PLG Readiness Scorecard Calculator

Score your product-led growth motion across 6 dimensions — Time-to-Value, Activation, Self-Serve, Viral K-Factor, Expansion NRR, and PQL Conversion. Get a True PLG / Sales-Led in Disguise verdict with OpenView benchmarks. No signup.

Last reviewed: April 2026 · Benchmarks from OpenView 2024 PLG Index

F
Not PLG
0/100
Experimental StageQuiz: 0/6K-Factor: 0.16

Next step: Focus on Viral K: Add collaborative features. Make sharing the default path, not an afterthought.

Are You Actually PLG?

Answer 6 questions — 5+ Yes unlocks the True PLG badge

1

Can users sign up, activate, and get value without talking to sales?

2

Do users reach aha moment in < 30 minutes without training?

3

Can users upgrade to a paid plan entirely in-app, no human needed?

4

Does using the product naturally invite or expose others to it?

5

Is your median TTV < 1 day?

6

Do activated users invite teammates without a prompt?

Your PLG Metrics

Signup Funnel

New free/trial signups per month

Minutes to reach first value moment

% who complete the core action

Monetization

% of revenue with no sales touch

Net Revenue Retention including expansion

% of PQLs that convert to paid

Overall free → paid conversion

Virality

Avg invites sent per activated user

% of invitees who sign up

Company Stage

Report Card

TTVC
45 min48/100
Elite: ≤5mOK: ≤30m

Reduce steps to first value moment. Progressively reveal complexity after aha.

ActivationC
18%45/100
Elite: 40%OK: 25%

Map activation milestones. Add in-app checklists and progressive onboarding nudges.

Consider Appcues or Userpilot for in-app onboarding.

Self-ServeC
42%53/100
Elite: 80%OK: 50%

Reduce friction in upgrade flow. Remove sales gates from your freemium tier.

Viral KF
0.1616/100
Elite: 1OK: 0.4

Add collaborative features. Make sharing the default path, not an afterthought.

K-Factor Calculator
Expansion NRRD
105%38/100
Elite: 130%OK: 110%

Add usage limits that grow with teams. Surface upgrade prompts at value milestones.

Churn & NRR Calculator

June.so or Amplitude can surface expansion signals.

PQL ConvC
10%40/100
Elite: 28%OK: 12%

Define PQL triggers based on usage signals, not time. Score leads automatically.

PLG Radar

TTVCActivationCSelf-ServeCViral KFExpansion NRRDPQL ConvC

vs. PLG Benchmarks

What-If Simulator

Adjust key levers to preview the composite impact

+0 pts → F
45 min
11440
18%
060
42%
0100
0.16
01.5

Reverse Calculator

Scenario A vs B Compare

Save the current state as Scenario A to start.

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What Is a PLG Readiness Scorecard?

A PLG readiness scorecard is a systematic audit of whether your SaaS product is genuinely product-led or whether sales and human touchpoints are still driving most of your revenue. Unlike a survey, this calculator uses your actual metrics — activation rate, self-serve revenue percentage, NRR, viral K-factor, time-to-value, and PQL conversion — to produce an objective composite grade.

The PLG readiness scorecard calculator on this page is calibrated to OpenView's 2024 PLG Index benchmarks: activation rate medians by stage, NRR percentiles for PLG vs sales-led cohorts, TTV bands (elite ≤5 minutes, danger ≥24 hours), and PQL conversion baselines. It produces 5 distinct verdicts — True PLG, PLG-Assisted, PLG-Curious, Sales-Led in Disguise, and Not PLG — based on composite score and a 6-question qualitative quiz.

Why a composite, not a single metric: every single PLG metric can be gamed. High activation but 0% self-serve means your onboarding is great but your product is still sold by humans. High self-serve % but 85% NRR means you close without help but your product is shrinking. The composite surfaces contradictions the gap detector flags explicitly.

How to Score Your Product-Led Growth Motion

The product-led growth score calculator measures 6 dimensions, each normalized to 0–100, then averaged into a composite. The composite drives one of 5 PLG zones and a maturity stage (Experimental → Dominant).

Dimension
Formula
A Threshold
F Threshold
Time-to-Value
Log-scale 0.5 min → 24h
≤ 5 min
> 24 h
Activation Rate
Linear 0 → 40%
≥ 40%
< 10%
Self-Serve Revenue
Linear 0 → 80%
≥ 80%
< 20%
Viral K-Factor
K = invites × conv%
K ≥ 0.7
K < 0.1
Expansion NRR
Linear 90% → 130%
≥ 130%
< 95%
PQL Conversion
Linear 0 → 25%
≥ 25%
< 5%

A critical rule: if self-serve revenue % is below 20%, the composite is capped at 45 regardless of other scores. A product where 80%+ of revenue requires a human is not PLG — and the scorer reflects that automatically.

