQLs important

for marketers?

MQL vs SQL

How do you score and
qualify a lead as an MQL?

Lead nurturing strategies
to convert more MQLs

Transferring MQLs to
SQLs and tracking their
progress

How to measure and
optimize MQL campaign
success

Attracting and nurturing
MQL leads with LinkedIn

What is a marketing qualified lead (MQL)?

An MQL or marketing qualified lead is a prospective customer who has taken a specific action (e.g., visited a branded website, downloaded a whitepaper, or clicked an ad) that indicates they are interested in a product or service but are still in the early stages of brand awareness, solution discovery, or evaluation. These MQL actions must be identified in advance by a B2B marketing team and given a score to indicate how likely that customer lead is to become a sales opportunity in the future.

Illustration of two individuals sitting across from each other and having a conversation.

Illustration of two individuals standing in front of a projection stand and having a conversation.

Why are MQLs important for marketers?

MQLs help marketing teams to better track, quantify, and nurture warm leads that come in through inbound marketing efforts that they can then pass along to their sales team. Once a lead is scored as high-quality, the customer’s contact information and any special insights will be shared with sales teams for direct follow-up.

Illustration of two individuals standing in front of a projection stand and having a conversation.

MQL vs SQL

MQLs can be confused with sales qualified leads or SQLs. Simply put, MQLs are leads that the marketing team attracts through various advertising and content marketing strategies. Marketing qualified leads are interested in learning more about a product or service but do not yet intend to make a purchase. SQLs are high-quality leads that are scored as being in the consideration or purchase phase of the sales funnel or are ready to buy a solution. SQL leads can be passed on via the marketing team when they are scored as such or via inside sales and cold outreach efforts. Refer to LinkedIn’s guide to learn more about SQLs.

How do you score and qualify a lead as an MQL?

Most MQLs have a sales cycle involving multiple stakeholders and a lengthy decision-making process. Lead scoring helps marketing teams evaluate which MQLs are warmest and worth nurturing, using strategies and resources to shorten the funnel for sales teams to close those deals faster.

When an MQL comes in via inbound marketing strategies such as content marketing (e.g., filling out a form to download a free ebook) or digital advertising (e.g., clicking a social media ad to visit a branded website), marketing teams will assign a specific score to identify where that lead fits within the sales funnel.

The marketing qualified lead-scoring process

There are different ways to score an MQL. Ideally, sales and marketing teams will work together to identify the criteria for what constitutes an MQL vs SQL. Additionally, they’ll assign a score based on how likely a customer intends to purchase in the near term.

For example, B2B marketers might score an MQL that visits their pricing web page lower on their scale than one that signs up online for a free product demo. Registering or subscribing to events and newsletters online are also good lead-scoring criteria. However, marketers may score those MQLs less than leads that call a 1-800 number to ask for product or service-specific information.

Many sales organizations will use the BANT method, which stands for budget, authority, need, and timing to score each MQL lead (e.g., a score of 1 for least likely to buy and 5 for most likely to buy) based on implicit and explicit data points which are described below.

Illustration of two individuals standing in front of a desk and having a conversation with several data visualization displayed above them.

Explicit data for scoring MQLs

Firmographic data: The MQL’s company size, industry, revenue, and location
Demographic data: An MQL’s job title, seniority, department, and authority
Technographic data: Product compatibility with an MQL’s technology stack

Implicit data for scoring MQLs

Behavioral data: An MQL’s frequent engagement with online marketing content, social media, company website activity, and email marketing
Trigger events: Recent changes at an MQL’s company, such as leadership changes, mergers, acquisitions, or expansions
B2B sales lead qualification data: When an MQL fills out marketing contact forms, visits a pricing page, asks for information or a product demo, and starts a free trial

Lead nurturing strategies to convert more MQLs

The following inbound marketing strategies will help B2B marketing teams to establish contact with new MQLs and nurture those leads throughout the sales funnel:

Retargeting

Suppose a prospect has previously clicked on a lead generation ad and has visited a branded website or landing page to learn more. In that case, marketing teams can use a retargeting campaign to expose them to relevant ads based on their topics of interest (e.g., after landing on a case study page or inviting them to sign-up for a webinar based on a topic they viewed on the website).

The more a prospective buyer comes in contact with a B2B brand, the more likely they will eventually submit their contact information, which is used to nurture the prospect relationship further.

B2B brands that advertise on LinkedIn can use the LinkedIn retargeting pixel, also known as the LinkedIn Insight Tag. This tag tracks visitor data and uses that data for retargeting or to enhance other paid ad or sponsored content campaigns.

Illustration of an individual sitting with their laptop and a website highlighting ads on the page displayed on the side.

Landing pages and lead generation forms

Once a prospect has arrived on a landing page, B2B marketers must create a compelling argument as to why the customer should provide their contact information to learn more about a product or service.

