Flicker Effect

What is the Flicker Effect?

The flicker effect, also known as FOOC (Flash of Original Content), is a visual glitch in client-side A/B testing. It occurs when a user briefly sees the original version of a webpage before the variation loads. The result is a quick flash of one design, then another.

This happens because variation changes are applied through JavaScript after the browser starts rendering the original page. If that delay is noticeable—even for a fraction of a second—it can make the site feel broken or confusing.

What Causes the Flicker Effect in A/B Tests?

The flicker effect is typically caused by:

• Asynchronous test scripts that load after the page begins rendering
• Delayed JavaScript execution, especially if placed late in the page
• Unoptimized assets (e.g., heavy images or unused JS libraries)
• Redirects or slow variation code in the testing setup

Some experimentation tools are more susceptible to flicker than others. For example, client-side tools that inject variation code after the page load are more prone to it than tools that block rendering until everything is ready.

How the Flicker Effect Impacts Experiments

Even brief flickers affect how users perceive your site. Research shows the human brain can process images in as little as 13 milliseconds. If the user sees one version of a page, then another, it can:

• Break trust or introduce confusion
• Cause users to bounce before engaging
• Skew results by creating mixed experiences
• Lead to false positives or inflated metrics in rare cases

You lose control over what the user actually experienced, and that undermines the entire point of running a controlled test.

“Although it’s not ideal for user experience, a well-optimized experiment setup can significantly reduce the flicker effect. From my perspective, the flexibility and speed of client-side testing often justify this tradeoff, especially when it empowers both technical and non-technical teams to execute rapid experimentation. However, monitoring the flicker effect’s influence on user behavior is important by tracking metrics like bounce and exit rates. Severe flicker or load speed issues could detract from the user experience, ultimately hindering the variant’s performance and skewing test results.”

Nina Bayatti, Director of Conversion Rate Optimization at ClassPass

How to Reduce or Prevent Flicker

To reduce flicker, you need to eliminate delays between when the original page loads and when the variation appears. Start with:

1. Load variation scripts as early as possible
Place the A/B testing snippet in thetag to ensure it’s prioritized during page load.

2. Use synchronous loading
Tools like Convert Experiences use SmartInsert™ to load both the script and the content synchronously. This creates a visual “layer” that hides the original content until the variation is ready.

3. Optimize your codebase

• Remove unnecessary JS libraries
• Use lazy loading for images
• Consolidate and streamline variation code
• Only load test code on relevant pages

4. Avoid redirects
Redirect-based experiments introduce extra load time and increase the risk of flicker. If possible, use inline updates or server-side logic.

5. Use a high-performance SDK
Some tools offer lightweight SDKs that enable fast, inline client-side changes with minimal impact on rendering.

Client-Side vs Server-Side: The Flicker Tradeoff

Client-side testing introduces flicker because changes are applied after the page loads in the browser.

Server-side testing eliminates flicker by rendering the variation before the content reaches the browser.

Server-side testing requires more developer support but offers a more stable user experience, especially for high-stakes or high-traffic pages.

How to Detect the Flicker Effect

There’s no alert for flicker. You have to look for it.

Here are a few ways to catch it:

• Manual QA testing across devices and browsers
• A/A tests to check for baseline layout stability
• Monitoring bounce and exit rates on test variations
• Session replays to visually confirm what users saw
• User feedback that references “glitches,” “flickering,” or “weird load behavior”

The earlier you catch it, the easier it is to fix and the more accurate your test data will be.