You launched a free tier six months ago, and the growth has been incredible. Ten thousand users signed up in the first three months. Your sales team is ecstatic—finally, a pipeline of qualified leads! They start working down the list, cold-calling every signup within twenty-four hours. "Hey, saw you signed up for our product. Let's hop on a call to discuss your needs."
The backlash is immediate. Users complain on Twitter about aggressive sales tactics. Your NPS drops. Conversion rate stays stubbornly at two percent. Sales starts grumbling that "PLG leads are low quality" and asking to return to traditional outbound. The entire motion feels broken.
Here's what went wrong: sales treated product-led growth like traditional demand gen. They reached out too early—before users experienced value. They targeted the wrong users—students and hobbyists alongside enterprise buyers. And they used the wrong message—generic discovery calls instead of value-based conversations.
Product-led sales is fundamentally different from traditional sales. You don't prospect cold into accounts that have never heard of you. You engage warm users who are already experiencing value from your product, at the precise moment when usage signals suggest they're ready to expand. Sales becomes consultative expansion, not cold interruption.
After building PLG-to-PLS motions at three companies—one with 3% conversion, one with 8%, and one with 12%—here's the framework that actually converts free users into paying customers.
The Core Principle: Product-Qualified Leads (PQLs)
Traditional MQL (Marketing Qualified Lead):
- Downloaded whitepaper
- Attended webinar
- Fits ICP
- Problem: Hasn't used product. May not have intent.
Product-Qualified Lead (PQL):
- Using product actively
- Hit specific usage milestones
- Exhibiting buying signals
- Fits ICP
- Advantage: Already seeing value. High intent.
PQLs convert 3-5x higher than MQLs because they've experienced the product.
The PQL Scoring Framework
Not all free users are equal. Score them based on fit and intent.
Dimension 1: Account Fit (0-40 points)
Company characteristics:
- Industry fit: 10 points
- Company size fit: 10 points
- Tech stack fit: 10 points
- Geography fit: 10 points
Example:
- B2B SaaS (10 pts) + 100-500 employees (10 pts) + Using tools we integrate with (10 pts) + North America (10 pts) = 40 points
Dimension 2: Usage Signals (0-40 points)
Product engagement:
- Weekly active user: 10 points
- Completed core workflow 5+ times: 10 points
- Invited teammates (2+): 10 points
- Used advanced features: 10 points
Example:
- Logs in 3x/week (10 pts) + Completed 10 workflows (10 pts) + Invited 3 teammates (10 pts) + Used integrations (10 pts) = 40 points
Dimension 3: Buying Signals (0-20 points)
Intent indicators:
- Hit free tier limit: 10 points
- Viewed pricing page: 5 points
- Contacted support asking about paid features: 5 points
Example:
- Hit 50-project limit (10 pts) + Viewed pricing 3 times (5 pts) + Asked about SSO in chat (5 pts) = 20 points
Total PQL Score (0-100 points)
Tier A (80-100 points): High fit + high usage + buying intent → Sales outreach immediately
Tier B (60-79 points): Good fit + moderate usage → Automated nurture, sales if they hit limit
Tier C (<60 points): Low fit or low usage → Product-led nurture only, no sales
Sales focuses on Tier A. Tier B gets light-touch. Tier C is product-led only.
When Sales Should Engage (The Trigger Framework)
Trigger 1: Hit Usage Limit
Signal: User hit free tier limit (projects, seats, API calls)
Why it works: They're blocked. They need paid tier to continue.
Example: "You've created 50 projects (free tier limit). Want to upgrade to Pro for unlimited projects?"
Sales approach:
- Automated email: "You've hit your limit. Here's how to upgrade" with self-serve link
- If high-value account (based on PQL score): Sales rep reaches out with special offer or trial
Conversion rate: 15-25% (high because they're already blocked)
Trigger 2: Invited Teammates
Signal: User invited 3+ teammates to collaborate
Why it works: Individual → team adoption. Teams pay.
Example: User invites 5 teammates, 4 accept. All are active.
Sales approach:
- Day 7 after team formation: "Your team is growing! Upgrade to Team plan for advanced collaboration features."
- Sales offers: Team pricing, onboarding support, trial of premium features
Conversion rate: 10-15% (team budget is easier than individual)
Trigger 3: Power User Behavior
Signal: User exhibits advanced behavior (daily usage, using 80% of features, creating integrations)
Why it works: They're committed. They see value.
Example: User logs in daily, completed 100+ workflows, built custom integration.
Sales approach:
- "We noticed you're a power user. Want to unlock [premium features] to do even more?"
