If you’re running outbound sales and just guessing which messages work—stop. You’re leaving conversions on the table. This guide is for anyone using Regie who wants to actually know what’s moving the needle, not just hope. I’ll break down how to A/B test sales sequences in Regie, what matters (and what doesn’t), and how to avoid the classic mistakes that waste time and confuse results.
Why A/B Test Sales Sequences (and Why Most People Get It Wrong)
Most sales teams think “A/B testing” means writing two random email templates and seeing which one gets more replies. That’s not testing—that’s gambling. A proper A/B test is about isolating one variable, measuring real results, and making calls based on data, not gut feelings.
The good news: Regie (regie.html) actually makes this pretty doable, if you set things up right. The bad news: It’s easy to get lost in the weeds or chase statistical ghosts. So let’s get practical.
Step 1: Get Clear on What You’re Testing
Before you start fiddling in Regie, figure out what you actually want to learn. Here’s what matters:
- One variable at a time. Subject line, call-to-action (CTA), opening sentence—pick one.
- Don’t test everything at once. If you change multiple parts, you won’t know what made the difference.
- Focus on conversions, not vanity metrics. Replies and meetings booked matter. Open rates? Meh—thanks to email privacy, they’re mostly noise.
Pro tip: Write down your hypothesis. “I think a shorter subject line will get more replies.” That keeps you honest.
Step 2: Set Up Your A/B Test in Regie
Setting up an A/B test in Regie isn’t rocket science, but there are a few gotchas. Here’s how to do it without tripping over your own feet:
- Build your base sequence.
- Create your sales sequence as usual.
- Decide which step you’re testing (e.g., first email, follow-up, etc.).
- Duplicate the step you want to test.
- Most people just edit the content—don’t do that. Use Regie’s “Add Variation” or “Duplicate Step” feature so you’re tracking side-by-side.
- Edit the variable.
- Change just the thing you’re testing. If it’s the subject line, only touch that. Leave the rest identical.
- Assign prospects randomly.
- Don’t cherry pick. Use Regie’s randomization tools or manually assign leads evenly across both versions.
What to skip: Don’t bother running a test if you only have a handful of leads. You need enough volume (think: at least 100+ per variation) to see real patterns instead of random blips.
Step 3: Decide What Success Looks Like
If you don’t know what result would make you change your approach, stop and figure that out first. Here’s what to track:
- Primary metric: Replies or meetings booked. Period.
- Secondary metric: If you really want, track open rates or click-throughs, but don’t hang your hat on them.
- Statistical significance: Don’t nerd out on stats formulas, but don’t jump at tiny differences either. If one version gets 10% more replies after a few hundred sends, you’re onto something. If it’s a 1% swing, flip a coin.
Pitfall alert: Don’t end tests early just because one version “looks better” after 20 sends. Give it time. Patterns settle in after 100+ real-world attempts.
Step 4: Launch—and Leave It Alone
Let your test run. Seriously. Don’t tweak things mid-flight, or you’ll muddy the waters.
- Keep sending prospects through both variants until you hit your target sample size.
- Resist the urge to “optimize” halfway through. If you see one email lagging, don’t swap it out. Finish the test.
What doesn’t matter: Seasonality, day of week, small sample blips. Unless you’re running massive campaigns, the basics matter more than chasing perfect timing.
Step 5: Review Results Honestly
Once your test wraps, look at the numbers, not your feelings.
- Did one variant get more replies or meetings—by a real margin?
- Is the difference meaningful for your business? (A 0.5% lift on a tiny list won’t change your world.)
- Spot-check replies. Sometimes one version gets more responses, but they’re all “unsubscribe me” or spam complaints. That’s not a win.
If there’s a clear winner, great—roll it out. If it’s a toss-up, either version is fine. Move on and test something else.
What’s Worth Testing (and What’s a Waste of Time)
A/B testing is powerful, but only if you focus on stuff that moves the needle. Here’s what’s usually worth your effort:
Worth Testing
- Subject lines: Quick wins, but don’t expect magic.
- First sentence/opening hook: Sets tone for the whole message.
- Call-to-action: “Book a call this week?” vs. “Open to chat?”
- Sequence timing: Spacing between steps can matter, but only after you’ve nailed the basics.
Skip or Do Sparingly
- Emoji vs. no emoji: Unless your audience loves them, this is mostly noise.
- Tiny wording tweaks: “Hey John,” vs. “Hi John,” will not double your conversions.
- Design tweaks: For plain-text sales emails, pretty formatting rarely matters.
- Testing lots of things at once: You’ll end up chasing your tail.
Common Mistakes to Avoid
- Testing too many things at once. You’ll get confusing, useless results.
- Declaring victory too early. Tiny sample sizes don’t prove anything.
- Ignoring reply quality. More replies isn’t better if they’re all negative.
- Chasing open rates. Email privacy changes have made these numbers mostly fiction.
Pro Tips for Better A/B Tests in Regie
- Document everything. If you don’t keep track of what you tested, you’ll repeat yourself (or forget what worked).
- Rotate what you test. Once you’ve optimized subject lines, move on to other elements. Don’t get stuck endlessly tweaking the same thing.
- Share results with your team. Let others learn from your hits and misses—no need for everyone to reinvent the wheel.
- Automate what you can. Regie can handle random assignment and reporting—use those features so you’re not stuck in spreadsheets.
Keep It Simple—And Keep Testing
A/B testing in Regie isn’t about chasing perfection or finding some “secret” formula. It’s about steady, real improvements—one tweak at a time. Focus on the big levers, ignore the noise, and don’t let perfect be the enemy of good. Launch, measure, learn, repeat.
You don’t need to test everything. Start with your biggest question, run a clean experiment, and let the data do the talking. Simple wins, every time.