4.4.5 Value Proposition Test - Fake Door

At a Glance
Other names 404 Test · Feature Stub · Painted Door Test · 404 Page Test
In Brief
A fake door test is a button, link, or advertisement for a product or feature that does not yet exist, placed in front of an audience to measure interest by counting how many people click it. A click is a behavioral signal — an action rather than a stated opinion. It is commonly used to test new feature ideas inside an existing product or to validate a concept with external ads before committing to build it.
Common Use Case
You have an idea for something new — a feature, a product, a service — but do not want to invest time and money building it if nobody cares. You present it as if it already exists (a button, a link, an ad) and measure how many people try to get it, which tells you whether real demand exists before you commit resources.
Helps Answer
- Are customers interested enough to click on this offer?
- Which audience segment is most attracted?
- Which words, icons, or images generate the most engagement?
Description
A fake door test presents a button, link, or ad for a product or feature that does not yet exist, then counts how many people click it. Because clicking is an action rather than an opinion, it sits a rung above a passing glance on the Value Proposition Test ladder — the person who clicks has chosen to act, even if all they have committed is the click itself. You place the door, count how many people try to use it, and read the result as a measure of real behavior rather than stated intent. The click-through rate — the share of viewers who click — tells you whether demand is real.
There are two types:
- Internal fake door — A button or menu item inside your existing product. Tests whether current users want a new feature. Example: adding a “Switch to map view” button on a page that only has a list view.
- External fake door — A paid ad or social post for a product that doesn’t exist yet. Tests whether a target audience is interested in a concept. Example: running a Facebook ad for an online community to see if anyone clicks.
Don’t use fake doors to test essential functionality (like registration flows) or your core value proposition. Use them to test additions and new directions.
Ethics — You are showing people something that does not exist. Keep it honest. The reveal page should clearly say the feature is in development and offer to notify them when it is ready. A few fake doors help you avoid building things nobody wants; many dead-ends in a short span erode trust.
How to
Prep
1. Write your hypothesis.
State what you expect to happen. Be specific: “At least 5% of users who see the button will click it” is testable. “People will be interested” is not.
2. Decide: internal or external.
- Internal (in your product): Best for testing new features with existing users. Requires adding a button or link and a tracking event. Fastest to set up.
- External (paid ads): Best for testing a new concept with a new audience. Requires an ad account and a landing page. More expensive but reaches people who don’t know you yet.
- Hybrid (ad → landing page with fake CTA): Tests both audience interest and messaging. The ad proves they’ll click; the CTA proves they’ll act.
3. Set your success threshold before you launch.
Decide what click-through rate counts as a win. Benchmarks:
- Internal buttons/features: 2–5% CTR is typical for in-product UI elements. Above 5% is strong interest.
- External ads: Industry average CTR for Facebook ads is ~1%. Google Search ads average ~3–5%. Beat the channel average to call it a win.
- Landing page CTAs: 5–10% email signup rate from a cold audience is solid.
If you don’t set a threshold up front, you’ll rationalize any result as success.
4. Set a target sample size.
You need enough views to trust the click-through rate:
- For a rough directional signal: 200+ views minimum.
- For a confident comparison between variants: 500+ views per variant.
- Use a sample size calculator (see References) if you need precision.
- If your traffic is very low (under 200 views): Run the test longer, use external ads to supplement traffic, or combine the fake door with qualitative follow-up (interview the people who clicked). A 10% CTR on 50 views is a signal worth investigating, even if it’s not statistically conclusive.
5. Design the fake door.
Rules:
- Make it look exactly like a real feature would look. Same font, same placement, same style. If you make it flashier or bigger than normal UI elements, you’re measuring novelty, not interest.
- Write the label/copy in the same language you’d use for a real feature. No hype.
- If testing multiple variants (different copy, different placement), run them sequentially or split traffic evenly.
6. Design the reveal page.
What users see after they click. Options:
- “Coming soon” page — Explains the feature is in development. Offers email signup for notification. Best for features you might actually build.
- “Help us prioritize” page — Short survey asking why they clicked and what they’d expect. Best for early exploration.
- Simple thank-you — “Thanks for your interest. We’re exploring this idea.” Minimal but honest.
Always include: a clear explanation that the feature doesn’t exist yet, and a way for the user to continue what they were doing without frustration.
7. Set up tracking.
- For in-product fake doors: Add a click event to your product analytics. Track both views (impressions) and clicks.
- For external ads: The ad platform tracks CTR automatically. Also track visits to the reveal page and any email signups.
- For both: Record the date range, total views, total clicks, and any segmentation data (user type, device, source).
