What Is Fake Door Testing: Methods And Best Practices

Fake door testing creates UI elements that look functional but don’t actually work. When customers interact with these fake doors, teams track the engagement to measure interest in proposed features.

The method goes by several names. Painted door testing refers to the same technique—the "painted door" looks real but doesn’t open. Some teams refer to it as a phony door or simply a door test. These terms all describe the same validation approach.

Here’s how it works: You add a labeled "Export to PDF" in your analytics dashboard, even though that feature doesn’t exist. When customers click it, they see a message saying "Coming soon—join our waitlist." The number of tells you whether PDF export is worth building.

A fake door test measures intent, not satisfaction. Unlike usability testing or customer interviews, door tests capture what people actually do when they encounter a feature option. This behavioral data often differs from what customers say they want.

The technique works best for discrete features that customers can understand from a simple description or button label. Complex workflows or multi-step processes don’t translate well to fake doors because customers can’t fully evaluate them from a single entry point.

A door test follows a simple sequence: present the fake element, track interactions, then reveal the truth transparently.

Customers see the testing door sign

The fake door appears as a realistic element within your product. Common formats include:

• Buttons: "Enable dark mode" or "Connect to Slack"
• Menu items: New options in or settings
• Toggles: Feature switches that appear functional
• Banners: Promotional messages for upcoming capabilities
• Landing pages: Full pages describing nonexistent products

The element looks and feels like part of your existing interface. Customers encounter it naturally while using your product, without knowing it’s part of an experiment.

Click tracking and data collection

When someone clicks the fake door, your analytics system records the interaction. Key data points include:

• Who clicked: Customer ID, account type, subscription level
• When they clicked: Timestamp and
• Where it appeared: Page location, device type, referral source
• How many times: Single clicks vs. repeated attempts

This click data becomes your primary demand signal. High click rates indicate strong interest, while low rates suggest weak demand or poor positioning.

Post-click transparency

After clicking, customers are directed to a disclosure page that explains the situation. Effective post-click messages include:

• Clear explanation: "This feature is in development"
• Timeline estimate: "Expected launch: Q2 2024"
• Interest capture: Email sign-up for updates
• Easy exit: Clear path back to their original task

The disclosure maintains trust by being upfront about the test. Customers appreciate honesty and often willingly join waitlists when they understand the purpose behind them.

Fake door testing works best in specific scenarios where you need before committing resources.

Feature demand validation

Use a door test when you’re unsure whether customers actually want a proposed feature. Place the fake element where customers would naturally expect to find that functionality.

For example, if you’re considering adding team collaboration features, put a "Share with team" button in your interface. Track how many people click it and compare engagement across different customer segments.

The key is testing features that customers can understand from minimal context. Avoid complex workflows that require extensive explanation or multi-step processes.

Pricing and packaging experiments

Door tests help evaluate willingness to pay for different feature tiers or add-ons. Create fake pricing cards or upgrade prompts to measure interest in premium capabilities.

You might test whether customers would pay for advanced analytics by showing an "Upgrade for custom reports" button. Click rates across different price points reveal sensitivity to pricing changes.

This approach works particularly well for freemium products where you’re considering which features to gate behind paid plans.

Beta tester recruitment

A fake door test can identify your most engaged customers for . People who click on upcoming features demonstrate a high level of interest and make ideal early adopters.

When someone clicks your fake door, route them to a beta sign-up form instead of just a "coming soon" message. These volunteers often provide better feedback than randomly selected testers.

Fake door testing offers several advantages over other validation methods:

• Low resource investment: Creating fake UI elements requires minimal design and development work compared to building .
• Behavioral evidence: Click data reveals what customers actually do, not what they claim to do in surveys or interviews.
• Quick results: You can gather meaningful data within days or weeks, much faster than full feature development cycles.
• Segment insights: Click patterns reveal which customer types show the strongest interest, informing targeting decisions.
• Risk reduction: Testing demand before building prevents wasted effort on unwanted features.

The method works particularly well when combined with other research techniques. Use fake doors to quantify demand, then follow up with customer interviews to understand the "why" behind the clicks.

Fake door testing carries reputation risks if not handled transparently. Customers who feel deceived may lose trust in your brand and product.

Managing customer expectations

The most significant risk comes from customers expecting immediate access to advertised features. When they discover the feature doesn’t exist, disappointment can turn into frustration or anger.

