MQL

How an MQL works

An MQL is a funnel stage that a contact passes through. In HubSpot's default lifecycle stages, a contact moves from Subscriber to Lead, then to Marketing Qualified Lead and Sales Qualified Lead, and later to Opportunity, Customer and Evangelist 1. HubSpot defines the MQL stage as a contact or company that the marketing team has qualified as ready for the sales team 1.

What earns the label varies by company, but two kinds of evidence usually combine.

• Fit. The company matches the ideal customer profile on size, industry and region, and the contact holds a relevant role. These are firmographics and job data that a team can check or fill in.
• Engagement. The person has interacted with marketing. HubSpot's examples are downloading an ebook, attending a webinar or regularly clicking through emails 2.

Most teams combine both into a lead score and set a threshold. When a contact crosses it, the stage changes to MQL and the lead goes to a sales development rep or into a review queue. HubSpot notes that its default automatic updates only move the lifecycle stage forward, so moving a lead back takes a deliberate change 1.

The stage works as an agreement between two teams. Marketing says the lead is worth a look. Sales then accepts it, works it and either promotes it to a sales qualified lead or sends it back with a reason. Without that loop, marketing optimizes for the count of MQLs and sales stops trusting the label.

An MQL is still early. Salesforce describes MQLs as prospects who are still working out their pain points and goals and have mostly interacted with the company through marketing channels 3. Sales should start with questions, not pricing.

Not every MQL needs a call. Some teams route MQLs from small accounts to a self-serve trial or a product tour and save rep time for accounts that match the higher tiers of the profile. The label says the lead is worth attention. The routing rule decides what kind of attention it gets.

Setting the MQL threshold

The hardest decision is where to draw the line. Set it too low and reps chase people who wanted one free resource. Set it too high and real buyers wait in a nurture stream while a competitor calls them.

Three habits keep the threshold honest.

First, mix fit and behavior. Engagement alone produces MQLs from students, job seekers and competitors. Fit alone produces MQLs from companies that never asked for anything. Salesforce suggests demographic criteria such as geography, role, company size and industry alongside behavior 3.

Second, subtract points. Salesforce recommends negative scoring for leads without adequate budget and using signals of disinterest, such as unsubscribing, to disqualify a lead 3. Without negative signals, scores only rise, and every old contact eventually becomes an MQL.

Third, measure conversion with the right lag. HubSpot puts typical MQL to SQL conversion at 10% to 20%, while noting that the range shifts with business model, sales cycle length and lead source quality 2. The formula is SQLs divided by MQLs, times 100 2. HubSpot's example is 26 SQLs from 200 MQLs, a 13% rate 2. If conversion takes three months, compare SQLs created in month three with MQLs created in month one 2.

Review the threshold against closed deals every quarter. If most MQLs that became customers shared two or three traits, weight those traits more.

Example of an MQL

A software company runs a gated guide on audit preparation. The form asks for a name, a company and a company website, and the marketing team scores each submission.

Lead score rule set
  Fit       +20 company in target industry
            +15 headcount in target band
            +10 job title in buying team
  Behavior  +10 downloaded the guide
            +15 attended a webinar in the last 30 days
            +20 visited the pricing page
  Negative  -30 personal email domain with no company match
            -40 unsubscribed from marketing email
MQL threshold: 60 points

A contact from a midsize clinic downloads the guide and attends a webinar. The company fits and the title is in the buying team. The score clears the threshold, so the contact becomes an MQL and lands in the review queue.

Before the handoff, the team fills the gaps that would stall a rep. The form did not ask for a work email, so a Zap calls the RichAPI email_finder endpoint and then email_verifier on each fill 4. RichAPI has no Zapier app, so both calls run through Webhooks by Zapier Custom Request, which is a paid Zapier action 4. A miss returns HTTP 200 with success false, so the Zap needs a Filter step on success before the verifier runs 4.

At 200 fills a month and a 60% hit rate, the finder bills 120 calls at 5 credits, or 600 credits, and the 80 misses are free 4. Verifying the 120 found addresses at 2 credits adds 240, for 840 credits in total 4.

The rep who picks up the MQL now has a verified address, the company record and the engagement history in one place. The first call asks about the audit timeline and who owns the budget, which is how the lead either becomes a sales qualified lead or returns to nurture.

MQL vs SQL

An MQL is a lead marketing believes is worth a look. An SQL is a lead sales has confirmed is ready for a sales conversation. Most SQLs start as MQLs, but the two labels are owned by different teams and answer different questions 2.