A B2B Marketing Qualified Lead (MQL) is a lead that the marketing team has determined meets the criteria for passing to the sales team. The criteria that define an MQL vary by company but typically combine two types of signals: fit signals (does the lead match the ICP -- the right industry, company size, geography, and role?) and intent signals (does the lead's behaviour suggest they are actively evaluating solutions -- content downloads, demo requests, multiple page views of pricing or product pages, email engagement?). The MQL threshold is the point at which the combination of these signals is strong enough that a sales rep's time is better spent engaging this lead than continuing to nurture them.
How to define the MQL threshold
Fit criteria
Fit criteria filter for ICP match: the right job titles (only decision-makers or influencers in the buying process), the right company size (e.g., 100-1,000 employees for mid-market SaaS), the right industries (the verticals where your product has the most proven value), and the right geography (especially relevant for India-focused B2B companies where the domestic vs. export segmentation changes the sales motion entirely). Leads that do not meet fit criteria should not become MQLs regardless of their behavioural engagement -- a very engaged lead from outside the ICP wastes sales time and distorts pipeline metrics.
Intent criteria
Intent criteria capture buying signals: a demo request (highest intent, should trigger immediate MQL regardless of fit score), a free trial signup, a pricing page visit (moderate to high intent), a gated content download (low to moderate intent), a webinar registration or attendance (low to moderate intent), or email click engagement above a threshold. Intent criteria should be weighted by their predictive power for conversion: in most B2B SaaS businesses, a demo request converts to SQL at 3-5x the rate of a content download, so weighting them equally in a lead score underestimates the value of demo requests.
Lead scoring and thresholds
Lead scoring assigns points to each fit and intent criterion: for example, job title VP or above = 10 points, company size 100-500 employees = 8 points, demo request = 20 points, pricing page visit = 10 points, gated content download = 5 points, email click = 2 points. An MQL threshold is set at a total score above which the lead is passed to sales (e.g., score of 30+ and at least one intent action = MQL). The threshold should be calibrated against historical data: review the leads at different score ranges and track which ones actually converted to SQL, then adjust the threshold to maximise the MQL-to-SQL conversion rate rather than maximising MQL volume.
MQL-to-SQL conversion rate
The MQL-to-SQL conversion rate is the percentage of MQLs that sales accepts as Sales Qualified Leads (SQLs). A healthy B2B MQL-to-SQL rate is 40-70%: above 70% suggests the MQL threshold may be too restrictive (sales is converting almost everything it receives, but marketing could be passing more volume); below 40% suggests the MQL threshold is too loose (sales is wasting time on leads that are not ready or not fit). The MQL-to-SQL rate should be measured and reviewed in a monthly marketing-sales alignment meeting -- persistent misalignment on this metric is a sign that the MQL definition needs to be renegotiated between marketing and sales.
Common MQL mistakes
- Volume over quality: marketing is incentivised on MQL volume rather than MQL-to-SQL conversion rate, leading to a low threshold that floods sales with unqualified leads
- Ignoring fit: high behavioural engagement from out-of-ICP companies creates MQLs that sales cannot convert, wasting time and distorting pipeline metrics
- No feedback loop: sales does not communicate back to marketing why MQLs were rejected, so marketing cannot adjust the scoring model
- Treating all MQL sources equally: a demo request and a content download have very different conversion rates but are often both counted as "MQLs" without differentiation
- Static thresholds: MQL criteria defined once and never revisited as the product, ICP, or market evolves
Frequently asked questions
- What is an MQL in B2B marketing?
- An MQL (Marketing Qualified Lead) in B2B is a lead that the marketing team has determined is ready to pass to sales, based on criteria that signal a combination of ICP fit and buying intent. Fit signals: the lead matches the target company size, industry, geography, and job title. Intent signals: the lead has taken actions that suggest active evaluation -- a demo request, a free trial signup, a pricing page visit, or high engagement with marketing content. MQL is the stage between a raw lead (any contact who has entered the database) and a SQL (Sales Qualified Lead -- a lead that sales has confirmed is a genuine, qualified opportunity). The MQL-to-SQL handoff is one of the most important process moments in a B2B marketing-sales alignment.
- What is the difference between an MQL and an SQL?
- MQL (Marketing Qualified Lead): a lead that marketing has qualified as ready to pass to sales, based on fit criteria (ICP match) and intent signals (behavioural engagement). The MQL qualification is done by marketing, usually automatically via lead scoring. SQL (Sales Qualified Lead): a lead that sales has confirmed is a genuine, qualified opportunity after an initial discovery conversation or qualification call. The SQL qualification is done by the sales rep who has spoken with the lead and confirmed: they have a real problem your product solves, they have a budget or can get one, they have the authority or access to the decision-maker, and there is a reasonable timeline for a decision. MQL is a marketing output; SQL is a sales input to the pipeline. The MQL-to-SQL conversion rate measures the quality of marketing's qualification.
- How do you set the MQL threshold?
- To set the MQL threshold: (1) Define your ICP criteria and make them binary gates -- a lead must meet all ICP criteria (right job title, right company size, right geography) to become an MQL regardless of their behavioural score; (2) Assign points to intent signals weighted by their predictive value for conversion (demo request: 20 points; pricing page visit: 10 points; content download: 5 points; email click: 2 points); (3) Set a minimum total score that balances MQL volume (enough leads for sales to work) with MQL quality (a conversion rate above 40%); (4) Review the MQL-to-SQL conversion rate monthly and adjust the threshold if it is below 40% (raise the threshold) or if sales is consistently under-worked (lower the threshold or review ICP fit criteria). The initial threshold should be set as a hypothesis and refined based on data, not set once and forgotten.
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