Users see an empty screen and don't know what to do
Empty states kill activation. Users can't imagine what "done" looks like. Show them a working example they can edit instead of starting from nothing.
When to use
Your product has a blank canvas problem—users need to add their own data before it becomes useful. Common in project tools, CRMs, trackers, and dashboards.
Hypothesis template
If we pre-fill new accounts with [sample data/template], then activation will increase because users immediately see a working product instead of a blank canvas.
Method
The problem: New users sign up, see an empty dashboard, and leave. They know your product does something useful—they just can't figure out how to get from zero to useful.
What Airtable did: Every new workspace comes with sample data—a pre-built project tracker, content calendar, or CRM depending on what you chose during signup. Users see a working product instantly and can edit it rather than building from scratch.
The result: Airtable reached 300k+ organizations. Their template-first approach means users experience the "aha moment" in seconds instead of spending 20 minutes setting up a blank base.
How to do it:
- Identify your product's "aha moment"—what does it look like when someone is getting value?
- Create 2-3 sample datasets that showcase that moment (e.g., a project tracker with realistic tasks, a CRM with sample contacts)
- Pre-fill new accounts with the most relevant sample data
- Make it obvious this is sample data ("This is example data—edit or delete it to make it yours")
- Add inline hints: "Try dragging this card" or "Click here to add your first real item"
- Let users clear all sample data with one click when they're ready
Key insight: Nobody wants to stare at an empty screen. A pre-filled product shows users the finish line before they start running.
Success metrics
- •Time to first meaningful action
- •Activation rate (first value moment)
- •Sample data interaction rate
- •Drop-off at empty state vs. pre-filled state
Prerequisites
- Clear understanding of your aha moment
- Ability to create realistic sample data
- A way to distinguish sample data from real data
Common pitfalls
- •Sample data that feels fake or irrelevant
- •No way to clear sample data easily
- •Too much sample data (overwhelming)
- •Sample data that doesn't match the user's use case
Source: Airtable. Template-first onboarding helped reach 300k+ organizations.
Suggested ICE scores
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