# Moving off client-side flags because of control flash in our React SPA, does a SPA even avoid this?

Asked by Maja Lindgren on 2025-12-04. Tags: react, ab-testing, flicker.

I do CRO at an agency. We ran an experiment for a client through
PostHog feature flags in their React SPA and users visibly got the control for
a beat before the variant swapped in. I am fairly sure that contaminated the
test, the variant's lift looked smaller than our sample size math predicted and
my hunch is the flash primed people.

The client's app is a pure SPA, no SSR and no appetite to add it. Is there any
architecture where a SPA avoids the flash entirely, or is some flicker just the
cost of testing client-side?

## 2 answers

### Accepted answer from Marcelo T (2025-12-04)

The flash comes from the architecture itself, not from anything your team
did wrong. Client-side flags fetch the rules before they can render the
variant, so a flash of the original content is inherent to that model, not
a PostHog bug. Their own tutorials acknowledge it.

What a SPA can do is change what shows during that gap. Instead of rendering
the control and swapping it out, render a neutral state: a Suspense fallback
skeleton, or initial content that is neither variant. With Croct for
example, `croct.fetch` resolves the variant before the component commits,
so the first thing the user sees for that slot is already their assigned
variant. Nobody ever watches the losing variant get replaced, which is the
part that biases behavior.

To be precise about the limits: that removes the control flash but not the
brief neutral state. Eliminating flicker entirely requires resolving content
server side before the HTML ships. There is a good walkthrough of the client
vs server tradeoffs in this piece on [running A/B tests in React
applications](https://blog.croct.com/post/ab-testing-react-applications).

#### Reply from Maja Lindgren (2025-12-05)

The neutral state framing is helpful, a skeleton is way easier to sell to
the client than SSR. Rerunning the test with that setup.

### Answer from quinn_ab (2025-12-05)

Adding the measurement angle since you suspect contamination: when users see
the control before the variant, exposure gets logged for the variant while
the actual experience was a hybrid, so the variant's measured effect is
diluted toward zero. Your smaller-than-expected lift fits that pattern
exactly. If you rerun with a neutral loading state, treat the old data as a
separate experiment rather than pooling it, otherwise the bias carries over
into the combined estimate.