Once upon a time (roughly five minutes ago in internet years), sales and marketing teams had a simple story:
marketing generated leads, scored them into MQLs, and tossed the “hot ones” over the wall to sales.
Then SaaS, freemium, free trials, and product-led growth showed up like a party crasher with analytics in one hand
and a “skip the demo” sign in the other.
Now buyers can try your product before they ever talk to a human. They can invite teammates, hit a value moment,
and quietly become “ready to buy” while your marketing automation is still proudly celebrating an ebook download.
Enter: PQLs (Product Qualified Leads).
So… are PQLs the new MQLs? Sometimes. Often. Kinda. But not always. The real answer is more useful than a trendy hot take:
PQLs change what “qualified” meansand they force your go-to-market team to coordinate around product usage,
not just marketing engagement.
Quick Definitions (Because Acronyms Multiply When You’re Not Looking)
What is an MQL?
An MQL (Marketing Qualified Lead) is a lead marketing believes is more likely to become a customer than
your average website visitorbased on engagement and/or fit. Think: webinar attendance, key page visits, repeat site
activity, content downloads, email clicks, and “this person matches our target profile.” In other words:
they’re interested, but not necessarily ready to buy.
What is a PQL?
A PQL (Product Qualified Lead) is someone who has experienced meaningful value in your product (usually via
freemium or a free trial) and is showing signalsthrough actual usagethat they’re likely to convert to paid.
PQLs are qualified by in-app behavior, not just marketing activity.
And what about SQL?
An SQL (Sales Qualified Lead) is a lead the sales team considers ready for direct outreach and an active
sales process. This can be based on interest, intent, fit, budget/timeline, or a combinationdepending on your business.
Are PQLs Replacing MQLs? The Real Answer (Without the Hype)
PQLs aren’t a universal replacement for MQLs. They’re a different qualification layer that becomes extremely
powerful when your product itself is a major part of acquisition and evaluation.
Here’s the simplest way to think about it:
- MQL: “This person is engaging with our marketing and looks like a good fit.”
- PQL: “This person is actively getting value from the product and looks close to buying.”
- SQL: “Sales is ready to work this opportunity now.”
In a product-led motion, PQLs often become the most reliable trigger for sales outreachbecause product usage can be
a stronger indicator of intent than a content binge. But MQLs still matter in a lot of situations (more on that soon).
Why PQLs Are Having a Moment
1) Buyers want to “try, then talk”
In many categoriesespecially SaaSbuyers prefer hands-on evaluation. They’ll explore features, test workflows,
and prove value internally before inviting sales into the conversation. That flips the traditional sequence:
the product becomes the top of the funnel, not just the thing you buy at the end.
2) First-party product data is a goldmine
Product usage data is high-signal when tracked thoughtfully. It can reveal:
which features matter, who is adopting, whether teams are collaborating, and whether usage aligns with successful
conversions. Compared to some “engagement” metrics (like a single email click), product actions can be harder to fake
and easier to connect to real value.
3) Sales teams want better timing
Nobody loves calling a lead who downloaded a checklist and is now emotionally attached to never speaking to another human again.
PQLs can help sales reach out when the prospect is already experiencing valueand might be hitting natural upgrade friction:
user limits, feature gates, permissions, security needs, reporting, integrations, compliance, and so on.
4) The “lead” is often an account, not a person
Many PLG companies move from PQLs to product-qualified accounts (PQAs)because one enthusiastic user doesn’t
always equal a buying decision. If three teams inside the same company are actively using the product, that’s a very different
kind of signal than one solo user dabbling at 2 a.m.
When MQLs Still Win (Yes, Really)
If your product isn’t easily trialable, or if your buyers can’t self-serve (think: complex implementation, regulated environments,
high-security requirements, or heavy services), then PQLs may not be the primary engine.
MQLs remain important when:
- There’s no meaningful free trial/freemium experience (or it’s too limited to show value).
- Your deal sizes are enterprise-heavy and require long evaluation cycles, committees, and procurement.
- Demand is created through education (new category, new problem awareness, or major behavior change).
- Buying happens before usage (e.g., hardware, certain professional services, or closed systems).
