Fake Door Testing

What Is Fake Door Testing? Meaning, Definition & Examples

Fake door testing is a lean validation method where you invite users to try a product, feature, or plan that does not exist yet to gauge demand. Instead of building something and hoping people want it, you measure genuine interest first by presenting what looks like a real option and tracking how many users click.

The “fake door” itself can take many forms: a button, banner, navigation item, popup, or landing page that looks fully real inside a live product or website. The visual aspect matters because it needs to blend seamlessly with your existing product so users interact with it naturally.

Here is what happens after a user clicks: they reach a simple page explaining the feature is in development. This page typically thanks them for their interest and optionally asks for an email or feedback. No deception lingers because you immediately tell them the truth.

Think of it like a store putting up a “Coming soon: new product shelf” sign and counting how many shoppers walk over and ask about it. The sign looks real. The interest is real. The product just is not built yet.

You might hear this technique called painted door tests, facade tests, or smoke tests. These synonyms all refer to the same core idea: validate ideas with real user behavior before investing significant resources in building anything.

Why fake door testing matters

Fake door testing bridges the gap between product-market fit research and actual development work. For product managers, marketers, and founders, it replaces guesswork with behavior data for ideas that are not fully developed.

The technique gives you metrics like click-through rate, signup rate, and scroll depth for features and products that do not exist. This is far more reliable than surveys or user interviews alone, where people often say one thing and do another. When potential users click on something, they are demonstrating initial interest through action.

For teams running conversion rate optimization experiments, fake doors fit naturally into the workflow. You can test a new feature concept alongside existing A/B tests and gather data on what resonates with your target audience.

SaaS and ecommerce businesses that iterate quickly benefit the most. Rather than shipping features that sit unused, you gather meaningful data to prioritize your backlog, test pricing changes, and refine positioning based on evidence.

For CRO tools, fake doors are part of a broader experimentation mindset. You can run fake door tests in the same platform where you personalize experiences and optimize conversions, creating a unified approach to understanding and responding to customer interest.

How fake door testing works

This section walks through the lifecycle of a fake door test from idea to decision.

The core flow is straightforward:

1. Pick a hypothesis about what users want

2. Design a realistic entry point (CTA, menu item, popup, or ad)

3. Route users who click to a “not yet available” page

4. Measure user behavior and analyze results

Teams should define success metrics upfront. For example, you might require a minimum click-through rate of 3% or at least 50 email signups within a one-week test window. Having clear thresholds prevents endless debate about whether results are “good enough.”

Tests can run in multiple contexts:

Analytics from tools like Google Analytics, or product analytics platforms help you decide whether to build, adjust, or drop the idea. The data collected tells you whether to invest engineering resources or move on to the next concept.

What is fake door testing used for?

Fake door testing serves several purposes across product development and marketing teams.

Common applications include:

• Validating entirely new products before writing code

• Measuring market demand for new features or add-ons

• Testing pricing tiers and packaging options

• Exploring interest from new target segments

Secondary uses extend the technique further:

• Building early-access waitlists with early adopters

• Recruiting beta testers for upcoming launches

• Collecting qualitative feedback for product messaging refinement

Growth and marketing teams often combine fake door tests with ads on platforms like Meta Ads or Google Ads to probe new markets cheaply. A fake door landing page can quickly test content and messaging before you commit to a full campaign.

In CRO workflows, fake doors are often combined with A/B tests. One variant contains the fake door while the other does not, letting you measure the impact on overall page performance while validating the new idea.

Benefits of fake door testing

Speed, cost efficiency, and behavioral accuracy make fake door testing a powerful addition to your validation toolkit. You can quickly test new ideas without waiting for development cycles or investing heavily in prototypes.

The key benefits come down to practical advantages that help teams ship better products faster.

Avoiding unnecessary development costs

Teams can evaluate multiple competing ideas using separate fake doors before committing developers. Want to know if users prefer an “AI Automation” feature or “Custom Workflows”? Run both as fake doors and let user interactions tell you which deserves priority.

Concrete benchmarks help here. Require at least a few hundred exposures and a clear uplift over baseline click rates before green-lighting work. This approach is especially valuable for complex capabilities like advanced analytics, recommendation engines, or third-party integrations that consume significant resources to build.

