Have you ever had difficulty choosing between two ideas?
Ever switch up a strategy just to realize you couldn’t tell if it made a difference?
Then welcome to the wonderful world of A/B testing, the battleground where strategies compete to see which works better. When done right, the winner is always you!
The fact is, small changes add up. An A/B testbench helps you gradually find the stronger of two options. Applied over many tests, these gradual improvements can yield compounding gains.
Change a headline or tweak an offer, and you can grow revenue without increasing ad spend. A/B testing helps you make those calls with hard data, honing your marketing with each finding.
This guide explains what A/B testing is, when to use it, and how to run simple, reliable tests that support real business decisions.
What Is A/B Testing?
In marketing, A/B testing is defined as an experiment with two variants of the same asset designed to measure which performs better. This approach is a simple but effective method for gathering data and scaling your marketing efficiency.
You can A/B test nearly any aspect of your ecommerce website and marketing efforts, including:
- Forms and checkout steps
- Product titles and descriptions
- Email subject lines and body copy
- Call-to-action (CTA) buttons
- Product and landing pages
- Offer structures
A/B testing works best when you ground it in a specific and measurable business goal.
When the results are in, you can double down on the winner or pit it against the next contender. We recommend maintaining at least one active testbed at all times to continue evolving your approach.
Simple A/B Test Example: Sales Ad CTA
Let’s say you’re planning on running an ad to generate higher sales volume but can’t decide whether to end on a call-to-action to “Learn more” or “Buy now.”
Unsure which message your audience will respond to, you test both versions for 30 days and track the results to see if one leads to more sales.
There are two main outcomes:
- One option outperforms the other. You know to go with the winner moving forward, and you learn something about your audience’s preferences.
- E.g., If “Learn more” performs better, it could signal that your audience prefers taking time to consider purchases over impulse buying.
- E.g., If “Learn more” performs better, it could signal that your audience prefers taking time to consider purchases over impulse buying.
- There’s no meaningful difference between options. This is still valuable info! You learn that your audience is either evenly divided or doesn’t respond strongly to either message.
- If your audience is divided across measurable lines—like demographics or purchase history—it could signal two distinct customer bases.
- E.g., Past buyers respond better to “Buy now,” while new customers show a preference for “Learn more.”
- If your audience is divided across measurable lines—like demographics or purchase history—it could signal two distinct customer bases.
The margin of how much one option has to outperform the other to consider it significant depends on what you’re measuring, but you’ll typically want to clock at least a 5% difference in outcomes.
Why Business Owners Should Care
In short, A/B testing keeps your marketing strategy in a state of constant improvement. The data you gain helps cut through assumptions and noisy projections with hard evidence, replacing wasteful guesswork with actionable results.
Despite the test’s simplicity, its implications are far-reaching and include:
- Compounding gains: A 5–10% gain over several tests adds up to serious revenue growth.
- Accessibility: You don’t need a big budget or expensive focus group to test an offer or headline. Many email automation and advertising platforms offer on-site split testing functions.
- Risk management: A/B testing is a smart pilot study before fully committing to a new direction. You can use it to test the waters before a big decision or rebrand.
- Strategic insights: Winning messages often reveal what your customers actually value.
When Marketers Recommend A/B Testing—and Why
If your marketing team has been begging you to let them run A/B tests, it’s probably because these testbeds are among the most cost-effective marketing investments available.
Most marketers recommend A/B testing for:
- Increasing conversion rates (turning more visitors into buyers or leads).
- Improving engagement (earning more clicks, longer time on page, higher email click-throughs).
- Reduce bounce, churn, and cart abandonment (keep more people moving forward).
- Compare offers or messages (e.g., free shipping vs. 10% off).
However, A/B testing is also highly recommended before any major marketing or website decision (or whenever performance has plateaued and you need fresh, low-risk wins).
Consider running an A/B pilot study before:
- Major site changes that need proof-of-concept before proceeding
- Entering a new market or targeting a new audience
- Launching an expensive paid ad campaign
A/B testing takes the guesswork out of growth decisions. It lets you prove what works with your audience—right now—so you can invest with confidence.
What Makes a Good A/B Test (in 6 Steps)
As a business owner, you don’t need to know every detail of how an A/B test runs, but you do need confidence that the process is solid. These six steps outline what makes a test reliable, so you know your team’s efforts are driving real results.
1) Starting with a clear objective
Every good test begins with a clear business goal like getting more checkouts, more form fills, or more email clicks. Defining a clear objective ensures your team is focused on improvements that directly support your KPIs.
2) Changing one thing at a time
To know what’s really working, your team should be testing one change—such as a headline, image, or button—at a time. That way, you can see exactly what moved the needle.
3) Collecting enough data
Small numbers can be misleading. Your team will let the test run long enough to gather a fair amount of activity before drawing conclusions. If traffic is low, they may test bigger differences so results are clearer.
4) Giving the test time
Stopping too soon often leads to false signals. Most website tests run for a week or two; email tests may wrap up faster, but still need enough opens or clicks to be trustworthy.
5) Leveling the playing field
Both versions are shown to similar audiences at the same time. This avoids outside factors—like seasonality or overlapping campaigns—skewing the results.
6) Agreeing on success ahead of time
Before the test begins, your team sets the rule for what counts as a win (e.g., “If Version B increases checkouts by 5%, we roll it out”). This removes guesswork and helps the business act quickly with confidence.
How to Use A/B Test Results (and When Not to Act)
To get the most from your test efforts, dig deeper than the face value numbers when interpreting results. If a CTA test (“Buy Now” vs. “Get Started”) lifts button clicks but not completed checkouts, the underlying problem is likely further down the line.
Treat tiny bumps and small samples with caution. Early winners often fade once you collect more data.
Pair your findings with relevant context. Talk to customers, review post-purchase surveys, and watch a few session recordings. When you understand the “why” behind your results, your next variation gets sharper.
If two versions perform the same, keep the simpler option (or swing bigger with a clearer change). When you do roll out a winner, keep an eye on the metric for a few weeks to confirm lasting results. Trends are apt to change.
Powering Business Growth One Test at a Time
A/B testing is one of the most practical tools for improving conversion rates and, ultimately, revenue. It’s not a one-time fix but a steady process that delivers compounding gains
You might be surprised by the small adjustments that can unlock a new growth path when you test with intent.
If you want a partner to help plan or implement those tests, talk with Human. We’ll help you focus on the changes that matter most, turning each win into repeatable growth.
FAQ
What is A/B testing in simple terms?
It’s a fair fight between two iterations. You show the same audience pool two different versions of the same media at the same time. After enough time has passed and your sample size is sufficiently large, you evaluate the results and keep your champion.
Do I need a lot of traffic to run an A/B test?
More traffic helps, but it’s not required. If traffic is light, test bigger changes—like a new offer or layout—so the difference pops. You can also test on high-traffic, low-stakes channels first (like email).
What’s the difference between A/B testing and multivariate testing?
A/B testing changes one thing at a time (A vs. B). Multivariate testing changes several elements at once and studies their combinations. It needs far larger sample sizes to yield meaningful results. Most teams should start—and often stay—with A/B tests.
How long should I run an A/B test?
Long enough to gather a fair sample and cover typical patterns, often 1–2 weeks for websites. For email, run until each version gets enough opens or clicks to compare with confidence.
Is A/B testing only for websites?
No. You can test practically anything—email subject lines, ad headlines, form lengths, offer types, and more. Anywhere customers make a choice where you can measure the result, you can test.
Can AI help with A/B testing?
Yes. AI can draft variations, predict likely winners, and help segment audiences. Still, you should run real tests with your audience and let actual results decide what you ship.