Minimize this risk through clear communication. Use language that suggests exploration rather than availability: "Interested in PDF export?" instead of "Export to PDF now." Visual cues, such as "Coming soon" badges, help set appropriate expectations.

Maintaining transparency

Always disclose the test nature immediately after customers click. Your post-click message should:

• Acknowledge the fake door experiment
• Explain why you’re testing demand
• Offer value in return (beta access, updates, feedback opportunities)
• Provide an easy path back to their original task

Transparency builds trust even when customers encounter fake doors. Many appreciate being part of the product development process when the reasoning is clearly explained.

Limiting exposure and frequency

Avoid overwhelming customers with multiple fake doors or running tests for extended periods. Too many fake elements create a frustrating experience and can damage your product’s credibility.

Target fake doors to relevant customer segments rather than your entire user base. Someone who’s never used reporting features probably shouldn’t see fake analytics options.

1. Define your hypothesis and success metrics

Start with a clear hypothesis about customer demand. Write it as a testable statement: "Enterprise customers will click ‘SSO integration’ at a 15% rate or higher."

Set specific success criteria before launching. What click-through rate would convince you to build the feature? What conversion rate from clicks to waitlist signups indicates strong demand?

Define your test duration and . Plan to run the test long enough to achieve but not so long that customers become frustrated with the fake element.

2. Target the right audience

Use customer segmentation to show fake doors to relevant users. If you’re testing an enterprise feature, target business plan customers rather than individual users.

Create that don’t see the fake door. This baseline helps you understand whether clicks represent genuine interest or just normal exploratory behavior.

Consider the stage when targeting your audience. New users may not fully understand your product, making it difficult for them to evaluate advanced features, whereas power users can more effectively assess complex capabilities.

3. Design the fake element

Create a realistic but clearly labeled entry point. The element should fit naturally within your existing interface without feeling out of place.

Use descriptive labels that help customers understand what the feature would do: "Export data to CSV" is clearer than "Export data." Include enough context for informed clicking without over-explaining.

Position the fake door where customers would logically expect to find that functionality. Don’t hide it in obscure locations or force it into unrelated workflows.

4. Create a transparent follow-up

Design a clear post-click experience that maintains customer trust. Your disclosure page should blend seamlessly into your product, rather than feeling like a jarring error message.

Offer something valuable in return for their interest, such as early access, product updates, or the opportunity to influence feature development. Make joining optional—never force email capture or account creation.

Provide a clear path back to their original task. Customers shouldn’t feel trapped or confused about how to continue using your product.

5. Measure and analyze results

Track multiple metrics beyond simple click-through rates:

• Unique vs. total clicks: Repeated clicks may indicate higher interest or confusion.
• Time to click: Immediate clicks suggest strong interest; delayed clicks might indicate discovery through exploration.
• Post-click behavior: Do customers immediately leave or continue using your product?
• Segment differences: Which customer types show the strongest engagement?

Compare results against your predefined success criteria. Avoid moving goalposts after seeing results—stick to your original hypothesis and thresholds.

Fake door testing sits between surveys and full product development in terms of investment and data quality.

Fake doors capture intent to try something, while capture actual usage patterns. Surveys tell you what customers think they want; door tests show what they actually click on.

Use fake door testing when you need quick demand signals before committing to development. Follow up successful tests with MVPs to validate usability and satisfaction.

Most fake door tests can be implemented with basic web development tools and . You don’t need specialized software for simple button-based tests.

Point solutions like Optimizely offer landing page testing capabilities but typically require separate analytics integration to track long-term customer behavior. These tools work well for external marketing tests but provide limited insight into in-product behavior patterns.

can show or hide fake elements for specific customer segments. However, they usually don’t include comprehensive analytics for understanding and retention patterns.

Amplitude’s digital analytics platform combines with behavioral analytics in a single system. This integration enables teams to track fake door clicks alongside customer lifecycle metrics, retention patterns, and revenue impact—providing a complete picture of how interest signals translate into business outcomes.

Successful fake door tests generate customer interest that you can act on. The transition from validation to development requires careful planning to maintain momentum and trust.

Use your to identify which customer segments showed the strongest interest in the fake door. Create cohorts based on engagement patterns and prioritize development for high-value segments first.

When you’re ready to build the real feature, consider a using feature flags. Start with customers who clicked the fake door and joined your waitlist—they’re most likely to adopt the new capability quickly.

Track for the real feature and compare them to your fake door test results. This comparison helps you understand how interest signals translate into actual usage, improving future door test interpretation.