When presenting to stakeholders, frame it as a simple ROI narrative: compare estimated build cost versus projected upside grounded in fake door interest. If 8% of users clicked on a feature concept, that is compelling evidence for allocation of engineering time.

Quick feedback loops

Fake door tests can run for 5 to 10 days and still provide directional data when traffic is sufficient. You do not need months of research to gather reliable insights.

Agile teams can include fake door results as a standing agenda item in sprint reviews or product councils. The data becomes part of regular planning rather than a special research project.

Using fake door testing tools, you can monitor results in real time and pause or tweak tests quickly if needed. Quick loops allow simultaneous exploration and learning while core product work continues unaffected.

Increased stakeholder confidence

Screenshots of real user interactions, click heatmaps, and conversion reports make it easier to argue for or against features with leadership. Rather than debating opinions, you present behavior data.

Include fake door results in roadmap decks as evidence that demand exists for proposed epics or pricing changes. Strong interest helps secure budget and buy in for design, engineering, or go-to-market campaigns before build begins.

Consider storing fake door outcomes in a shared internal knowledge base so future teams see what has already been tested. This prevents duplicating experiments and builds institutional learning.

Enhanced understanding of user behavior

Fake doors reveal where in the interface users expect capabilities to live. Does a “Teams” feature get more interest in the top nav or the account menu? Track user behavior to find out.

Combine click counts with qualitative methods like short on-click surveys asking “Why were you interested in this feature?” This helps teams decide based on both numbers and context.

Analyzing user cohorts (new vs returning, free vs paid, SMB vs enterprise) reveals which segments truly care about the idea. This behavior data can feed directly into personalization engines to tailor offers or follow-up messaging based on demonstrated interest.

When to use fake door testing

Fake doors are most useful early in the lifecycle, before building prototypes or full features. They answer the question “Should we even explore this?” before you invest in answering “How should we build this?”

Ideal use cases include:

• Pre-MVP concept validation for new business idea exploration

• New feature prioritization for mature products with many competing requests

• Pricing and packaging experiments before committing to new plans

• Exploring new verticals or international markets before localizing

Fake doors work best when traffic volume is high enough to reach statistically meaningful sample sizes within 1 to 3 weeks. If your site gets 100 visitors per month, you will struggle to gather enough data for confident decisions.

They are less useful for tiny audiences or mission-critical flows where any perceived deception could create serious trust issues.

Validating product and feature ideas

Use standalone landing pages with clear value propositions and CTAs like “Join the waitlist” to validate brand new products. Buffer famously used this approach in 2010, collecting over 5,000 sign-ups via a fake door landing page before writing code. That early validation sparked their growth to millions in revenue.

SaaS teams can add a disabled menu item like “AI Automation” or “Workflows” in-app to test feature demand before building back-end services. Potential customers who click are showing you where their pain points lie.

Ecommerce brands can experiment with new categories (like “Home office bundles”) as menu items leading to “Coming soon” pages. This helps teams gauge interest before sourcing inventory or creating product photography.

Capture emails and use them to follow up if the feature is built. This turns testers into early adopters who feel invested in the product’s success.

Testing pricing and packaging

Fake doors can help identify interest in new pricing tiers, add-ons, or billing cycles. Want to know if an annual pricing plan with a discount would attract customers? Add it as a fake option and measure clicks.

Test alternative labels and value messaging for the same underlying plan. Does “Growth” or “Pro” resonate more with your audience? Conduct fake door tests on the pricing page to find out.

Clicks on higher-priced plans or add-ons show potential willingness to pay. Combine this with later real pricing experiments for fuller validation.

Use a/b testing tools to show different pricing banners or promo popups to segments and record engagement. This lets you test multiple concepts simultaneously across different visitor groups.

Building beta lists and early-access cohorts

Clicking a fake door can lead to a simple form inviting users to join a beta or early access list for the upcoming feature. This turns a validation exercise into a list-building opportunity.

These lists help product and CX teams recruit interview participants and usability testers before launch. You get beta testers who have already demonstrated genuine interest.

“Founding customer” or “Early partner” messaging often performs better than generic “Coming soon” notices. It makes users feel special and invested.

