Your product has a free tier. Users can sign up without talking to sales. The product itself is supposed to drive upgrades and expansion.
You're tracking standard SaaS metrics—MRR, CAC, LTV—but they don't tell you whether your product-led motion is actually working. Are free users experiencing value? Are they converting to paid at healthy rates? Is the product creating expansion opportunities, or do users hit a ceiling?
Product-led growth requires fundamentally different metrics than sales-led growth. In sales-led models, you measure sales performance. In product-led models, you measure product performance as your growth engine.
After implementing PLG analytics for four B2B companies and helping teams understand whether their product-led motions were succeeding or failing, I've learned that standard dashboards miss the metrics that actually matter for PLG.
Here's what to measure when your product drives growth.
The PLG Funnel: Different from Traditional SaaS
Traditional SaaS funnel: Marketing → Sales → Customer → Retention
PLG funnel: Product awareness → Free signup → Activation → Conversion to paid → Expansion
Each stage requires specific metrics that indicate funnel health.
Stage 1: Product awareness → Free signup (Top-of-funnel)
Traditional metric: Marketing qualified leads (MQLs)
PLG metric: Product-qualified signups (PQS)
Not all signups are equal. Track signup quality by measuring what percentage demonstrate buying intent:
- Used business email (vs. personal email)
- Completed profile with company information
- Invited team members during signup
- Connected business tools/integrations
If 60% of your signups are personal email addresses from users who never invite teammates, you have top-of-funnel quality problem, not volume problem.
PQS rate = Product-qualified signups / Total signups
Target: 40-60% for B2B PLG. If you're below 30%, you're attracting too many tire-kickers. Above 70% means you might be overfitting friction that prevents legitimate trial.
Stage 2: Free signup → Activation (First value)
Traditional metric: Demo completion rate
PLG metric: Time to value (TTV)
How long until a user accomplishes the core outcome your product promises? This isn't time to first login. It's time to first meaningful outcome.
For a CRM: TTV = time from signup to logging first customer interaction and viewing first insight about customer behavior
For analytics tool: TTV = time from signup to connecting data source and viewing first actionable report
Median TTV should be measured in hours or days, not weeks. If median TTV is 7+ days, most free users churn before experiencing value.
Track TTV by cohort and acquisition channel. If organic signups have median TTV of 2 days but paid signups have median TTV of 9 days, your paid targeting is attracting users with different readiness levels.
Stage 3: Activation → Conversion to paid (Monetization)
Traditional metric: Sales win rate
PLG metric: Product-qualified lead (PQL) to paid conversion rate
A PQL is a user who's demonstrated sufficient product engagement that they're likely ready to buy:
- Activated successfully
- Used product X times in Y days (habit formation)
- Hit a usage limit or constraint that paid plan would solve
- Shown expansion signals (invited teammates, connected integrations, created multiple workspaces)
Define your PQL criteria based on signals that correlate with high conversion rates. Then track:
PQL conversion rate = Users who converted to paid / Users who became PQLs
Target: 25-40% for most B2B PLG products. Below 15% means your PQL definition is too loose (you're flagging users who aren't truly ready to buy). Above 50% means it's too strict (you're missing conversion-ready users).
Stage 4: Conversion to paid → Expansion (Growth)
Traditional metric: Upsell and cross-sell rates
PLG metric: Net revenue retention via product triggers
In PLG, expansion shouldn't require sales calls. The product should create natural upgrade triggers:
- User hits usage limit (storage, API calls, seats)
- User requests feature only available in higher tier
- Account reaches threshold that suggests higher tier would deliver more value (team size, data volume, integration needs)
Track:
Product-triggered upgrade rate = Upgrades initiated from in-product prompts / Total upgrade opportunities created
If you're creating 200 upgrade prompts per month (users hitting limits or requesting premium features) but only 20 users upgrade, your prompt strategy or upgrade path has friction.
Also track: Expansion revenue from product-led triggers vs. sales-led outreach
In healthy PLG, 60-70% of expansion should come from product triggers, not sales reaching out. If sales drives most expansion, your product isn't creating enough compelling upgrade moments.
The PLG-Specific Metrics Dashboard
Beyond the funnel, PLG products need metrics that sales-led products don't track.
Metric 1: Virality coefficient
How many new users does each existing user bring?