- Offer: Free trial of paid tier, exclusive beta access
Conversion rate: 8-12% (power users are invested but may not need paid features yet)
Trigger 4: Viewed Pricing Multiple Times
Signal: User viewed pricing page 3+ times in last 7 days
Why it works: They're evaluating. Considering upgrade.
Example: User viewed pricing 5 times, compared tiers, left without upgrading.
Sales approach:
- "I noticed you've been looking at our pricing. Have questions? I can help you choose the right plan."
- Offer: Quick 15-minute call to answer questions, not a sales pitch
Conversion rate: 5-10% (they're interested but may have objections)
Trigger 5: Asked About Paid Features
Signal: User asked support or in-app chat about features only in paid tiers
Why it works: Explicit intent. They want paid features.
Example: User: "How do I set up SSO?" (Enterprise-only feature)
Sales approach:
- Support: "SSO is available on our Enterprise plan. Want me to connect you with our team to discuss?"
- Sales: Reach out with Enterprise demo, pricing
Conversion rate: 20-30% (explicit intent is highest signal)
The Sales Playbook by PQL Tier
Tier A (80-100 points): High-Touch Sales
Who: High-fit accounts, high usage, buying signals
Approach:
- Personal outreach from sales rep
- Reference their specific usage ("I see you've completed 50 launches...")
- Offer: Demo of paid features, free trial, custom package
Cadence:
- Day 1: Email (personalized, not template)
- Day 3: Follow-up email
- Day 5: LinkedIn message
- Day 7: Phone call (if contact info available)
Goal: Book demo, start sales conversation
Conversion target: 20-30%
Tier B (60-79 points): Light-Touch Sales
Who: Good fit, moderate usage, some intent
Approach:
- Automated email sequence with option to talk to sales
- In-app messages highlighting paid features
- Self-serve upgrade path emphasized
Cadence:
- Automated nurture emails (weekly)
- In-app banners when they approach limits
- Sales reaches out only if they hit high-intent trigger (pricing page views, hit limit)
Goal: Self-serve conversion or inbound request
Conversion target: 8-12%
Tier C (<60 points): Product-Led Only
Who: Low fit or low usage
Approach:
- No sales outreach
- Product-led nurture (email tips, feature highlights)
- In-app prompts to upgrade
Goal: Activate them first, convert later (if fit improves)
Conversion target: 2-5%
The Sales Messaging Framework
Bad PLG sales message: "Hi, I see you signed up for our product. Want to schedule a demo?"
Problem: Ignores that they're already using it. Sounds like generic outbound.
Good PLG sales message:
"Hi [Name],
I noticed you've created 45 projects in the last month and invited 4 teammates—amazing!
I wanted to reach out because you're close to your free tier limit (50 projects). Rather than hit that limit mid-launch, want to chat about upgrading to Pro? You'd get unlimited projects plus advanced analytics.
Happy to jump on a quick call or just send over a trial link if you want to test it out.
[Sales rep name]"
Why it works:
- References their actual usage (not generic)
- Acknowledges they're already getting value
- Solves a real problem (hitting limit)
- Low-pressure (trial offer, not hard sell)
How to Build Your PQL Model
Step 1: Define "Good Fit" Account Criteria
Firmographics:
- Industry: [target industries]
- Company size: [employee range]
- Revenue: [ARR range]
- Geography: [regions]
Tech stack:
- Using tools you integrate with
- Using competitors (displacement opportunity)
Step 2: Identify Usage Milestones That Predict Conversion
Analyze cohorts:
- What behaviors do paying customers exhibit before upgrading?
- Usage patterns: How often do they log in?
- Feature adoption: Which features do converters use?
- Team collaboration: Do converters invite teammates?
Example findings:
- 80% of paying customers invited 2+ teammates before upgrading
- 70% completed core workflow 10+ times
- 60% were weekly active users for 3+ weeks
Use these as PQL criteria.
Step 3: Score and Tier Accounts
Build scoring model:
- Account fit: 40 points
- Usage signals: 40 points
- Buying intent: 20 points
Tier accounts:
- A: 80-100 (sales outreach)
- B: 60-79 (light-touch)
- C: <60 (product-led only)
Step 4: Define Triggers
When should sales reach out?
- Hit usage limit
- Invited teammates
- Power user behavior
- Pricing page views
- Asked about paid features
Automate trigger alerts to sales.