Tag these users in CRM or marketing automation for focused nurture sequences and future upsell attempts. Their demonstrated interest makes them prime candidates for new customers when the feature launches.

Risks and disadvantages of fake door testing

Fake doors intentionally simulate availability, which carries ethical and UX risks if not handled carefully. Acknowledging these risks upfront helps teams mitigate them effectively.

Main risk categories include:

• User frustration from clicking something that does not exist

• Perceived dishonesty if messaging is not transparent

• Brand damage, especially for early-stage companies still building trust

• Misinterpreted data from curiosity clicks rather than purchase intent

These risks can be mitigated with transparent messaging, limited exposure, and clear internal guidelines. For regulated industries or highly sensitive products, teams may need stricter legal review before running fake doors.

Decide upfront what percentage of audience will see fake doors and for how long. Overuse erodes trust quickly.

Potential user frustration and credibility loss

Users can feel misled when they click a feature or offer that turns out to be unavailable, especially if they needed it urgently. This frustration is real and valid.

Use clear, empathetic copy on the follow-up page acknowledging their interest and explaining why the feature is not live yet. Something like “We are exploring this feature and your click tells us it matters to you” respects users respond better than vague corporate speak.

Consider offering a small gesture to reduce disappointment on commercial sites: educational content, roadmap insight, or a discount code. This turns a potentially negative moment into a positive brand interaction.

Repeated fake doors in the same product area quickly erode trust. If users see “Coming soon” in the same spot multiple times, they stop believing you.

Ethical and brand concerns

There is a real ethical tension between learning what users want and not deceiving them about what is currently available. Teams must navigate this thoughtfully.

Be explicit that the feature is “in development” or “planned” rather than implying it is fully live. Never use fake advertisement tactics that make claims you cannot support.

Young or lesser-known brands must be especially careful. A single poorly executed test can create suspicion about legitimacy that takes months to overcome.

Define and document internal rules for fake door use, including approval steps with product, marketing, and support teams. This prevents rogue experiments that could damage brand reputation.

Limitations of the data

A click indicates interest in the headline, not necessarily long-term usage, retention, or willingness to pay. The data collected from fake doors is directional, not definitive.

Combine fake door metrics with follow-up surveys, user interviews, or later-stage experiments that include real or prototype functionality. This gives you the full picture.

Novelty or curiosity can inflate click rates, especially when the copy is sensational or vague. Someone clicking “Revolutionary AI Feature” might just be curious, not genuinely interested.

Use consistent thresholds and benchmarks across tests to avoid overreacting to small data sets or random spikes. User research should inform interpretation.

How to run a fake door test

This section provides a concise, step-by-step process for running a basic fake door experiment from scratch.

The flow covers: define mission, craft hypothesis, design the fake door, create the follow-up experience, launch, and analyze results.

Before building any asset, teams should align on what decision they will make based on each possible outcome. This prevents post-hoc rationalization of ambiguous results.

Use a standard experiment template to log assumptions, metrics, and learnings for future reference.

1. Decide on the mission and hypothesis

The mission should be a focused question. For example: “Will existing customers use an AI summary feature monthly enough to justify development in Q3 2026?”

Write a testable hypothesis. Something like: “At least 5 percent of active workspace admins who see the new ‘AI Summary’ nav item will click it within 14 days.”

List key assumptions behind the hypothesis:

• Users have pain with current manual summary workflows

• Demand for automation exists in this user segment

• The placement in navigation is discoverable

Document what thresholds will trigger a “build”, “rethink”, or “discard” decision before launching the test. This helps teams decide objectively.

2. Design the fake door

Different types of fake doors work for different contexts:

Make the fake door visually consistent with existing design and interaction patterns so users interact with it as if it were real. The visual aspect should match your brand perfectly.

Use concise, benefit-driven copy on the trigger itself. “Automate reports with AI” works better than vague labels like “New Feature.”

Teams can design fake doors as targeted popups, slide-ins, or embedded widgets without editing code if they use a high-end tool. This removes developer dependencies and lets marketers quickly test concepts.

