If you are an online marketer, then you know that A/B testing is the key to success.
Many people set up their tests wrong from the beginning and then wonder why they don’t see any results. Setting up a good test takes time and effort, which many marketers aren’t willing to invest in this process.
However, setting up effective tests can be tricky and time-consuming, which means that many of us don’t do it enough or at all. This guide will show you how to set up profitable A/B tests for PPC Success so that your campaigns start making money instead of losing it!
You’ll learn what makes a good test and how to avoid common mistakes when setting them up. We’ll also cover some advanced techniques like multivariate testing (MVT) and lookalike audience targeting. By the end of this article, you’ll have everything you need to run your own successful A/B tests in AdWords, Bing Ads, or Facebook.
What are Split Tests?
A split test is a method of comparing two versions of something to see which one performs better. In online marketing, this often refers to an A/B test or multivariate test (MVT).
In a split test, you show the same group of customers different versions of your ad or landing page to see which one generates the best results.
For example, let’s say you are advertising a new blue widget. You can put two ads against your ad group and serve both of them to the same customers. This way, you can see which one generates a better CTR (click-through rate) and conversion rate.
Why Do We Need A/B Tests?
A/B testing is the only way to know for sure whether a change works or not. If you make a change to your ad and start seeing a lift in CTR, do you know whether it is because of the new headline or the blue button? After all, you don’t want to change your brand colors just because of a small lift in CTR.
You can’t be 100% sure what is working and what isn’t. You need to keep running tests while simultaneously adjusting your other ads and keywords; that’s why having a proper test in place is crucial for successful online marketing.
What is Focus in A/B Testing?
Focus in an A/B test is the thing you are testing, whether it’s copy, design, pricing, or anything else.
For example, if you are testing two different color variations of the same product, then the color is your focus. If you are splitting traffic between two landing pages, then the design is your focus.
It’s important to remember that you can only test one focus with a split test. This is why MVT (multivariate testing) and lookalike targeting are more complex. They allow you to test multiple focuses at once.
Tips for Organizing and Managing Your PPC A/B Tests
It’s important to organize your tests properly so that you can stay on top of them. Without proper organization, you run the risk of forgetting about your tests or, worse—running conflicting or overlapping tests.
Here are some tips for keeping track of your PPC A/B tests.
1. Identify what you want to test, and set a testing plan before you begin.
2. The planning process is both tactical and strategic, so take time to define your goals clearly before testing commences.
3. Focus on one metric when designing individual A/B tests; you can later combine them if they are successful.
4. Use your testing software to track all of your tests and display them in a logical manner.
5. Maintain competitive intelligence; it will help you make better-informed decisions about when to stop or restart your tests.
6. As you test, make sure that all of your ad messaging stays on point; this will help ensure that your tests are not skewed due to unintentional variations in messaging.
7. Establish a system so you can prioritize your tests following the initial setup.
8. Ensure that you set up your tests to be easy to read; otherwise, you risk slowing down the results, which could lead to incorrect decisions.
9. If you have a team of people managing your testing, make sure that they are all on the same page, so there is no overlap.
10. Start testing, and monitor your results daily.
11. Consistency is key when it comes to PPC A/B testing, so make sure to establish a rhythm and stick with it.
What Makes a Good PPC A/B Test?
The key to running successful tests is using the right metrics. When you’re starting out, it can be helpful to focus on one metric at a time.
For example, you might test the CTR of your ads against each other first. Once you’ve found the ad with the highest CTR, you can move on to testing against other metrics like CVR or average cost per lead.
How to Evaluate & Act on Tests
After you’ve run your tests and found a winner, it’s time to act on the results. If you just saved $4 per lead or more, you’ll want to keep on running the winning ad. When it costs you more on a CPL basis, then stop running it.
If you see a lift in CTR and conversions, keep on running with the winner. And if not, go back to the drawing board and try to figure out why your ad wasn’t resonating with your audience.
How Long Should Each PPC A/B Test Run?
The length of your A/B test will depend on your business goals. If you’re looking to figure out the best ad campaign, then you may need to run for months.
However, if you’re trying to determine which landing page converts at a higher clip, then it could be as short as a day. Your tests need to be long enough for the data to be statistically significant, but not a lot longer than that.
Your golden rule of thumb is to keep the time of your tests relative to the goal.
How to Use Clarity Features in A/B Testing
When running tests, make sure that you’re using the clarity features correctly. That way, you can immediately identify which ad or landing page is performing better and optimize your marketing activities.
The following are some of the Clarity features you should be aware of when running A/B tests:
To identify the click patterns on your ads or landing pages, use Clarity’s Click Heatmaps tool to get detailed information about where users are clicking on your ads and landing pages.
