Most teams treat qualification as a meeting: marketing passes a name, sales calls it, and only then does anyone know if it fits. Much of that check is classification, and classification can run on a written rule in minutes. Below: both stages, shows a hand-off rule you can write down, and explains where product qualified leads fit.
What is a marketing qualified lead?
An MQL is a lead that meets two tests: the company fits the ideal customer profile, and the person has shown enough interest to justify a seller's time. Fit is about who they are: company size, industry, role. Interest is about what they did: requested a demo, downloaded a pricing guide, attended a webinar, visited the pricing page several times.
The term comes from the SiriusDecisions Demand Waterfall, first published in 2006 and revised in 2012 and 2017. It gave marketing and sales a shared set of stages, with the MQL as the point where marketing's job hands over to sales.
What is a sales qualified lead?
An SQL is a lead that sales has confirmed is a real opportunity: there is a problem the product solves, a person who can act, and an agreed next step. That confirmation usually needs a conversation, because the facts it rests on, such as a pain, a timeline or a budget, rarely show up in data.
Teams often write SQL criteria as a checklist. IBM's partner programme published its BANT criteria template, covering budget, authority, need and timeline, as one formal example. Many teams now use lighter versions focused on need and a confirmed next step.
The SQL stage protects the pipeline. If every MQL counted as an opportunity, forecasts would fill with names that never had a problem to solve. Counting only confirmed SQLs keeps the pipeline honest and shows marketing which sources produce real conversations.
Who decides the hand-off, and on what?
Marketing and sales decide it together, in writing, before any lead moves. The rule should name the fit criteria, the interest threshold, who owns the lead after hand-off, and what happens when sales rejects it. A rejected lead goes back to nurture with a reason, not into a void.
| Criterion | MQL | SQL | Back to nurture |
|---|---|---|---|
| Company fit | Matches the ICP on size, industry, country | Confirmed on the call | Outside the ICP |
| Role | Can influence the purchase | Can act or brings the person who can | No link to the problem |
| Signal | Demo request, pricing visit, hiring in the target team | Problem confirmed in their words | No activity after the last touch |
| Action | Routed to an owner | Next meeting booked | Added to a nurture sequence |
Example rule in plain text: company size 50 to 500, role in sales or marketing, hiring an SDR in the last 90 days: route as MQL to the regional owner. Illustrative; set your own thresholds.
Forrester's 2021 Revenue Waterfall changed the unit from a single lead to the buying group. In practice, the hand-off rule should ask whether the account is qualified, not just whether one person filled in a form.
The stage names come from SiriusDecisions, now part of Forrester. Forrester's history of the Demand Waterfall covers the 2006, 2012 and 2017 versions and the MQL and SAL stages. The 2021 Revenue Waterfall moved the unit of measurement to the buying group and added renewal, cross-sell and upsell. IBM's BANT template is a formal example of SQL criteria.
Where does a product qualified lead fit?
A product qualified lead (PQL) is a user of a free plan or trial whose behaviour in the product signals buying intent: inviting colleagues, hitting a usage limit, connecting an integration. It sits alongside the MQL rather than replacing it. The MQL relies on marketing engagement; the PQL relies on product usage, which is usually the stronger signal. Teams with a free tier often route PQLs straight to sales and keep the MQL for leads from content and events.
Can qualification run automatically?
The MQL stage can, almost entirely. Fit is classification: compare company size, industry, role and recent signals against written criteria. Once a lead is enriched with that data, a rule or an AI classifier can apply the criteria in seconds and route the lead to its owner. Speed matters here, because the value of an inbound lead falls quickly while it waits in a queue.
The SQL stage mostly cannot. Whether the problem is real, and whether the person will take a next step, is learned in a conversation. Automate the first gate and give sellers more time for the second.
Marketing teams use Leadspicker to enrich inbound leads and assign the right salesperson automatically: classification that would take a person time runs on custom rules in a few seconds. Leadspicker's guidance is to respond to an engaged lead ideally within five minutes.
Frequently asked questions
What is the difference between an MQL and an SQL?
An MQL is a lead marketing judges a good fit and engaged enough to pass on. An SQL is a lead sales has confirmed as a real opportunity, usually after a conversation. The MQL rests on data; the SQL rests on what the prospect said.
What is a SAL?
A sales accepted lead is the step between the two in the SiriusDecisions waterfall: sales has accepted the MQL and committed to follow up, but has not yet qualified it. Many teams merge it into the SQL stage.
Should every MQL get a call?
Only if it still fits after enrichment. Check company fit and role against the written rule first; leads that fail go to nurture with a reason, so sellers spend their calls on leads that can become SQLs.