3. Decide who will see the test

Targeting the right audience matters enormously. Showing a “Bulk Discounts” feature to one-time buyers makes less sense than showing it to store owners who already use discount codes regularly.

Use segmentation rules based on behavior, device, traffic source, or plan type to show the fake door only to relevant users. Testing cohort selection determines result quality.

Good testing tools allow precise targeting. For example: “users who viewed the Analytics page at least twice in the last 7 days.” This ensures you gather data from users who would actually use the feature.

Limit exposure to a subset of users at first, such as 20 to 30 percent of eligible traffic. This reduces risk while still providing enough data to validate demand.

4. Create what is behind the door

The destination should be a simple thank-you or information page explaining that the feature is in development or planned. Never leave users at a dead end.

Include these elements:

• A short description of the planned feature

• 2 to 3 bullet benefits explaining the value

• An optional signup form for early access or updates

• Clear message about timeline (if known)

Use honest, empathetic language: “We are exploring this feature and your click tells us it matters to you.”

Screenshots, wireframes, or a 30 to 60 second concept video can help users understand what is coming and provide better user feedback through follow-up questions.

5. Launch, monitor, and follow up

Soft-launch the test first. Verify tracking (clicks, views, signups) is working correctly, then expand to the full test audience.

Monitor performance daily in analytics dashboards. Watch for:

• Unexpected traffic spikes

• Technical bugs affecting display

• Negative feedback to customer support

Plan email or in-product follow-ups for users who opted in. Include updates, surveys, or invites to beta programs.

Close the loop when the test ends. If you decide not to build the feature, let signups know, thank them, and share what you are doing instead. Transparency maintains trust.

6. Analyze results and decide

Compare actual metrics (click-through rates, form completions, feedback sentiment) to your predefined thresholds and hypotheses.

Segment results to find where interest is strongest:

• By user type (free vs paid, new vs returning)

• By traffic source (organic vs paid vs referral)

• By device (desktop vs mobile)

Top tools can export data to analytics platforms or BI tools for deeper analysis.

Document key learnings, next steps, and how many users showed interest. Record how the data influenced roadmap decisions in a short experiment summary that future teams can reference.

How to run in-app fake door tests

This section focuses on SaaS products, web apps, and logged-in experiences rather than marketing landing pages.

In-app tests are powerful because they measure interest from active users who already understand the product context. These users have demonstrated commitment by logging in, making their behavior more predictive of actual adoption.

In-app fake doors can be delivered as tooltips, modals, slide-ins, or new menu items controlled by no-code tools. You do not need to modify your codebase to run experiments.

FD testing tools can trigger different fake doors based on behavior rules. For example: “after user completes 3 orders” or “after 2 sessions in 7 days.” This precision targeting helps teams gauge interest from the most relevant users.

Segment your target audience

Target users most likely to benefit from the potential feature. When testing a “Bulk Discounts” feature, focus on store owners who already use discounts rather than casual shoppers.

Use product analytics or CRM data to build segments like:

• Power users of Feature X

• Customers with more than 100 sessions in the last month

• Enterprise accounts with multiple team members

• How many users fit your ideal customer profile

Tools for FD testing allow building these segments using conditions like pages visited, events triggered, and location.

Exclude new users in onboarding flows if the test is about advanced or power features. Showing complex new functionality to first-time users creates confusion rather than valuable insight.

Pick the right in-app location

Choose the page or view where the new feature would naturally live. An “Analytics” feature belongs on reporting screens, not buried in account settings.

Consider contextual placement options:

Testing tools can place widgets on specific URLs, product sections, or based on scroll position to keep context relevant.

Use simple triggers like “after 5 seconds on the Analytics page” or “when user hovers over Export menu” for maximum relevance.

Create the in-app fake door content

Use concise copy focusing on the main benefit (“View customer journeys automatically”) instead of technical implementation details. Users care about outcomes, not architecture.

Include a single primary action button like “Try it” or “Get early access.” Avoid multiple competing CTAs that dilute the signal.

You can use templates that can be styled to match brand fonts, colors, and UI components for a seamless experience. The fake door should feel native to your product.

A/B test different headlines or visuals within the fake door itself. This helps you understand which value framing resonates more with users before building anything.

