Fake Door Test experiment

Tomáš Veselý - podpořen AI
1 day ago
4 min read

We're building a comprehensive knowledge library about product development as part of our mission. The library is for anyone looking to make better decisions — primarily decisions about product development. Whether you're an inventor, a product manager, or a Chief Product Officer, using the right research methods and experiments increases your chances of building the right things for the right audience. Today we'll introduce the Fake Door Test validation method.

When to Use This Experiment?

This method is a good fit when you need to verify market interest in a product or one of its variants at minimal cost. Instead of building, you first test whether the product can be sold at all.

There's a product idea, but it's unclear whether there will be demand for it.
Several messaging or positioning variants are in play, and you need to find out which one resonates most.
It makes sense to verify willingness to pay before investing in the product.
Targeted traffic (ads, communities, email) can be driven to a dedicated page.

Basic Experiment Principles

The principle is to present the product as if it was finished — one or more simple landing pages are built with a clear message and a purchase button that doesn't yet do anything real. Genuine interest is measured by the number of clicks on the button.

Prepare the page. Create a simple one-page presentation of the product: the problem it solves, its unique benefits, and the reason someone should buy it. It's worth preparing several variants for different messages or price points.
Add the fake button. Place a call to action ("Buy", "Try", "Order") and a pricing table. After the click, a "coming soon" page appears with the option to leave an email.
Drive traffic. Deliver targeted traffic through ads, communities, or email campaigns, ideally in a way that lets the individual variants be compared against each other.
Collect data. Track the number of unique visits, call-to-action clicks, and emails submitted. The decisive signal is the conversion rate from landing on the page to clicking the fake button: if it significantly exceeds typical industry values and one of the messaging or pricing variants repeatedly wins, demand is confirmed and you can move on to development. A low number of clicks across all variants, on the other hand, tells you the problem lies in the message or in the level of interest itself.
Identify the risks. The method measures declared interest (clicks, email), not actual purchases — a click is not the same as a payment. The quality of the signal depends entirely on the quality of the traffic you drive; poorly targeted ads will distort the result. Small samples give direction, not statistical certainty. And there's an ethical line to keep in mind: advertising a nonexistent product as finished can damage trust, which is why a transparent "coming soon" page is a good idea.

Real-World Experiment Example

Link to research: Idea to Paying Customers in 7 Weeks: How We Did It

Buffer founder Joel Gascoigne wanted to validate the idea for a Twitter post-scheduling tool before he started building it. So in 2010 he launched a two-page site: the first page explained what the product did, and a "Plans and Pricing" button led to a page inviting visitors to leave their email. He tracked how many people clicked through and submitted their contact details.

Once it was confirmed that there was interest in the product, he added one more page between the two — with a pricing table. That single extra click tested two things at once: willingness to pay (based on which plan a person clicked) and the strength of interest (anyone who clicks this far means it). People kept clicking through, and some of them chose paid plans.

This signal was enough for Gascoigne to start building a minimal version of the product, which he finished in seven weeks of evenings and weekends. Buffer launched on November 30, 2010, and the first paying customer arrived within four days of launch.

What Can Be Tested With This Experiment?

The main value of this method is that it reveals the real market interest in a product or service.

Demand (desirability): whether the presented problem exists and people are looking for a solution to it; the signal is an above-average number of clicks from an ad to the fake purchase button.
Strength of the message: which formulation of the benefit and positioning resonates; the signal is a higher conversion rate for one page variant compared to the others.
Willingness to pay: whether the idea is valuable even for money; the signal is clicks on pricing plans or the "Buy" button, not just on a general sign-up.
Price point: which price best matches the perceived value; the signal is the distribution of clicks across the offered plans.
Target audience: which segment responds most; the signal is the difference in conversion between ad campaigns aimed at different audiences.