- Before launching: Test the tracking yourself — click the fake door and confirm the event appears in your analytics. This is the most common reason fake door tests produce no usable data.
Execution
1. Launch the fake door.
Deploy it exactly as designed. Don’t tweak the copy or placement after launch — changes mid-test invalidate your data. If you realize something is wrong (broken link, tracking not firing), fix the bug but note the date and exclude pre-fix data.
2. Wait.
Set a deadline based on your traffic estimate. For internal fake doors, run for at least one full week to account for day-of-week variation in usage patterns. Don’t check results hourly — it leads to premature conclusions. Check once at the halfway point to verify tracking is working, then again at the end.
3. Collect qualitative data from the reveal page.
If your reveal page includes an email signup or survey, monitor responses. If several people leave the same comment or question, that’s signal about what they expected.
Analysis
1. Calculate the click-through rate.
CTR = clicks ÷ views × 100. This is your primary metric.
2. Compare against your pre-set threshold.
- Above threshold: The concept has enough interest to justify further investment. Move to the next validation step (solution interview, pre-sales, or build).
- Below threshold but close: Consider testing a different copy variant, placement, or audience before giving up. A 3% CTR when you needed 5% might mean your messaging is off, not that demand is zero.
- Well below threshold: The concept doesn’t resonate with this audience. Either pivot the concept or try a different audience.
3. Segment if possible.
If you have enough data, break CTR down by user type, device, or traffic source. A feature that gets 8% CTR from power users but 1% from new users tells you something different than a flat 3%.
4. Check for confounds.
- Did something else change in the product during the test period?
- Was there a spike in traffic from an unusual source (press mention, viral post) that diluted the signal?
- Was the fake door placed in a high-traffic area that gets incidental clicks (near a navigation element, close to a scroll path)?
5. If your sample was small (under 200 views): Treat the CTR as directional. Follow up with 5–10 interviews of people who clicked (or didn’t) to understand why. A small-sample fake door plus qualitative interviews is often more useful than a large-sample fake door alone.
- Copy bias The words on the button matter enormously. “Try our new dashboard” and “See your analytics” will get very different click rates for the same feature. Test at least two copy variants if you can.
- Location bias A button at the top of the page gets more clicks than one at the bottom, regardless of interest. If possible, test the same door in multiple positions.
- Novelty bias Users click new things because they’re new, not because they want them. A spike in the first day that drops off quickly is novelty, not demand. Look at sustained CTR after the first 48 hours.
- Click ≠ commit CTR overstates real demand. A click is the lowest possible signal of interest. Always follow a successful fake door with a higher-commitment test (signup, pre-order, deposit) before building.
- Polished-reveal deception AI page builders produce reveal pages that look production-ready by default, making a “coming soon” stub feel indistinguishable from a real product page. Visitors who cannot tell the difference feel deceived when they discover the feature does not exist, eroding trust in the product. Consciously roughen the reveal or label it plainly as exploratory.
- Concurrent-test saturation AI makes it trivially easy to spin up many fake doors at once. Running multiple concurrent tests on a small audience simultaneously dilutes the click signal across concepts and compounds trust erosion: visitors who hit several dead-end stubs in one session lose confidence in the product faster than a single test would warrant.
Learn more
Case Studies
Polyvore: “Buy this outfit” fake door
Polyvore added a “buy this outfit” button with no store behind it. Over three months, about 2 in every 100 people who saw an outfit clicked to buy, and orders were handled by hand before any payment system was built.
Notino: Language-switcher fake door
Notino, a multi-country European beauty retailer, placed a visible language switcher on its Swiss site to measure interest in localization. About 3.5% of visitors clicked it, giving real behavioral data before committing to translation work.
Zynga: Pitch-ad demand testing inside live games
Zynga tests prospective games by running short pitches inside its existing games and through ads, measuring how many current players click before any production work begins.
Tippiq: Dedicated fake-door lab site
Dutch aggregator Tippiq ran a separate site, tippiqlabs.nl, where new ideas were tested with paid ads pointing at description pages. Interested visitors saw a “still in development” notice and could leave their email. (Tippiq’s dedicated fake-door lab site has since been discontinued.)
Further reading
- Alberto Savoia — The Right It (HarperOne, 2019)
- Alberto Savoia — Pretotyping resources
- Eric Ries — The Lean Startup (Crown Business, 2011)
- Marty Cagan — Inspired, 2nd ed. (Wiley, 2017)
- Jess Lee — Fake Doors: How to Test Product Ideas Quickly (Hustlecon 2013)
- Amplitude — What Is Fake Door Testing: Methods and Best Practices
- Chameleon — Fake Door Testing: How it Works, Benefits & Risks
- Kromatic — Experiment Calculator
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