PLG Metrics: The 10 KPIs That Actually Matter
Only 25% of PLG companies measure Product Qualified Leads. Yet PQLs convert at 5-6x the rate of MQLs.1 Most companies drown in vanity metrics while ignoring the numbers that predict revenue. This chapter gives you the 10 metrics that matter for PLG, with benchmarks to know if you’re winning or losing.
Why Do Traditional Metrics Fail Product-Led Growth?
Traditional SaaS metrics assume a sales-led funnel: MQLs, SQLs, opportunities, closed-won. Product-led growth doesn’t work that way. Users experience value before talking to sales, often before you even know their company name.
Traditional vs PLG Metrics
| Traditional | PLG Equivalent | Why It’s Different |
|---|---|---|
| MQL (marketing qualified lead) | PQL (product qualified lead) | Usage signals > form fills |
| SQL (sales qualified lead) | Expansion-ready account | Product data shows readiness |
| Demo requests | Activation rate | Users prove value themselves |
| Pipeline value | Free user quality score | Revenue comes from engaged free users12 |
The AARRR framework (Acquisition, Activation, Retention, Revenue, Referral) works better for product-led growth because it follows the user journey, not the sales process.3 Some teams flip it to RARRA, prioritizing Retention first, because most PLG companies fail from churn, not acquisition.3
The 10 PLG Metrics Stack
Here are the 10 metrics that predict PLG success, organized by funnel stage.
Activation Metrics
1. Activation Rate
The percentage of signups who reach your aha moment.
| Performance | Activation Rate | Context |
|---|---|---|
| Poor | <20% | Onboarding broken or wrong users |
| Average | 20-35% | Typical PLG (34.6% average)4 |
| Good | 35-50% | Strong onboarding |
| Excellent | >50% | Best-in-class |
Product-led growth companies average 34.6% activation, lower than sales-led (41.6%) because freemium attracts less committed users.4 That’s not a bug. It’s the model. Your job is to convert the committed ones.
2. Time to Value (TTV)
How long until users experience meaningful value. Measured in minutes for simple products, days for complex ones.
| Product Type | Target TTV | Example |
|---|---|---|
| Simple tools | <5 minutes | Calendly (first booking) |
| Collaboration | <1 hour | Slack (first team message) |
| Complex SaaS | <1 day | Figma (first design shared) |
For the complete TTV optimization playbook, see Time to Value.
3. Core Feature Adoption
Percentage of users who adopt your primary value-driving feature.
Benchmark: Only 24.3% of users adopt core features.4 Three out of four users never see your main value proposition. This is where most PLG companies leak users.
Engagement Metrics
4. DAU/MAU Ratio (Stickiness)
Daily Active Users divided by Monthly Active Users. Measures how often users return.
| Category | Typical DAU/MAU | Interpretation |
|---|---|---|
| Communication tools | 40-60% | Daily habit |
| Collaboration tools | 25-40% | Regular use |
| Productivity tools | 20-30% | Frequent use |
| Business software | 10-20% | Weekly/periodic |
| Analytics tools | 5-15% | Occasional use5 |
What DAU/MAU actually means:
- 50% = Users engage every other day
- 20% = Users engage ~6 days/month
- 10% = Users engage ~3 days/month
Don’t compare your analytics tool to Slack. Compare to products with similar usage patterns.
5. Day 7 and Day 30 Retention
Percentage of users who return at Day 7 and Day 30 after signup.
| Timeframe | Poor | Average | Good | Excellent |
|---|---|---|---|---|
| Day 1 | <30% | 40-50% | 55-65% | >70% |
| Day 7 | <15% | 20-30% | 35-45% | >50% |
| Day 30 | <5% | 10-20% | 25-35% | >40%2 |
Day 7 retention is your leading indicator. If users don’t return in Week 1, they rarely return at all. Trial-to-paid conversions spike around Day 7 for both PLG and sales-led companies.4
Once you’ve validated that users stick around, the next question is whether they pay.
Revenue Metrics
6. Free-to-Paid Conversion Rate
Percentage of free users who become paying customers.
| Model | Poor | Average | Good | Excellent |
|---|---|---|---|---|
| Freemium | <1% | 2-5% | 5-10% | >10% |
| Free trial (no CC) | <10% | 15-25% | 30-40% | >50% |
| Free trial (CC required) | <25% | 30-40% | 50-60% | >60%26 |
Benchmark: 9% of free accounts convert to paid overall. Products with $1K-$5K ACV see 10% median conversion.4
7. PQL-to-Customer Rate
Percentage of Product Qualified Leads who convert to paying customers.
| ACV Range | PQL Conversion | vs MQL |
|---|---|---|
| <$1K | 15-25% | 3x MQL |
| $1K-$5K | 25-30% | 5x MQL |
| $5K-$10K | 35-39% | 6x MQL1 |
PQLs convert 5-6x better than MQLs because they’ve already experienced value. Yet only 25% of companies track them.1 This is the biggest measurement gap in product-led growth.
