Your product has 5,000 signups this month. Sales is celebrating. Marketing is reporting growth metrics. Product is tracking DAUs.
But nobody's asking the most important question: How many of those signups actually experienced value?
This is the activation gap—the difference between users who create accounts and users who achieve meaningful outcomes using your product. In traditional enterprise software sold through sales, activation happens through dedicated onboarding specialists and CSMs. In product-led growth, activation must happen automatically, at scale, without human touch.
Product marketers own a critical piece of this: defining what activation means, measuring how well it's happening, and partnering with product to improve time-to-value.
After working with dozens of PLG companies on activation optimization, I've learned: teams that clearly define activation metrics and instrument them properly grow 3-5x faster than teams who track vanity metrics like signups.
Here's how to build activation metrics that actually drive PLG growth.
Why Signups Don't Matter
Most companies celebrate signup volume: "We got 2,000 signups this month!"
Great. How many of them will still be using your product in 30 days? How many converted to paid? How many became advocates?
Signups are the start of the funnel, not a success metric. What matters is activation: the moment when a user experiences core product value and decides your product is worth using regularly.
The activation metrics framework:
Signup → Activation → Retention → Monetization → Advocacy
Skip activation, and the rest falls apart. Unactivated users don't retain. They don't pay. They don't refer others.
Defining Your Activation Milestone
Activation isn't arbitrary. It's the specific action or set of actions that correlates with long-term retention and monetization.
The discovery process:
Step 1: Hypothesize value delivery moments
What actions indicate a user has experienced core value?
- For project management: Created project, added tasks, assigned to teammate
- For analytics: Connected data source, viewed first insight
- For communication: Sent message, got response
- For design tools: Created design, shared with collaborator
List 5-7 candidate actions that might indicate activation.
Step 2: Analyze retention cohorts
Pull retention data for users who completed each candidate action vs. those who didn't.
Example analysis:
- Users who completed Action A: 45% retained at Day 30
- Users who completed Action B: 62% retained at Day 30
- Users who completed Action C: 23% retained at Day 30
Action B correlates strongest with retention. That's likely your activation milestone.
Step 3: Validate with monetization data
Do users who complete your suspected activation milestone convert to paid at higher rates?
If Action B drives retention but users still don't pay, you might need composite activation (Action B + Action D).
Step 4: Set time boundaries
Activation must be achievable quickly, ideally in first session (under 10 minutes). If your milestone requires hours of work, break it into smaller interim milestones.
The Activation Metrics You Need to Track
Once you've defined activation, instrument these metrics:
Metric 1: Activation Rate
Formula: (Users who reached activation milestone / Total signups) × 100
What it tells you: What percentage of signups are experiencing value
Benchmarks by product type:
- Simple tools (Calendly, Loom): 40-60%
- Medium complexity (Notion, Figma): 25-40%
- High complexity (data platforms, dev tools): 15-30%
How to improve:
- Simplify onboarding flows
- Remove friction in key workflows
- Provide better in-product guidance
- Set clearer expectations during signup
Metric 2: Time to Activation
Formula: Median time from signup to activation milestone
What it tells you: How quickly users reach value
Benchmarks:
- Best-in-class: Under 5 minutes
- Good: 5-15 minutes
- Needs improvement: 15-30 minutes
- Problem: Over 30 minutes
How to improve:
- Pre-populate sample data
- Reduce required input fields
- Auto-connect integrations
- Skip non-essential setup steps
Metric 3: Activation Completion Rate by Step
Formula: % of users completing each step in activation workflow
What it tells you: Where users drop off during activation
Example drop-off analysis:
- Signup to first login: 85%
- First login to account setup: 70%
- Account setup to first core action: 45%
- First core action to activation milestone: 30%
Biggest drop: Account setup to first core action. That's where to focus optimization.
Metric 4: Activated User Retention
Formula: Day 7/Day 30 retention rate for activated vs. non-activated users
What it tells you: Whether activation predicts retention
Target: Activated users should retain at 3-5x rate of non-activated users. If they don't, your activation milestone may be wrong.
Metric 5: Activation-to-Paid Conversion
Formula: (Activated users who convert to paid / Total activated users) × 100
What it tells you: Whether activation drives monetization
Typical range: 10-25% for freemium products, 30-50% for free trials
If activation rate is high but conversion rate is low, users experience value but don't see enough value to pay.