Step 5: Measure and Iterate
Track:
- PQL → SQL conversion rate by tier
- PQL → Paid conversion rate
- Time from PQL to paid
- Sales efficiency (hours per conversion)
Optimize:
- Adjust scoring weights
- Refine triggers
- Test messaging
The Tech Stack for PLS
Product analytics: Amplitude, Mixpanel, Heap
- Track usage, identify PQLs
CRM: Salesforce, HubSpot
- Score leads, assign to sales
Sales engagement: Outreach, Salesloft
- Automate cadences for PQLs
In-app messaging: Pendo, Appcues
- Nudge users toward upgrade
Data warehouse: Snowflake, BigQuery
- Combine product + CRM data for scoring
Common PLS Mistakes
Mistake 1: Sales calls every signup
Every free user gets cold-called Day 1.
Problem: Users aren't ready. Annoying.
Fix: Only reach out to PQLs (high fit + usage + intent).
Mistake 2: No PQL scoring
Sales guesses who to call based on company name.
Problem: Inefficient. Low conversion.
Fix: Build scoring model. Automate PQL identification.
Mistake 3: Generic messaging
Sales uses same template for PLG and outbound leads.
Problem: Doesn't acknowledge they're already using product.
Fix: Reference their usage. Personalize based on behavior.
Mistake 4: Sales pitches features, not outcomes
"Want to see our analytics dashboard?"
Problem: They can see it themselves. Not helpful.
Fix: "You're manually exporting data. Want to automate that with scheduled exports?"
Mistake 5: No self-serve option
Every upgrade requires sales call.
Problem: Friction. Many users want to self-serve.
Fix: Self-serve upgrade for <$25K deals. Sales for enterprise.
Measuring PLS Success
Funnel metrics:
- Free signups → Activated users (completed core workflow)
- Activated users → PQLs (hit scoring threshold)
- PQLs → SQLs (sales-accepted)
- SQLs → Paid customers
Conversion rates:
- Activation rate: 40-60% (signups → activated)
- PQL rate: 20-30% (activated → PQL)
- SQL rate: 50-70% (PQL → SQL)
- Close rate: 20-40% (SQL → paid)
Efficiency metrics:
- Cost per PQL (product investment + nurture)
- Sales time per conversion
- PQL → Paid timeline (target <30 days)
Business metrics:
- % of revenue from PLG motion
- Expansion rate (free → paid → upsell)
- Retention (PLG customers vs. sales-led)
The Uncomfortable Truth
I've watched companies launch PLG motions and immediately undermine them with sales-led thinking. They celebrate hitting 10,000 free signups, then tell their sales team to call all of them. "More signups means more revenue," the VP of Sales announces in the Monday meeting. "Let's get aggressive with outreach."
Two weeks later, the motion is broken. Sales reps are burning through lists calling users who signed up fifteen minutes ago and haven't even activated. Users complain on Twitter about aggressive sales tactics when they just wanted to try the product. Sales complains the leads are terrible quality because 95% aren't interested in buying. Both teams are frustrated. The PLG motion that was supposed to create efficient growth is now creating friction and negative brand sentiment.
The fundamental problem is treating PLG like a lead generation engine for traditional sales rather than a fundamentally different go-to-market motion. In true product-led sales, the product drives activation and engagement while sales stays completely out of the way. Users discover value, activate features, invite teammates, and expand usage—all without talking to anyone. Sales only engages high-fit, high-intent users based on product signals that indicate genuine buying intent, not arbitrary calendars or signup dates. The self-serve path remains the default for most users. Sales assists expansion and enterprise deals where complexity genuinely requires human help.
The best PLG companies I've worked with operate this way. They have clear PQL definitions and scoring built into their product analytics. Sales reaches out based on actual product signals—team expansion, hitting usage limits, enterprise features activated—not because someone's been a user for 14 days. When sales does reach out, messaging references the user's actual usage: "I see your team is using X feature heavily and you're approaching the 50-user limit. Want to talk about our Team plan?" Self-serve remains the default path. Sales is optional assistance for users who signal they're ready, not mandatory friction for everyone who signs up.
When I diagnose PLG motions that aren't converting, the problem is usually one of four things. First, the product doesn't deliver fast enough time-to-value, so users churn before experiencing the "aha moment" that would make them want to buy. Second, there's no clear PQL scoring system, so sales just guesses which users to call based on company size or job title rather than actual product engagement. Third, sales reaches out too early or to the wrong users, creating friction instead of value. Fourth, messaging is generic outbound sales speak rather than personalized references to how they're actually using the product.
Fix the product experience first—make sure users can discover value quickly without human help. Then add sales to accelerate users who are already engaged and showing buying intent through their behavior. That's product-led sales, and it's a completely different motion than slapping a free trial onto your existing sales-led playbook.