The message should be short, clear, and easy for customers to request information. B2B marketers should include convincing copy and focus on only one specific topic for the landing page. Be sure to offer an incentive, such as a free research report or ebook, to entice leads to share their name, email address, and phone number.

Finally, include a strong call to action or CTA, like “download,” “sign up,” or “subscribe.” Adding social proof in the form of a customer testimonial is also recommended. Refer to LinkedIn’s guide to learn more about landing pages.

Many sales organizations also try to gather information about the lead’s level of influence in the contact form by asking for their role or title and the industry they are in. Some will try to understand the lead’s budget range for purchasing their product or service. However, neither is mandatory and the fewer fields required for form completion, the more likely a prospect will be to share their contact information.

Illustration of an individual sitting with their laptop and a website highlighting areas on the page displayed on the side.

Watch the LinkedIn lead generation form video to learn more:

Email and content marketing

After a lead fills out a lead generation form or signs up for an industry webinar or event, marketing teams will establish contact via email marketing (e.g., newsletters or blog updates) – assuming they have opted in to receive communications from their company.

Marketers will then begin sending prospects high-quality content that drives them deeper into the sales funnel – answering common industry or solution-based questions that remove any fear, uncertainty, or doubt about purchasing their product or service.

Ideally, the marketing MQL will eventually reach the highest lead score to be transferred over to the sales team for outreach and to set up a discovery call. The time required to nurture and convert an MQL to an SQL depends on where a prospect has entered the purchase funnel when they first connect with a brand. It also depends on how that lead is first scored. It can take as little as a few weeks or months to a year or two to close the deal, depending on an MQL’s internal decision-making process.

Review LinkedIn’s lead generation guide to learn more about nurturing an MQL throughout the sales funnel.

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Transferring MQLs to SQLs and tracking their progress

Once an MQL reaches the highest lead score, their contact information or personal data will be automatically shared with sales via a CRM system such as Salesforce or Microsoft 365 – especially in larger sales organizations. In smaller organizations, the information may simply be forwarded to an account team or rep via email or Slack.

Refer to LinkedIn’s lead automation tips to learn how to track and transfer MQLs efficiently. Or, read LinkedIn’s guide to defining and tracking SQLs throughout the sales funnel.

Illustration of several data visualizations.

How to measure and optimize MQL campaign success

As new MQL sales leads enter the B2B marketing lead nurturing process, businesses can use campaign reporting tools, conversion tracking, web analytics data, and their sales CRM systems to monitor and nurture prospective customers through the sales funnel.

They may also integrate their CRM systems with relationship intelligence tools like LinkedIn Sales Navigator to identify, track, and nurture even more high-quality leads using real-time, first-party Insights from over 850 million LinkedIn members worldwide.

Before launching campaigns to attract new MQLs, it’s essential to set KPIs and benchmarks for how many leads the marketing team needs to attract to help sales teams achieve quarterly and annual targets. Those performance metrics will vary across sales organizations based on company size and revenue targets.

Calculating and optimizing the cost per marketing lead (CPMQL) and target conversion rates is also important. To calculate CPMQL, B2B marketers can divide the total cost of their ad, social media, or email campaigns by the total number of new MQLs generated for a certain period (e.g., monthly, quarterly, or annually).

The formula for market share is:

CPMQL = Total costs / Total number of new MQLs.

For example, if a campaign costs $2,000 and generates 50 new high-quality MQLs, the CPMQL would be $40. Realistically, a good MQL can cost up to a few hundred dollars to attract, nurture, and qualify. That’s because many leads will not fit the proper lead scoring criteria to be deemed “high-quality” by a sales team when they first enter the sales funnel.

It’s also why lead nurturing and tracking B2B ad campaign conversions, or the percentage of leads that turn into a sale, are essential for optimizing MQL results. B2B marketers should always prioritize the highest-scoring leads to nurture first, based on their urgency and importance to their sales team.

Review LinkedIn’s guide to properly track and optimize online leads and conversions.

Attracting and nurturing MQL leads with LinkedIn

B2B marketing teams are often under pressure to help sales teams generate more high-quality leads. Attracting, scoring, nurturing, and converting new marketing MQLs takes time and practice.

Inbound marketing strategies like digital ads, content marketing, social media, and email campaigns are an excellent place to start. As new leads come in, score each using implicit and explicit data that evaluates an MQL’s budget, authority, need, and timing (BANT) to make a purchase decision. Next, develop appropriate strategies to help sales teams move MQLs through the funnel, transfer them into their CRM systems, and close more deals faster.

Visit LinkedIn’s Lead Generation overview page to learn how to attract and nurture new leads by targeting over 1 billion professionals worldwide through social media ads, and sponsored content and/or messaging.

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