You’re running a smart, sleek email campaign. You’ve A/B tested your heart out. But the results look… weird. Sloppy. Not quite what you expected? Well, you’re not alone. A/B test automations can break in mysterious ways. But don’t worry—we’ll figure it out together.
TL;DR (Too Long, Didn’t Read)
A/B tests go sideways when things aren’t properly randomized, or when people get bounced between test versions. Long campaign flows can make this worse. Always double-check how splitting works in your tool. Lock assignments early and avoid re-checking conditions mid-flow.
Why Do A/B Test Automations Malfunction?
A/B tests should be simple: split your group, send different content, see which one wins. But in long automations, things can go off the rails.
Here are the biggest culprits:
- Improper Randomization – People are not always evenly or consistently split.
- Conditional Triggers – Users might change behavior mid-journey, getting reassigned.
- Flow Reentries – If they loop through your flow again, they might switch groups.
- Delayed Actions – Timing issues can blur the boundaries between A and B versions.
Let’s break that down with some friendly examples—and learn how to fix it.
Improper Randomization: The Core Problem
Think of a magician pulling rabbits from a hat. Half of them should be white, the other half black. But what if he pulls just white ones for the first 5 minutes? Not very fair, right?
That’s what happens in your automation flows when randomization isn’t truly random. If split logic runs based on some dynamic user data (like city, page visits), you might unknowingly create bias.
Example: You have a flow that sends Offer A to users who signed up on weekdays and Offer B to weekend users. But weekends have fewer signups! Hello, uneven split.
How to Fix It:
- Use a random number generator or pre-built random split tool in your automation platform.
- Assign users to variants at entry—not mid-flow.
- Avoid splitting with behavioral conditions unless neutral and permanent.
Users Changing While in Flow
This one’s sneaky. Imagine if someone starts in Group A because they haven’t bought anything yet. But halfway through your campaign, they make a purchase. So they get moved to Group B’s path.
Now you have a monster: half-A-half-B users. Their data messes everything up.
How this Happens:
- You base A/B logic on user behavior that can change (like purchases, site visits).
- Your automation tool reassesses users at every step.
- You don’t “lock” users into a group after assigning them.
How to Fix It:
- When a user enters, assign them a tag or variable like “AB-Test=A”. Never touch it again.
- Use fixed segment membership instead of dynamic rules.
- Don’t let reactive logic interfere once split is set.
Bottom line? Keep the user’s group permanent. Like sorting hats in Harry Potter. Once Gryffindor, always Gryffindor.
Flow Reentry and Looping Users
In long campaign flows, people might leave and come back days or weeks later. Or worse, your system might re-enroll them when they requalify.
Now imagine a loop where someone jumps between versions like a pogo stick. Bye-bye, reliable data.
What Causes It:
- Flows that allow reentry on every visit.
- Campaigns that don’t check for previous assignment.
- Custom code that overwrites groups on each loop.
How to Avoid It:
- Limit access: only allow entry once per user per test.
- Use conditions to block reentry if they already have a test tag.
- Store the test assignment in a way that flows can read and respect it.
Getting consistent user journeys is key. Nobody wants half their sample doing yoga in two different flows.
Time-Based Actions Can Slip
A/B tests often include wait steps. “Send email A, then wait 3 days, then send follow-up.” Sounds chill, right? But if something changes during that wait—uh oh.
The user might qualify for a different branch… or skip a crucial step. It’s like switching lanes in traffic without signaling.
What to Do:
- Combine time delays with locked segments.
- After the split, avoid adding new conditional forks based on changing data.
- Use parallel branches instead of evaluative branches.
You want your test to be as controlled as a science fair volcano. Not a surprise lava eruption.
Best Practices for Reliable A/B Testing in Long Flows
Let’s round things up with golden rules you can stick on your wall.
- Split early. Assign A/B groups right at the start.
- Lock user paths. Use permanent tags, flags, or custom fields to commit to a group.
- Prevent reentry. Use filters to keep users from cycling back in.
- Don’t mix logic. Keep test paths separate and controlled.
- Watch your timing. Long waits + changing data = confusion.
- Name things clearly. A/B tags like “Test_Group=A” help you debug later.
- Use analytics outside the automation when needed. Sometimes it’s clearer in a dashboard.
Cool Tips & Tools
Want to level up your split game? Try using:
- UUID modulus logic: Split based on if their ID % 2 == 0 for Group A, odd for B. Super random.
- Custom user properties: One-time set fields won’t change mid-flow.
- Third-party testing tools: Use analytics platforms to double-check split accuracy.
Also, never trust the first 24h of test data. People flood in unevenly. Let the magic settle in.
Conclusion
A/B testing in automation flows sounds easy. But long flows add complexity. People shift, change behavior, reenter flows—and your data takes the hit.
The solution? Lock things early. Avoid mid-flow randomness. Keep your conditions clean and your paths uncluttered.
Follow these tips, and your A/B tests will be as sharp as ever. No more mystery results. Just sweet, clean insight.
Now go forth and split like a champ.