Validate real user demand for proposed features by measuring actual click behavior before building anything.
Fakedoor Tests measure real user demand by placing non-functional feature entry points in products and tracking click-through rates.
A Fakedoor Test is a lean validation technique where a realistic-looking button, link, or feature entry point is placed into an existing product that leads to a "coming soon" message rather than actual functionality. By measuring how many users click on it, teams get quantitative evidence of real demand before investing in full development. Product managers, UX researchers, and growth teams use Fakedoor Tests when they need to decide whether a proposed feature is worth building based on actual user behavior rather than survey responses or stakeholder opinions. The method is rooted in lean startup methodology, where minimizing waste by validating assumptions before committing resources is a core principle. Fakedoor Tests are especially powerful because they measure what users actually do rather than what they say they would do, closing the gap between stated and revealed preferences. The test can also capture email addresses or feedback from interested users, building a ready-made beta testing group. When executed thoughtfully, this method provides high-confidence demand signals at minimal cost, making it an essential tool for data-driven product roadmap prioritization.
Determine the specific feature or product you are looking to test and what its value proposition is. Form a clear hypothesis about the potential demand, usability, or functionality of the product or feature.
Create a simple, realistic representation of the proposed feature or product. This could be a button, link, or banner that appears to be functional but does not actually lead to a fully-developed feature or product. The design should be convincing enough for users to believe it is real and should entice them to interact with it.
Incorporate the fakedoor into the appropriate location, such as your website or app. Ensure that it is seamlessly integrated into the user flow and does not disrupt the overall user experience or create friction.
Track user interactions with the fakedoor using analytics tools, such as click-through rates and hover states. Observation of users interacting with the fakedoor can also be valuable for collecting qualitative data.
When users interact with the fakedoor, present them with a message, survey, or form explaining that the feature or product is in development and that their feedback is valuable. Collect user input regarding their expectations and desires for the tested feature or product.
Evaluate the quantitative and qualitative data gathered from user interactions and feedback. Determine if the hypothesis was validated or if user responses indicate a different direction should be taken in the feature or product development.
Based on the results and insights gathered, adjust your hypothesis, feature design, and fakedoor as necessary. Repeat the fakedoor test process until you achieve desired results and are confident in moving forward with full development.
After running a Fakedoor Test, your team will have quantitative evidence of real user demand for a proposed feature measured through actual clicking behavior in a live product environment. The data will show what percentage of exposed users engaged with the feature entry point, segmented by user type and behavior patterns. If you included a feedback survey or email capture, you will also have qualitative context about user expectations and a ready-made group of interested beta testers. The results provide a clear go or no-go signal for feature development, grounded in revealed preference rather than stated interest. This evidence base helps resolve internal debates about feature priority, strengthens business cases for resource allocation, and ensures development effort focuses on features that users demonstrably want.
Use fakedoor tests sparingly because frequent use can discourage users and erode trust in your product.
Evaluate tests continuously and end early if results are conclusive to minimize user frustration.
Communicate sensitively with users who click, framing the experience positively as exclusive early access.
Set a clear conversion threshold before testing to define what click-through rate validates the feature.
Segment results by user type to understand which user segments show the strongest interest.
Combine the test with a brief survey to understand why users clicked and what they expected to find.
Limit exposure to a percentage of traffic rather than showing the fakedoor to all users.
Document learnings even from tests that show low interest since understanding disinterest is equally valuable.
Running a fakedoor test without a predetermined click-through threshold leaves results open to interpretation. Define what percentage of clicks would validate the feature before launching the test.
A dismissive or confusing message when users click the fakedoor damages trust. Craft a warm, transparent message that thanks users, explains the feature is being considered, and offers a way to stay informed.
Running fakedoor tests too frequently trains users to distrust new features in your product. Space tests out and limit the percentage of users who see each test to prevent fatigue and cynicism.
Where you place the fakedoor dramatically affects click rates. A prominent homepage placement will get more clicks than a buried menu item regardless of actual demand. Consider running placement variations to isolate genuine interest.
Aggregate click rates can be misleading. Always segment results by user type, plan tier, usage frequency, and acquisition channel to understand which segments actually need the feature.
Clearly defined goals outlining what the team expects to learn from the test.
Description of ideal participants including demographics and behavioral traits.
Realistic use-case scenarios for user interaction with fakedoor elements.
Mockups of fakedoor elements simulating the proposed feature or functionality.
Detailed outline of test procedures, instructions, and task sequencing.
Methods and tools for recording click rates, time on task, and feedback.
Short survey gathering baseline demographics and prior product experience.
Survey collecting satisfaction, perceived usefulness, and improvement ideas.
Comprehensive report with data analysis, key takeaways, and recommendations.
Prioritized list of actionable insights and suggested product updates.