When it’s time to create a new marketing campaign, you may get stuck on questions like, “What exact text should we use for the CTA?” or “Would a different image be more impactful here?” At that point, many business owners just guess and move ahead, waiting to see how the campaign turns out. There’s a better way, though.
A/B testing lets you compare two versions of a marketing asset to see which version performs better. Discover how to create effective A/B tests to improve your marketing results and earn a higher return on investment from your campaigns.
What Is A/B Testing and Why Does Your Shop Need It?
A/B testing, also known as split testing, is a method of comparing two versions of a webpage or ad. Here’s how it works:
- Version A acts as the control. This is your original design or existing version.
- Version B is a modified version of the control, with one specific variation.
- Users randomly see either Version A or Version B.
- By analyzing engagement rates and other metrics for each version, you'll determine which performs better and which to use going forward.
Using A/B tests removes much of the guesswork from marketing. With these tests, you gain hard data to base your decisions on. You can continually refine your efforts using these tests and continued analysis of your campaign performance.
No marketing campaign is perfect from the start. It takes time to try different techniques and strategies, using analysis to identify the ones that are most effective. A/B testing speeds up the analysis process and helps you invest your marketing budget in the versions of your marketing materials that are most likely to drive results. Many
digital advertising services include A/B testing as part of the process because it’s such an effective way to gather data to inform marketing decision-making.
Boosting Ad Performance With Smart Split Tests
One of the most effective
marketing strategies for service businesses looking to boost visibility fast is local service ads. These ads can be very competitive and expensive, though, so you want to put out versions that will maximize your conversions. That’s where A/B testing comes into play.
With Google Local Service Ads, you don't have many variables to change and test. The most obvious factor to change is your business bio — an area where you can highlight what makes your shop stand out, like being locally owned or offering free estimates. Try testing different versions to see which one generates the best results.
Facebook local ads give you many more factors to adjust. Try running a test on the same ad with two different images, for example. Or change your CTA and analyze the results to see which version is more persuasive to users.
How To Run Your First Test Without Breaking a Sweat
Running an A/B test can seem intimidating at first, but it actually follows a very straightforward process. Use this step-by-step guide:
- Pick a goal for your campaign. Are you trying to improve your click-through rate? Generate leads? Drive sales? Your goal will shape all the other decisions you make about your campaign.
- Create a control. Make one version of the marketing material you think will be successful. Write compelling ad copy, choose a strong image, and create a standout CTA, depending on what kind of campaign you’re running.
- Change one variable. Choose one thing to test and change only that variable, like the headline, image, or CTA button.
- Launch both versions.
Split your audience into two random groups. Show one group the control version and the other group the test version.
- Run tests simultaneously. If you run the tests at different times, outside factors like time of day or day of the week can skew your results.
- Be patient. Use both versions for at least two weeks or until you get a sample size large enough to avoid false positives.
- Analyze and apply the results. Review the performance data for each version, paying close attention to data related to your goal. If you want to improve your click-through rate, for example, determine which version performed better on that metric.
If the better-performing version is the one with a changed variable, consider implementing that change going forward. Then, you can start a new test if you want to examine a different variable. You can run A/B tests endlessly, but you have to weigh the costs of the tests against the value of the information they provide.
Picking the Right Metrics To Measure Success
Getting useful results from an A/B test depends on choosing the right metric to watch. Focus on just one key metric that’s directly tied to your goal for the test or the campaign broadly. For example, you might look at open rates if you’re testing two different subject lines in an email marketing campaign. Conversion rate may make sense as a metric to watch for campaigns focused further along the customer journey.
Whatever you choose, stay focused. Looking at multiple metrics simultaneously can muddy the waters and make it harder to understand which version of your marketing materials performed better in the test.
Common metrics to focus on in an A/B test include:
- Conversion rate
- Click-through rate
- Revenue per visitor
- Abandonment rate
- Bounce rate
- Average session duration
Make sure you let your test run long enough to achieve statistical significance. Simply put, that means gathering enough data that you can be confident in your results. If one version’s conversion rate is three times higher than the other version but your audience size is only 15 people so far, that information isn’t very useful. Wait for more data before drawing a conclusion.
Real-World A/B Test Ideas For Auto Repair Shops
A/B tests are flexible, so you can test pretty much any changeable variable in your marketing materials. If you’re looking for some ideas, though, consider these A/B testing marketing examples for auto repair shops:
- Compare CTAs: Try "Get a Quote" vs. "Book Now" buttons to see which drives higher conversions.
- Compare photos: Use a professional photo in one version and DIY-style photos to see which your target audience responds to.
- Compare ad copy:
Creating high-converting ad copy is tricky, so try testing two versions of your ad text.
Common Pitfalls That Could Mess Up Your Results
When you’re getting started with A/B tests, there are a few common mistakes you want to avoid to get the best results, such as:
- Stopping the test too early: You may get a false positive if you stop too early, so run your test for long enough to collect plenty of data.
- Testing too many things at once: Testing more than one variable means you can’t tell which specific change affected user behavior. Stick to just one change you’re testing at a time.
- Mismatching your samples: If you don’t end up with equal (or very near equal) numbers of randomly assigned users in each group, your results won’t be as reliable.
If you make one of these errors, don’t worry. Even a "failed" test can provide valuable data about your customers, and you can fix the issue moving forward.
Running these tests and optimizing your campaigns can be its own full-time job. Turn to Optimize Digital Marketing for help. Our team will create a customized ad strategy for your business, including built-in A/B testing for better performance.
Contact us today to book a demo.