Self-Serve SaaS Conversion Metrics: The 4 That Matter

Of the 6 PLG dimensions, 4 are conversion metrics: activation rate (signup → aha), PQL conversion (behavioral intent → paid), free-to-paid conversion (freemium → paid), and self-serve revenue % (paid accounts closed without humans). The other two — TTV and NRR — are efficiency metrics.

Why self-serve revenue % outweighs the others: you can have 50% activation and still have zero PLG if a salesperson is closing every deal. Self-serve % is the single most honest signal of PLG maturity. A threshold of 80% or higher defines a True PLG motion; 20–50% is the Sales-Led in Disguise zone.

OpenView's 2024 benchmarks for self-serve revenue %: p10 = 15%, p50 = 45%, p90 = 85%. Most companies that call themselves PLG in investor pitches are clustered around the p25–p50 range — product-assisted, not product-led.

NRR Benchmarks for PLG Companies

Net Revenue Retention is the most powerful signal of PLG health because it measures whether your product creates value that expands over time without human intervention. PLG NRR benchmarks from OpenView 2024: p10 = 95%, p50 = 110%, p90 = 135%. Elite PLG companies (Figma, Notion at scale, Miro) hit 125–145%.

NRR below 100% is a contraction signal that overrides everything else in the PLG scorecard. If your product is shrinking its installed revenue base, expansion loops are not working — and the gap detector in this calculator will surface it as a priority gap.

The PLG NRR formula used here: score = clamp(((NRR% − 90) / 40) × 100, 0, 100). This puts 90% at 0 (contractionary), 110% at 50 (healthy median), and 130% at 100 (elite). NRR below 90% is treated as an F regardless of the formula output.

Time-to-Value: What OpenView Says Is Top-Decile

Time-to-Value (TTV) — the median time from signup to aha event — is the most controllable PLG lever. OpenView's 2024 benchmarks: p10 = 2 minutes, p50 = 30 minutes, p90 = 24 hours. Top-decile PLG products (Canva, Figma, Linear) get users to aha in under 5 minutes.

This calculator uses log-scale scoring for TTV because the relationship is non-linear: cutting TTV from 2 hours to 30 minutes is more impactful than cutting from 30 minutes to 10 minutes. The formula is: score = 100 × (1 − log(max(TTV, 0.5)) / log(1440)), where 1440 is the 24-hour ceiling.

Practical TTV reduction levers: (1) pre-loaded sample data eliminates empty-state confusion; (2) one-click integrations cut setup time by 70%; (3) interactive product tours cut TTV by 15–30 minutes; (4) role-based onboarding paths get users to the right aha for their job function.

The PLG Maturity Model: Experimental → Dominant

The PLG maturity model categorizes companies into 4 stages based on composite PLG score. Experimental (below 50): running PLG experiments but not yet a motion. Most usage is sales-driven. Self-serve is a side door, not the main entrance.

Emerging (50–69): hybrid motion. PLG handles small-deal or SMB acquisition; sales still closes mid-market and enterprise. TTV and activation are improving, but self-serve revenue % lags. Most Series A and B SaaS companies land here.

Scaling (70–84): PLG is the dominant motion. Self-serve revenue % is above 50%. Viral loops are working. Sales is now product-assisted rather than product-independent. This is where companies like early Notion, Figma, and Linear operated.

Dominant (85+): PLG is the competitive moat. NRR above 125%, K-Factor above 0.5, TTV under 10 minutes. The product sells itself in most segments. Less than 3% of self-described PLG companies reach this stage.

Activation vs Aha Moment: What the Calculator Measures

Activation rate and aha moment are not the same metric. Activation is the percentage of signups who complete the first meaningful action (account setup, first data input, first teammate invited). Aha is the emotional inflection point where the user realizes the product solves their problem. A user can activate without reaching aha.

This calculator measures activation in the aggregate: the % of signups who cross your defined aha event within the trial or onboarding window. Benchmark: median 18% (OpenView 2024), top-quartile 42%. Activation rate directly drives the activation aha moment calculator — every 10pp improvement flows through to a 3–5pp trial-to-paid lift.

The fastest activation improvements come from: (1) pre-filling the new user's workflow with sample or imported data; (2) a single mandatory "must-do" step in onboarding that maps directly to aha; (3) real-time progress feedback ("You're 1 step away from your first insight"); (4) removing friction from account setup (SSO, no billing during trial, no credit card).