Virality coefficient = (Invitations sent × Invitation acceptance rate) / User
If average user sends 2.5 invitations and 40% of recipients sign up, your virality coefficient is 1.0 (each user brings one more user).
Coefficient > 1.0 creates organic growth loops. Coefficient < 0.5 means you're relying on paid acquisition, not product virality.
Track this by user segment. Power users might have coefficients of 2.5+ (they invite whole teams), while casual users have coefficients near 0.1 (they rarely invite anyone). Your product should make it easy for power users to activate their teams.
Metric 2: Feature adoption velocity
PLG products succeed when users discover value quickly across multiple features. Track:
Features adopted in first 30 days (by user segment)
Successful PLG users typically adopt 3-5 features within first month. Users who only use one feature tend to churn or stay stuck in free tier.
If your median user adopts 1.2 features in 30 days, your onboarding isn't creating multi-feature engagement. Users experience shallow value, not deep value.
Metric 3: Self-serve vs. assisted conversion
What percentage of conversions happen without human interaction vs. requiring sales touchpoints?
Self-serve conversion rate = Users who upgraded without sales contact / Total conversions
True PLG targets 70-80% self-serve. If only 30% of conversions are self-serve, you have a hybrid model (which is fine!) but not pure PLG.
If self-serve rate is low, diagnose why:
- Unclear pricing/packaging in product
- Checkout flow has friction
- Users have questions product doesn't answer
- Decision requires procurement process that needs sales facilitation
The diagnosis tells you whether to fix product UX or accept that your sales motion is necessary.
Metric 4: Paid user reactivation rate
PLG advantage: churned customers can reactivate without sales calls.
Reactivation rate = Churned users who reactivate / Total churned users (measured 90 days post-churn)
Traditional SaaS rarely sees reactivations above 2-3%. PLG products with good win-back flows achieve 10-15%+ reactivation.
Track what triggers reactivation:
- Automated win-back email campaigns
- Product updates that address previous churn reason
- New use case emerges for the user
- User returns due to external trigger (new job, new project)
High reactivation rates indicate your product has staying power—even users who leave remember the value and come back.
The Bottleneck Identification Framework
Use metrics to identify where your PLG motion breaks down.
Calculate conversion rates between each stage:
- Signup → Activation: X% of signups reach activation
- Activation → PQL: Y% of activated users become PQLs
- PQL → Paid: Z% of PQLs convert to paid
- Paid → Expansion: W% of paid users expand within 12 months
Your weakest conversion rate is your primary bottleneck.
If signup → activation is lowest:
Problem: Onboarding doesn't deliver fast time-to-value
Fix: Simplify activation criteria, reduce setup friction, improve in-product guidance
If activation → PQL is lowest:
Problem: Users activate but don't form habits or hit usage thresholds
Fix: Nurture campaigns, usage nudges, expand free tier limits to drive engagement
If PQL → paid is lowest:
Problem: Even engaged users don't convert
Fix: Pricing/packaging clarity, better upgrade prompts, reduce friction in checkout
If paid → expansion is lowest:
Problem: Paid users don't grow usage
Fix: Product-led expansion triggers, usage-based pricing, better upsell in-product prompts
Focus on your biggest bottleneck first. Improving a 10% conversion to 15% (50% relative improvement) has more impact than improving a 60% conversion to 65% (8% relative improvement).
The Cohort Maturity Model
PLG metrics evolve as user cohorts mature. Track cohorts over time to see adoption curves.
Week 1: Activation rate (did they get first value?)
Week 4: Habit formation rate (are they using it regularly?)
Week 8: PQL conversion rate (have they hit signals indicating readiness to pay?)
Week 16: Paid conversion rate (did they actually convert?)
Month 6: Expansion rate (are they growing usage/spend?)
Plot these metrics for each monthly cohort. You're looking for improvements over time:
- Are newer cohorts activating faster?
- Are PQL rates improving?
- Is paid conversion increasing?
If every metric stays flat across cohorts, your PLG motion isn't improving despite product changes. If metrics improve for new cohorts, your iterations are working.
When you track PLG-specific metrics, you stop guessing whether product-led growth is working. You have clear evidence of where the motion succeeds and where it breaks down—insights that let you systematically improve the product as a growth engine.