Plan the follow-up experience

Users should never hit a dead end. Always show a dedicated message or modal after the fake door click.

Give users a clear next step:

• Joining a waitlist for updates

• Voting on feature priorities

• Watching a short concept demo video

• Providing qualitative feedback on what they hoped to accomplish

There are workflows in fake door testing tools that can trigger follow-up widgets or email capture forms automatically after the click event.

Route any support questions about the fake feature to a prepared help article or macro. This keeps messaging consistent and prevents confusion among support staff.

Measure success and refine

Key in-app metrics to track:

Run tests for a fixed window, such as 7 to 14 days or until reaching a minimum of several hundred exposures, depending on traffic volume.

Several tools' dashboards show performance by segment, device, and traffic source. Use these insights to refine targeting for future tests.

One in-app fake door test often leads to follow-on experiments. Strong results might warrant deeper pricing tests, UX prototypes, or beta testing programs.

Tools for fake door testing

Several categories of tools combine to execute fake door tests effectively.

Primary tool categories:

The right stack depends on where the fake door lives (site, app, ads, email) and how sophisticated tracking needs to be.

Some tools can often replace multiple tools for on-site and in-app tests by combining widgets, segmentation, A/B testing, and analytics in one platform.

Prioritize tools that allow non-technical users to launch and iterate tests quickly. Developer bottlenecks slow down experimentation cycles.

Using fake door testing tools

These tools enable marketers and product teams to create fake doors as modals, slide-ins, top bars, or embedded CTAs without writing code. This removes friction from the testing process.

Key capabilities of fake door testing tools:

• Precise segmentation: Target based on behavior, traffic source, device, and location

• Built-in A/B testing: Compare different messages, designs, or placements for the same fake feature

• Real-time analytics: See impressions, clicks, and conversions as they happen

• No-code editing: Design and launch without developer support

Analytics in fake door testing tools show results immediately, so teams can evaluate interest and stop or scale tests quickly. No waiting days for data exports.

Fake door testing examples

Real-world examples show how different companies use fake doors to validate ideas before building.

SaaS feature validation

A B2B SaaS company wanted to gauge user interest in usage heatmaps. They added a “Usage Heatmaps” item in their analytics navigation that led to a “This feature is in development” page.

The approach:

• Tracked click-through rate among admin users over 10 days

• Collected emails from those wanting beta access

• Used a/b testing tool to target the prompt only to power users

The result: High engagement from enterprise accounts convinced the team to prioritize the feature for the upcoming quarter. The data gave product managers confidence to allocate engineering resources.

Pricing and packaging experiment

A SaaS business wanted to test a higher-priced tier without committing to new sales processes. They added a “Scale” tier card on their pricing page that was not yet available for purchase.

The approach:

• Clicking the card opened a modal asking users to talk to sales or join a pilot program

• Measured clicks and form submissions over two weeks

• Used testing tool to show this experimental tier only to visitors from high-intent sources

The result: Strong form completion rates from visitors arriving via competitor comparison pages validated the pricing strategy. The team moved forward with developing the tier.

Ecommerce category and bundle test

An ecommerce store considered launching “Remote work starter kits” but did not want to source inventory without proof of demand.

The approach:

• Added the category into main navigation as a fake door

• Category led to a landing page stating kits were coming soon

• Offered email signup for launch-day discounts

The result: Strong engagement convinced the merchandising team to assemble and photograph real bundles. Segmentation showed higher interest from visitors arriving via specific ad campaigns, guiding future targeting and ad spend.

Buffer’s famous fake door MVP from 2010 remains a classic example. They created a landing page for a nonexistent social media scheduling tool and garnered over 5,000 signups through Twitter promotion. This validation happened before any coding, ultimately sparking their growth trajectory.

Fake door testing and related concepts

Fake door testing relates to several other experimentation and validation methods. Understanding these connections helps teams choose the right approach.

Fake doors usually come before or alongside A/B testing, prototypes, and traditional user research methods. They answer “Is there interest?” before you answer “What is the best implementation?”

Fake doors are a type of Pretotyping, intended to validate demand before investing in any form of working solution. Other pretotyping methods include Wizard of Oz tests (manually simulating functionality) and fake door mvp approaches.