Activation Segments: Not All Users Activate the Same Way
Different user segments may need different activation milestones:
By user role:
- Individual contributors: Activate by completing personal workflows
- Managers: Activate by seeing team collaboration value
- Executives: Activate by viewing aggregate insights
By use case:
- Use case A users: Activate via feature set 1
- Use case B users: Activate via feature set 2
By company size:
- Solo users: Activate individually
- Team users: Activate when multiple teammates join
- Enterprise users: Activate when integrations connect
Track activation rates by segment to identify which segments activate well (double down) vs. poorly (fix or deprioritize).
Creating Activation Dashboards
Build dashboards that make activation metrics visible to all teams:
For product teams:
- Activation funnel with drop-off rates at each step
- Time-to-activation distribution
- Activation rate trends over time
For marketing teams:
- Activation rate by acquisition channel (which channels bring users who activate?)
- Activation rate by campaign/messaging (which messaging drives activatable users?)
For sales teams:
- PQL identification: Activated users from target accounts
- Expansion opportunities: Activated users ready for upsell
For leadership:
- Overall activation rate trend
- Activated users vs. signup volume
- Retention rate for activated vs. non-activated users
Activation Experiments to Run
Experiment 1: Onboarding flow variations
Test different onboarding sequences:
- Version A: Tutorial first, then product
- Version B: Product first, tutorial optional
- Version C: No tutorial, in-context tips
Measure: Activation rate and time-to-activation
Experiment 2: Sample data vs. blank slate
Test whether pre-populated data helps:
- Version A: Empty product on first login
- Version B: Sample data showing what success looks like
Measure: Activation rate (sample data usually wins)
Experiment 3: Progressive vs. all-at-once setup
Test information collection timing:
- Version A: Complete profile upfront before product access
- Version B: Skip to product, collect profile data progressively
Measure: Signup-to-activation rate (progressive usually wins)
Experiment 4: Social proof in onboarding
Test whether showing other users' success helps:
- Version A: Generic onboarding
- Version B: "500 teams activated this week" social proof
Measure: Activation completion rate
Common Activation Measurement Mistakes
Mistake 1: Defining activation too early in the journey
Creating an account isn't activation. Completing profile isn't activation. These are setup steps, not value delivery.
Mistake 2: Defining activation too late
Requiring users to complete 10 actions before "activation" means most users will never activate. Keep it achievable in first session.
Mistake 3: Tracking only aggregate activation rates
"Our activation rate is 35%" tells you nothing about who activates and why. Segment by user type, source, and behavior patterns.
Mistake 4: Not connecting activation to business outcomes
Activation metrics must connect to retention and revenue. If you can't show "activated users retain 4x better and convert 3x more," you're tracking the wrong metric.
Mistake 5: Set-and-forget activation definition
As your product evolves, what constitutes value delivery changes. Revisit activation definition quarterly.
The Activation Optimization Playbook
Week 1: Baseline current state
- Define activation milestone
- Measure current activation rate
- Calculate time-to-activation
- Identify drop-off points
Week 2-3: Fix biggest drop-offs
- Find step with largest abandonment
- Hypothesis why users drop there
- Ship improvement
- Measure impact
Week 4: Test alternative flows
- Design 2-3 onboarding variations
- A/B test with new users
- Measure activation rate difference
Week 5-6: Optimize time-to-value
- Remove non-essential steps
- Pre-populate data where possible
- Simplify input requirements
- Re-measure time-to-activation
Week 7-8: Segment analysis
- Identify which segments activate best/worst
- Double down on best segments
- Fix or deprioritize worst segments
Repeat this cycle continuously. Activation optimization is never done.
The Reality
Activation is the most important metric most PLG companies under-invest in. They obsess over signups (top of funnel) and revenue (bottom of funnel) while ignoring the critical middle: getting users to value quickly.
The companies that win at PLG don't have 10x better products. They have 2x better activation rates and 3x faster time-to-value. That compounds into massive growth advantages.
As a product marketer, you can't build the product. But you can define what success looks like, measure how well it's happening, and drive the cross-functional focus needed to improve it.
That's the activation game. And it's the most leveraged work you can do in PLG.