Free-to-Paid Conversion Benchmarks in PLG SaaS

Free-to-paid conversion benchmarks in PLG SaaS depend on the model. Freemium: 2–5% annually (Slack ~5%, Figma ~7% at scale). Reverse trial (paid defaults, auto-downgrade): 12–18%. Free trial without CC: 15–25%. CC-required free trial: 50–65% per user against 40% of normal TOF.

The free-to-paid conversion benchmark saas context matters: a 5% freemium conversion is excellent. A 5% free trial conversion is poor. The calculator accepts a separate "free-to-paid %" input to incorporate your actual conversion and use it as a PQL sub-score modifier.

The highest-leverage free-to-paid improvements target the upgrade trigger — the moment where the user first hits a paid-only feature while doing something valuable. Notion's block limit, Linear's team size limit, and Figma's editor-seat restriction are all upgrade triggers designed to fire at peak perceived value.

PQL Conversion Benchmarks by Stage

PQL conversion rates vary significantly by stage and deal size. Product-qualified lead conversion benchmarks: median 12%, top-quartile 25%, elite 30%+. Enterprise PQL (intent: multi-seat expansion, API usage spike) converts at 40–60% because the signal is unambiguous.

The most common PQL triggers: hitting usage limits (storage, seats, API calls), inviting a certain number of teammates (3+ for enterprise intent), 7+ consecutive active days, or using integrations (Salesforce, Jira). Products with product qualified lead conversion benchmark scores above 25% typically have 2–3 well-defined PQL triggers and a PQL-triggered sales workflow (not a spray-and-pray outbound sequence).

The relationship between PQL conversion and self-serve revenue %: high PQL conversion with high self-serve % = true PLG. High PQL conversion with low self-serve % = you have good intent signals but still require humans to close — PLG-Assisted at best.

Frequently Asked Questions

Am I really running a PLG motion?

True PLG requires users to sign up, activate, upgrade, and invite teammates without a human touchpoint. The 6-question quiz tests each gate. If you score less than 4/6, you are PLG-curious at best. Self-serve revenue below 50% is the most common signal that a product marketed as PLG is actually sales-led in disguise.

How do you calculate a product-led growth score?

A PLG score is a composite of 6 dimensions: TTV (log-scale, lower is better), Activation Rate (40% = A), Self-Serve Revenue % (80% = A), Viral K-Factor (K=1.0 = A), Expansion NRR (130% = A), and PQL Conversion (25% = A). If self-serve revenue is below 20%, the composite is auto-capped at 45.

What is a good activation rate benchmark by stage?

Seed: median 12%, top-quartile 20%. Series A: median 18%, top-quartile 28%. Series B: median 22%, top-quartile 35%. Series C+: median 28%, top-quartile 42%. Activation compounds every downstream metric — a 10pp lift typically moves trial-to-paid by 3–5pp.

What is a good PQL-to-customer conversion rate?

PQL-to-customer conversion: median 12%, top-quartile 25%, elite 30%+. Enterprise PQL converts at 40–60%. PQL conversion is 3–5× higher than MQL because intent is behavioral. Products with 2–3 well-defined PQL triggers outperform those using single-metric signals.

What is the time-to-value benchmark for PLG companies?

OpenView 2024 TTV benchmarks: median 30 minutes, top-decile 2 minutes, danger zone 24+ hours. Sub-5-minute TTV earns an A. The log-scale scoring means cutting from 2 hours to 30 minutes matters more than from 30 to 10 minutes.

How do you measure PLG expansion revenue and NRR?

NRR = (starting MRR + expansion − contraction − churn) / starting MRR. PLG NRR benchmarks: break-even 100%, healthy 110–120%, elite 130%+. NRR below 90% is severe contraction — fix it before optimizing other PLG dimensions.

What is the difference between PLG and sales-led?

PLG uses the product as the primary driver of acquisition, activation, and expansion — no salesperson needed. Sales-led uses human outreach. Most companies claiming PLG are PLG-Assisted: >50% of revenue still requires a human. The self-serve % input in this calculator is the most honest discriminator.

What is the PLG maturity model and which stage am I at?

PLG maturity stages: Experimental (< 50 composite) — running experiments; Emerging (50–69) — hybrid, mostly sales-led; Scaling (70–84) — PLG dominant, investing in infrastructure; Dominant (85+) — PLG is the competitive moat. Less than 3% of self-described PLG companies reach Dominant.

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