Fake door testing vs a/b testing

These techniques serve different purposes in the product development process.

A typical flow: run fake door tests to validate demand, then build a minimum version and A/B test variations of UI or messaging.

Famous testing tools support both patterns by enabling fake doors and traditional A/B tests within the same interface. This creates a seamless progression from validation to optimization.

Clearly label experiments internally to avoid confusing concept validation with optimization tests. These require different success criteria.

Fake door testing and feature flags

Feature flags control rollout of actual working features. Fake doors present features that do not yet exist. The distinction matters for how fake door tests work in your development pipeline.

Once a fake door shows strong interest and the feature is built, feature flags can manage its gradual release to segments. This creates a continuous learning loop from concept through launch.

Many teams track metrics consistently from fake door stage through flagged release. This reveals whether initial interest translates to actual usage and retention.

Experimentation and flagging strategies should be documented together so teams understand the entire lifecycle of a feature from validation through full rollout.

Key metrics for fake door testing

Clear metrics make the difference between a useful test and a confusing one.

Core quantitative metrics:

Supportive metrics to consider:

• Bounce rate on the follow-up page

• Time on page (indicates reading vs immediate exit)

• Scroll depth (shows engagement with content)

• Repeat visits (suggests strong interest)

Collect qualitative input through short questions like “What were you hoping this feature would help you do?” This gather user feedback adds context to the numbers.

Set numeric thresholds before the test. Industry benchmarks suggest 2 to 5 percent CTR often indicates viable demand, while below 1 percent typically signals the idea should be reconsidered.

Best practices and tips for fake door testing

Careful design, ethical handling, and disciplined analysis make fake doors both powerful and safe to use.

Practical do’s

Be transparent after the click. Clearly state that the feature is not yet available and thank users for their interest. Honesty protects trust.

Start with small segments. Begin with 10 to 20 percent of eligible traffic and gradually increase exposure if results are positive and UX impact is acceptable.

Pair with existing research. Combine fake door data with user interviews, NPS comments, or sales feedback. The full picture emerges from multiple sources.

Use no-code tools. No-code platforms let marketers and PMs iterate quickly without developer bottlenecks. Speed matters for learning.

Document everything. Record hypotheses, results, and decisions. This builds organizational learning and prevents repeated experiments.

Common don’ts

Never promise specific dates. Making commitments you cannot keep damages credibility. Keep timelines vague until you are confident.

Avoid misleading copy. Do not overstate current capabilities or hide that the feature is in development. Meet user expectations honestly.

Stay away from critical flows. Running fake doors on checkout, login, or other essential paths risks conversion and trust. The stakes are too high.

Do not rely on raw click counts. Always normalize for impressions, segments, and baseline click behavior. Context matters for interpretation.

Limit concurrent tests. Decide how many fake doors any single user can see to avoid clutter and distrust. One per context is usually best.

Use fake door testing effectively

Fake door testing is a lean technique to quickly measure real user interest in unbuilt ideas using realistic CTAs and follow-up pages. It helps teams decide whether to build based on behavior, not opinions.

The approach helps teams prioritize roadmaps, pricing experiments, and marketing bets while reducing wasted development. Features that nobody clicks never consume engineering resources.

Ethical transparency, careful targeting, and clear pre-defined thresholds are critical to protecting user trust. Done well, fake doors build credibility by showing users that their feedback shapes product direction.

A good tool can bring together segmentation, no-code widgets, A/B testing, and analytics to run fake doors efficiently on websites and web apps. Teams can launch tests in hours and have actionable data within days.

Start with a small, low-risk fake door in the next two to three weeks. Pick a feature idea that has been debated but not validated. Build the habit of testing before building, and watch your product development process become more efficient and user-centered.

Key takeaways

• Fake door testing presents a CTA, page, or widget for a non-existent feature or product to measure real user interest through clicks and signups.

• It is a fast, low-cost lean technique for validating product ideas, pricing, and features before any engineering work.

• Ethical, transparent messaging is critical to protect brand reputation and user experience when users hit the “not available yet” page.

• Tools let teams create, A/B test, and target fake doors on sites and web apps with no-code widgets and real-time analytics.

FAQs about Fake Door Testing