- Your best-fit prospects aren’t the ones signing up (common when signups skew SMB but ICP is larger firms).
In these cases, MQLs can still guide pipeline creationespecially when combined with strong qualification frameworks and
careful handoffs to sales.
The Best Model for Most Teams: MQL + PQL (Not MQL vs PQL)
The smartest go-to-market teams don’t run an acronym cage match. They build a system where:
marketing generates awareness and demand, product creates activation, and
sales engages when timing and fit align.
A common modern flow looks like this:
- Marketing → drives acquisition and identifies early intent/fit (MQLs).
- Product → creates value and captures usage signals (PQLs/PQAs).
- Sales → focuses on the highest probability opportunities (SQLs), often triggered by PQL/PQA signals.
How to Build a PQL System That Sales Actually Trusts
A PQL program fails when it becomes “MQL scoring, but inside the product.” A PQL program wins when it reliably identifies
the users and accounts most likely to buy, and when sales can see why a lead is qualified.
Step 1: Define your “value moment” (your product’s version of an “aha!”)
Start with a simple question: What do successful customers do early on?
Examples vary by product, but the pattern is consistent: there’s usually an activation milestone that correlates strongly with retention
and conversionlike completing onboarding, inviting teammates, connecting a key integration, or generating a meaningful output.
Step 2: Combine fit + usage + intent (the PQL trifecta)
Product usage alone can be misleading. A student can be a power user and still have a budget of $0 (a tragic story, but a true one).
The most useful PQL definitions typically blend:
- Fit signals: company size, industry, role, region, tech stack, ICP match.
- Usage signals: activation events, feature adoption, frequency, collaboration, time-to-value.
- Intent signals: hitting limits, viewing billing, requesting security docs, repeated admin actions, pricing page visits, upgrade clicks.
Step 3: Create a clear threshold (and resist “PQL inflation”)
If everything is a PQL, nothing is. Set thresholds based on historical data:
look at closed-won customers and identify the usage patterns that predicted conversion.
Then define a PQL in plain Englishsomething sales can repeat without sweating:
“An ICP-fit account that has invited 3+ users, completed setup, and used Feature X at least twice in the past week.”
Step 4: Route PQLs like you mean it
Your routing rules should answer:
Who owns the next action, and how fast should it happen?
Some teams route by account size (self-serve for SMB, sales-assist for mid-market, strategic sales for enterprise).
Others route by “high intent” actions (billing page + limit hit + admin activity).
Step 5: Give sales context, not just a label
The single best way to build trust: show the “why.”
When a rep sees that a team has:
(1) invited coworkers,
(2) integrated with a key system,
and (3) hit a usage cap,
the outreach becomes helpful instead of annoying.
Step 6: Nurture in-product (because email isn’t the only channel anymore)
In a PLG motion, the product itself is a communication channel. Use in-app prompts, tooltips, checklists,
and contextual messages to guide users to valueand to upgrade points.
Sales outreach works best when it feels like an extension of that experience, not a cold interruption.
Concrete Examples of PQL Definitions (Steal These and Tweak Them)
Example A: Project management SaaS
- Fit: company email + team size 20–500.
- Usage: created 5+ projects, added 10+ tasks, used automation once.
- Collaboration: invited 3+ teammates and assigned tasks to 2+ users.
- Intent: visited billing page or clicked “upgrade” twice, or attempted to use a gated feature (permissions/reporting).
Example B: Analytics/BI tool
- Fit: role includes analyst/ops/finance; ICP industry match.
- Usage: connected a data source, built 2 dashboards, shared 1 dashboard.
- Intent: invited an admin, requested SSO/SAML docs, or hit refresh/usage limits.
Example C: Developer platform
- Fit: business domain + company size threshold; work email.
- Usage: completed API setup, generated keys, made 1,000+ calls, integrated with CI/CD.
- Intent: viewed pricing for higher tier, attempted advanced security features, created multiple environments.
Common Mistakes That Make PQLs Look Great on Slides (and Bad in Reality)
Mistake 1: Treating any active user as sales-ready
High usage is not the same as buying intent. Usage without fit can create noisy pipelines and burned-out reps.
Build guardrails with ICP signals and account-level context.
