---
title: "How to A/B Test a Hero Section in Next.js"
description: "The hero section is the highest-leverage, lowest-risk place to run a first A/B test — here's how to scope it so the test is actually clean."
canonical: https://landtest.dev/blog/ab-test-hero-section-nextjs
last-updated: 2026-10-30
---

# How to A/B Test a Hero Section in Next.js

> The hero section is the highest-leverage, lowest-risk place to run a first A/B test — here's how to scope it so the test is actually clean.

A/B testing a hero section in Next.js is one of the cleanest tests to run because it's usually a single, well-isolated component above the fold — the main risks are layout shift from swapping variants after render and picking a metric that only measures engagement with the hero itself rather than what happens after it. Done well, this is a good first test for a team new to A/B testing: contained scope, clear hypothesis (headline, subhead, or CTA framing), and low risk of the cross-page complexity that pricing or onboarding tests introduce.

## Isolate the component, not the page

Structure the variant so only the hero component differs, with everything below it — nav, footer, rest of the page — identical between variants. This keeps the test's effect attributable to the one thing you're actually testing, rather than confounded by unrelated differences elsewhere on the page:

```tsx
// page.tsx
import { Hero } from "./hero"; // swapped per variant, rest of page shared

export default function LandingPage() {
  return (
    <>
      <Hero />
      <Features />
      <Footer />
    </>
  );
}
```

## Avoid layout shift from the swap

If hero height differs meaningfully between variants (a shorter headline, a different CTA layout), a client-side swap after initial render can cause visible layout shift below the fold — everything shifts down or up as the hero resizes. Server-side or deploy-layer variant assignment avoids this because the browser only ever receives the final layout; if you're testing client-side, reserve consistent height across variants or accept the CLS cost as a known tradeoff.

## Measure past the hero, not just engagement with it

Scroll-past rate or hero CTA click rate are useful diagnostics but not the metric that matters — the actual goal (signup, demo request, purchase) downstream of the hero is. A variant that increases hero CTA clicks but doesn't change downstream conversion has probably just made the CTA more prominent without actually improving the pitch; worth knowing, but a different finding than "this headline converts better."

## Keep the hypothesis specific

"Test a different headline" isn't specific enough to act on the result. "Test whether leading with the outcome (what the product does for the user) outperforms leading with the mechanism (how the product works) for this specific audience" gives you something to act on regardless of which variant wins, because you learn about the audience, not just about two arbitrary pieces of copy.

## FAQ

**Is the hero section a good first A/B test?**
Yes — it's usually well-isolated as a single component, has a clear and specific hypothesis available (headline, subhead, CTA framing), and carries lower risk than tests spanning multiple pages or touching auth/signup flows.

**Does swapping hero variants cause layout shift?**
It can, if variants differ in height and the swap happens client-side after render. Server-side or deploy-layer assignment avoids this since the browser only receives the final variant.

**What should I measure in a hero section test?**
The actual downstream goal (signup, demo request, purchase), not just hero CTA click rate or scroll-past rate, which measure engagement with the hero itself rather than whether it actually improved conversion.

---

Related: [A/B test a pricing page in Next.js](/blog/ab-test-pricing-page-nextjs) · [Best A/B testing tools for Next.js developers](/blog/best-ab-testing-tools-nextjs-developers) · [Landtest for A/B testing](/ab-testing)