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Troubleshooting

Why Your A/B Test Isn't Working (And How to Fix It)

February 18, 2025
12 min read

Your test has been running for two weeks. The confidence level is stuck at 47%. Nothing is happening. Sound familiar? Here's what's probably wrong — and how to fix it.

Quick Diagnosis

Before diving into specifics, check these first:

Is the test actually running? (Check status in your tool)
Are both variants receiving traffic? (Check visitor counts)
Are conversions being tracked? (Check conversion counts)
Can you see the variant yourself? (Test in incognito)

The 8 Most Common Problems

1

Not Enough Traffic

Symptoms

  • Test running for weeks with no significance
  • Confidence jumping between 30-70%
  • Results that keep flipping

Cause

Your sample size is too small to detect the effect you're testing for.

Fix

Either run longer, test a bigger change, or focus on higher-traffic pages. Use a sample size calculator before starting.

2

Testing Too Small a Change

Symptoms

  • Variant looks almost identical to control
  • Expecting 2-3% lift
  • Button color changes

Cause

Small changes need massive sample sizes to detect. A 5% improvement requires 10x more traffic than a 50% improvement.

Fix

Test bigger, bolder changes. Headlines, value props, layouts — not button colors.

3

Stopping Too Early

Symptoms

  • Stopped when you saw 95% confidence on day 3
  • Results flipped after you stopped
  • Different result each time you check

Cause

Early results are unreliable. Statistical significance can appear and disappear as data accumulates.

Fix

Calculate required sample size before starting. Commit to that duration. Don't peek.

4

Wrong Goal Tracking

Symptoms

  • Conversions not registering
  • Numbers don't match other analytics
  • Zero conversions recorded

Cause

Goal tracking isn't set up correctly. The event isn't firing, or it's firing for the wrong action.

Fix

Test your goal tracking before launching. Click the button yourself and verify it registers.

5

Flicker Contaminating Results

Symptoms

  • Users see original then variant
  • Content flashes on page load
  • Variant users behave like control

Cause

Users are seeing both versions, contaminating the test. They're no longer a clean variant group.

Fix

Use a tool with proper anti-flicker implementation. Or add an anti-flicker snippet.

6

Testing the Wrong Page

Symptoms

  • High-traffic page but low conversions
  • Goal is 3 clicks away from test
  • Testing top of funnel, measuring bottom

Cause

The page you're testing is too far from the conversion event. Too many variables between test and goal.

Fix

Test pages closer to the conversion. Or use micro-conversions (clicks, scroll depth) as goals.

7

Variant Not Loading

Symptoms

  • Analytics show 0 variant visitors
  • Variant never appears when you test
  • Only control is being served

Cause

Technical issue preventing the variant from loading. Could be script error, targeting issue, or caching.

Fix

Check browser console for errors. Verify targeting rules. Clear cache and test in incognito.

8

External Factors Skewing Results

Symptoms

  • Big spike in one variant mid-test
  • Results don't match historical patterns
  • Unusual traffic sources

Cause

Something external affected one variant more than the other. Holiday, press mention, ad campaign.

Fix

Check for external events. Segment by traffic source. Consider restarting the test.

Prevention Checklist

Before launching any test, verify:

Calculated required sample size
Tested goal tracking manually
Previewed variant on multiple devices
Checked for flicker issues
Set a fixed end date (no peeking)
Documented hypothesis and expected outcome

When to Stop a Failing Test

Technical issues that can't be fixed without restarting
Major external event contaminated results
Variant is clearly hurting conversions significantly
Business needs require the page to change immediately

Most Tests Aren't Broken — They're Underpowered

The #1 reason tests "fail" is insufficient sample size. Before assuming something is broken, calculate whether you've had enough visitors to detect the effect you're looking for.

When in doubt: run longer, test bigger changes, or focus on higher-traffic pages.

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