Mistake 2: Defining PQLs by vanity actions
Logging in is not a value moment. Neither is clicking around like a tourist at a buffet.
Focus on actions that correlate with outcomes: setup completion, collaboration, repeat use of core features,
and reaching upgrade friction.
Mistake 3: Ignoring the account
In B2B, one enthusiastic user might be a championor just someone procrastinating.
Track whether adoption is spreading across a team. Consider shifting from PQL to PQA when it fits your motion.
Mistake 4: No SLA, no ownership, no follow-up
A PQL that sits untouched is just a fancy label. Define SLAs (response time goals),
ownership rules, and the next best action. Otherwise, you’re basically collecting “qualified” leads like trading cards.
How to Measure Whether PQLs Are Actually Working
Don’t just count PQLs. Track what matters:
- PQL → SQL rate: Do PQLs become real sales opportunities?
- PQL → Paid conversion rate: How many PQLs convert (and how quickly)?
- Pipeline velocity: Do PQLs move through the funnel faster than MQLs?
- Win rate and ACV: Are you generating better deals, or just more activity?
- Expansion/retention: For some teams, “PQL thinking” also improves upsell and cross-sell targeting.
So… Are PQLs the New MQLs?
If your product can be tried easilyand product usage strongly predicts purchasethen PQLs often become the most practical,
highest-signal handoff to sales. In that sense, yes: PQLs can act like the “new MQLs” because they’re a more direct
proof of value and intent.
But the best teams don’t “replace” MQLs as much as they upgrade the qualification system:
marketing still drives awareness and early intent; product validates value and readiness; sales focuses on the moments where help
accelerates conversion.
Extra: Real-World Experiences Teams Commonly Have When Shifting from MQLs to PQLs (About )
When companies start leaning into PQLs, the first “experience” is usually emotional: excitement, followed by confusion,
followed by someone saying, “Wait… who owns this now?” That’s normal. PQLs change not just lead scoring, but team behavior.
One common story goes like this: marketing proudly reports a big number of MQLs, sales complains that the MQLs aren’t ready,
and product is quietly thinking, “We can literally see who’s getting valuewhy aren’t we using that?”
The first time the team builds a PQL definition and routes it to sales, everyone expects magic.
Then reality shows up, carrying a spreadsheet.
The early PQL list is often too big. Reps chase users who are active but not buyersstudents, consultants testing tools,
or small teams that love the product but will never pay for the premium plan. This is where teams learn the hard lesson:
usage signals need fit signals. Once the team adds ICP filters (company size, role, industry, work email, account matching),
sales trust starts to increase because reps aren’t wasting cycles on “power users with zero purchasing power.”
Another experience teams report: sales outreach gets better when it becomes helpful.
Instead of, “Hey, saw you downloaded our guide,” the rep can say,
“Noticed your team created three workspaces and hit the reporting limitwant me to show you how teams like yours handle that?”
The conversation feels timely. It also feels less like a pitch and more like removing friction.
Reps who were skeptical often become fans once they see they can anchor outreach on real product context.
There’s also a “culture shift” moment: product managers and growth teams realize they are now shaping pipeline.
When onboarding improves and time-to-value drops, PQL volume and quality improve too. That’s a big change from the old world,
where pipeline was mostly a marketing-and-sales conversation. Teams start meeting together to review activation funnels,
identify where users stall, and decide what in-app nudges (or lifecycle emails) should happen before sales reaches out.
Finally, many teams discover that PQLs don’t eliminate marketingmarketing evolves.
Content and campaigns still matter, but now they’re designed to drive the right people into the product,
help them succeed quickly, and then support the upgrade moment. The “win” isn’t choosing PQLs over MQLs.
The win is aligning the whole go-to-market engine around one simple truth:
the fastest path to revenue is helping customers experience value.
Conclusion
PQLs are powerful because they’re grounded in what buyers actually do, not just what they click.
For product-led and hybrid sales motions, they can dramatically improve timing, prioritization, and conversionespecially when you
combine product usage with fit and intent. MQLs still play a role in awareness and early demand creation, but PQLs often become
the clearest signal that someone is moving from “interested” to “ready.”