Marketing Qualified Lead (MQL)
A Marketing Qualified Lead (MQL) is a lead that has shown enough interest and fit — through behaviors like downloading content, attending a webinar or repeated site visits — that marketing deems it worth passing to sales for follow-up. It is more engaged than a raw lead but not yet vetted by a salesperson.
How it works
Leads become MQLs when they cross an agreed lead-score threshold or trigger a qualifying action. The MQL is then routed to an SDR or sales rep who attempts contact and further qualification, either accepting it or sending it back.
Why it matters
The MQL is the handoff point between marketing and sales, so a shared, precise definition prevents the classic friction where marketing claims to deliver leads that sales dismisses as junk. Tracking MQL-to-SQL conversion reveals whether the definition is calibrated.
How Autocloz handles it
Autocloz keeps the full engagement history that qualifies an MQL — opens, clicks, replies, calls, meetings — on one contact timeline, so the marketing-to-sales handoff carries the context the rep needs to act.
FAQ
What is the difference between an MQL and an SQL?
An MQL is qualified by marketing based on engagement and fit signals; an SQL is a lead a salesperson has vetted and accepted as a genuine opportunity worth pursuing. The MQL-to-SQL step is where sales validates marketing's judgment.
What makes a good MQL definition?
One that sales and marketing agree on and that correlates with real conversion. It usually combines fit criteria (matches the ICP) with a meaningful action or score threshold, and is revisited as MQL-to-SQL conversion data comes in.
Related terms
Lead enrichment is the process of automatically adding missing data to a lead or company record — job title, company size, industry, verified email, phone, LinkedIn, technographics — from third-party data sources, so reps can segment, personalize and prioritize without manual research.
An Ideal Customer Profile (ICP) is a description of the company that gets the most value from your product and is easiest to win and retain — defined by firmographics like industry, company size, revenue, geography and technology stack. It targets accounts (the company), distinct from a buyer persona, which describes the individual within the account.
Lead scoring is the practice of assigning a numeric value to each lead based on how well they fit your ideal customer profile (demographic/firmographic fit) and how engaged they are (behavioral signals like email opens, site visits, demo requests). The score ranks leads so sales works the hottest ones first.
Intent data is behavioral information that signals a company or person is actively researching a product, category or solution — indicating they may be in-market to buy. It includes first-party signals (activity on your own site and content) and third-party signals (content consumption and search behavior across a data provider's network of sites).