Efficiency Metrics
8. Net Revenue Retention (NRR)
The metric that separates good PLG companies from great ones. NRR measures revenue from existing customers after accounting for expansion, contraction, and churn. Above 100% means you’re growing from your existing base alone, before any new sales.
| Performance | NRR | What It Means |
|---|---|---|
| Poor | <90% | Losing customers faster than expanding |
| Average | 90-100% | Breaking even on existing base |
| Good | 100-120% | Growing from existing customers |
| Excellent | >120% | Strong expansion engine |
Top PLG Companies:
| Company | NRR | How They Do It |
|---|---|---|
| Snowflake | 158% | Usage-based pricing compounds |
| Twilio | 155% | API calls grow with customer success |
| Datadog | 130% | Land and expand across teams |
| Slack | 143% | Seat expansion + tier upgrades7 |
9. CAC Payback Period
Months to recover customer acquisition cost.
| Performance | Payback | Context |
|---|---|---|
| Excellent | <6 months | Efficient growth |
| Good | 6-12 months | Healthy unit economics |
| Average | 12-18 months | 2024 median is 20 months |
| Poor | >24 months | Unsustainable without capital2 |
Median payback hit 20 months in 2024, down from 25 months in 2022, but still far above the historical 12-14 month standard.4 Best-in-class PLG companies achieve <12 months.
The efficiency crisis: Median B2B SaaS companies now spend $2 to acquire $1 of new ARR.8 This unsustainable ratio is driving the shift to hybrid PLG + sales motions and renewed focus on expansion revenue over new logo acquisition.
10. LTV:CAC Ratio
Lifetime value divided by customer acquisition cost.
| Ratio | Interpretation |
|---|---|
| <1:1 | Losing money on every customer |
| 1-2:1 | Marginal economics |
| 3:1 | Healthy (industry benchmark) |
| 4-5:1 | Strong unit economics |
| >6:1 | Excellent (or underinvesting in growth)2 |
Product-led growth typically achieves higher LTV:CAC (4-6:1) because self-serve acquisition costs less than sales teams. But watch out: if your ratio exceeds 6:1, you may be underinvesting in growth.
Retention Compounds Faster Than Acquisition
Run the math: 5% better activation helps once per user. 5% better monthly retention compounds twelve times per year. After 12 months, that retention improvement beats doubling your activation rate. Compounding is everything.
The Math:
- 1,000 users at 90% monthly retention = 282 users after 12 months
- 1,000 users at 95% monthly retention = 540 users after 12 months
- That 5% difference = 91% more retained users
Implication: The RARRA framework (Retention, Activation, Referral, Revenue, Acquisition) may be more accurate than AARRR for mature PLG companies. Fix retention first. Then optimize the funnel that feeds it.
PLG Benchmarks by Category
Different product categories have different benchmark expectations. Use these to calibrate your targets.
| Category | Typical Free-to-Paid | Best-in-Class NRR | S&M as % of Revenue |
|---|---|---|---|
| Communication | 25-30% | 140%+ (Slack) | 30-50% |
| Design tools | 10-15% | 130%+ | 20-40% |
| Developer tools | 5-10% | 120%+ (Atlassian) | 12-21% |
| Project management | 10-15% | 135% (Asana enterprise) | 50-65% |
| Analytics | 2-5% | 110-120% | 40-60%9 |
What this means:
- Communication tools have the highest conversion rates because team value is immediately obvious. Slack and Zoom demonstrate clear ROI when teams communicate.
- Developer tools have lower conversion but much more efficient go-to-market (Atlassian’s 12-21% S&M spend vs. 50%+ for most SaaS). The product does the selling.
- Analytics tools struggle with conversion because value is often delayed. Users need to collect data before seeing insights.
- Project management shows high S&M despite PLG because enterprise deals require sales involvement. Asana spends 62% of revenue on S&M.
Action Items
- Calculate your activation rate: What percentage of signups reach your aha moment within 7 days? If you don’t know your aha moment, stop here and define it first. You can’t measure activation without knowing what “activated” means.
- Start tracking PQLs: Define 2-3 product signals that predict conversion. Slack uses 2,000 messages. Dropbox uses multi-device sync. Only 25% of companies track PQLs. The other 75% are guessing who to sell to.
- Measure Day 7 retention: This is your leading indicator for everything else. Below 25%? Your activation is broken. Above 40%? You’ve found product-market fit. Check this number before optimizing anything else.
- Calculate your NRR: (Starting MRR + Expansion - Contraction - Churn) / Starting MRR. Below 100% means your flywheel spins backwards. Fix churn before scaling acquisition. Above 120% means existing customers are your growth engine.
- Build a weekly metrics dashboard: Track these 10 metrics every Monday. Trends matter more than snapshots. A declining activation rate is a bigger problem than a low-but-stable one.
Footnotes
-
OpenView Partners, “Product Benchmarks Report 2022-2024.” PQL conversion rates 5-6x MQL. Only 25% of PLG companies track PQLs. ↩ ↩2 ↩3 ↩4
-
OpenView, “2022-2024 SaaS Benchmarks.” Retention, conversion, LTV:CAC, and payback benchmarks. ↩ ↩2 ↩3 ↩4 ↩5
-
Dave McClure, “AARRR Pirate Metrics Framework.” RARRA variant prioritizes retention via Growth Hackers, Amplitude. ↩ ↩2
-
Userpilot, “SaaS Product Metrics Benchmark Report 2024-2025.” Activation rates, feature adoption, trial conversion timing. ↩ ↩2 ↩3 ↩4 ↩5 ↩6
-
Amplitude, “Guide to Product Metrics.” DAU/MAU benchmarks by product category. ↩
-
First Page Sage, “SaaS Free Trial Conversion Rate Benchmarks,” 2023. Trial conversion by credit card requirement. ↩
-
Slack Technologies S-1 (2019), Snowflake S-1 (2020), Twilio and Datadog earnings reports. NRR figures from public filings. ↩
-
T2D3 Research, “The Great Recalibration: B2B SaaS Performance and the Hybrid Mandate in 2025.” ↩
-
OpenView 2022 Product Benchmarks, company filings (Atlassian, Asana, Slack). Category-level conversion, NRR, and S&M benchmarks. ↩