This will tell you where users are clicking on the page. If a lot of people are clicking on a certain area, then that area may need to be emphasized. This information will help you improve your ad layout and design, as well as identify which ad copy is attracting the most clicks.
Session Recordings are available on Clarity. They show users’ actions, mouse movements, and scrolling behavior that were recorded during the experiment.
The Clarity Session Recordings feature makes it easy to check if users are truly engaging with your experiment. You can look into every minute of the sessions, even if you have a huge number of users.
Scroll heatmaps are similar to click heatmaps. However, they’re great for identifying how far your users are scrolling on your ads or landing pages.
This is a great tool for identifying which ad or landing page your users want to engage with more. You can also use scroll heatmaps to see whether a certain part of your ad is capturing the most attention.
Another Clarity feature you can use to improve your A/B tests is the Conversions heat map. Find out where your users are “sticking” or converging to on your landing pages by checking out the conversions heatmaps.
This is another great A/B testing tool for identifying how people are interacting with your landing page. If you have a lot of conversions on one area, then that area should be emphasized more. If you don’t have many conversions, though, then you should try to find out what’s stopping users from taking the desired action on your ad.
The Clarity Abandonment Rate feature shows you how many people have abandoned your ad or landing page.
This is a great tool to determine whether your ad’s messaging and call-to-action are effective. You can also determine whether factors like your page’s load time or if there are any distractions on the page that are causing users to leave.
When people are frustrated with your ad or landing page, they can rage-click.
This feature tells you whether users are having issues with your ad or landing page. If rage clicks occur, then your ad may need to be improved.
You can also use Clarity’s Segmentation feature to determine where your users are coming from, their demographics, and a lot of other data points.
Clarity also has an Attribution feature that helps you assess how your campaigns are performing.
You can also use Clarity’s Funnel feature to analyze the path users took before converting your ad.
Additionally, Clarity offers real-time alerts for your campaigns, so you’ll know when there are changes in the performance of your ads or landing pages.
Clarity not only helps you optimize your campaign, but it can also help you create better ads and landing pages by highlighting important information.
Finding the Winning Ad or Landing Page
By now, you should have a pretty good idea of which ad or landing page is performing better for your PPC A/B test. If you haven’t, though, here’s how to find out:
1. Tag your ads and landing pages
You’ll need to identify which ad or landing page is performing better by tagging them. You can use any identifier that’ll help you compare the two. You can also prioritize which ad or landing page to focus on first by giving them “1” and “2” tags.
2. Find out which ad or landing page is getting more conversions and traffic
To find out, simply take a look at the metrics column on Clarity and compare the number of conversions and traffic for each ad or landing page.
3. Finalize your winning ad or landing page
Lastly, just choose your winner and create a new ad or landing page that has the attributes of the winning ad.
Ultimately, optimizing your PPC campaigns doesn’t have to be complicated. You just need to know which metrics you should take a look at and what tools can help you easily determine which ad or landing page is performing better.
That’s why we recommend using the clarity platform to make things easier for you to optimize your PPC campaigns.
Common PPC A/B Testing Mistakes
Here are some of the most common PPC A/B testing mistakes you should avoid to optimize your PPC campaign and make it more effective:
1. Being biased with your hypothesis
This is one of the most common A/B testing mistakes. It is normal to have an initial idea or impression about your experiment, but you should avoid making decisions based on that. You need to keep an open mind if you want to succeed with A/B testing. If you’re not prepared for failures and rejection of ideas, you’re headed straight to disaster.
2. Not defining success metrics
You should define the success metrics for your experiment before starting it. There can be two types of results: online (conversion rate, bounce rate, etc.) and offline (sales volume). Also, you need to understand that A/B testing is not a magic bullet, so being 100% accurate isn’t possible. One way to reduce this inaccuracy is to test as many things as you can.
3. Not having the mindset of an outsider
After you run a test for some time, it can be very easy to start thinking in a specific way. For example, if you test headlines of the blog post and the winner has more emotional words like “horror” or “shock,” you might start thinking that it affects the user’s behavior. But if someone else runs the test, he can come to different conclusions. Try to stay unbiased and form your own opinion after each A/B test you run.
PPC advertising is not only an effective way to get leads and sales, but it is also a great way to test your assumptions about your target audience.
So if you’re using PPC ads for driving traffic to your website, you should consider A/B testing different variants of ad copy, landing pages, etc. By doing this, you’ll be able to increase the effectiveness of your campaigns.
If you have any questions about PPC A/B testing, feel free to contact us. We are happy to help.
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