If you’re a social media marketer, your primary goal is getting the best results in your marketing campaign. However, knowing which content is better for your brand can be challenging.
That’s where A/B testing comes into play. A/B testing is a powerful method for creating the best brand content and determining the difference between various elements.
A/B testing dates back to before the Internet. Direct mail marketers used it to conduct tests on many of their customers. This help them determine statistical significance before committing to the massive cost of printing and mailing the whole campaign.
Marketers have found many ways to use A/B testing in social media. Thus, social network marketing campaigns shouldn’t be more challenging. It will help you learn which type of content ticks your audience.
This article will discuss everything you need to know about A/B testing in social media. Remember to read to the end to learn more.
What is an A/B test method?
A/B testing allows you to compare two different versions of the same content. The primary objective is determining which is more engaging and how your audience has interacted with it.
Social media A/B testing can help improve the performance of your content. Thus, you don’t need to worry about sharing poor-performing content. It can also help you to:
But should we just implement A/B testing abruptly? No, of course not. You need to be aware of certain things to ensure you achieve success without any roadblocks.
First, you will need to define your hypothesis. What do you want to test? What metric do you want to improve? After that, you must create two similar content with a difference of just one testing variable.
Then, you split your audience into two groups and share two variations of the same content. Once you distribute the content, you must analyze which one performed better. In such cases, pay close attention to the clicks or engagement, including likes, comments, and shares.
Based on the analysis, comparing two versions will be easier. And if the difference is significant, your changes positively impacted engagement. On the other hand, you can overlook the marginal differences.
Here are a few examples of social media A/B tests:
These examples will help you understand which strategies are performing excellent. This way, you can create effective social media marketing efforts.
Remember that most marketers use 95% of the pre-determined significance levels to calculate the p value. Thus, make sure you pay close attention to the p value to avoid making any mistakes.
Importance of A/B Testing in Social Media
A/B testing is an excellent method to determine which performs better. Many studies examine general marketing strategies. While general strategies are an excellent way to start, they only work in some situations.Â
Testing your social media content strategy this way tells you about your audience’s likes or dislikes. It can also tell you the difference between certain sections of your audience. After all, it doesn’t mean that the same people who follow you on X (formerly Twitter) also follow you on LinkedIn for the same type of content.
As time passes, you will learn what works best for your brand. However, you should continue testing more minor variations to ensure you are on the right path. Even when you know you have the right formula, the more you test, the better it’ll get.
How to identify A/B testing goals?
Identifying A/B testing goals is quite simple. First, you need to understand the main business objectives. Then, you have to lay down goals that connect those objectives.
Finally, you select the metrics that accurately measure how close your content variants are to achieving those objectives. Here is a more detailed breakdown of these same steps:
1. Setting clear goals for social media A/B tests
Setting clear goals is crucial for your social media A/B tests. They measure how well your variations perform when your audience interacts with them. Additionally, they will indicate if the test variations achieve the brand goals better than the original.
Understanding your brand’s key objective can help you set goals for A/B testing. Then, your team can use the results to create a data-driven path for your social media campaign and make the best decisions to produce long-term, positive impacts for users and the business.
2. Evaluate your primary business objectives.
For A/B test results to be viable, they need to align with your essential objectives, which will vary depending on your industry.
For example, if you own an eCommerce company, your business goal would be to generate more revenue by selling more products. Considering this will help you narrow down the goals that are more relevant to achieving your business’s central objective.
3. Pinning down the right A/B testing goals
Now, you know which goals to track when running the A/B tests on various aspects of your product. These goals involve or are related to your primary business objective.
Following the previous eCommerce example, your goals may relate to how different variations impact your sales and revenue. For example:
You should determine what visual changes you must make on specific content or web pages to encourage visitors to buy your products.
Try different social media marketing campaigns to promote a variety of on-sale products to see which combination increases revenue.
4. Identifying key performance indicators or metrics
Finally, in addition to selecting the right goals for your A/B testing, you should identify some key performance indicators (KPIs). Good KPIs will link your objectives. Moreover, you should set a main KPI to calculate the success of your A/B test.
Returning to the eCommerce example, some good KPIs include cart abandonment and average order value. A secondary metric related to the primary metric would provide additional insight into your A/B test’s performance.
You and your team can create clear and compelling A/B testing goals with enough consideration and critical thinking. As a result, you will be able to measure test variables accurately and ensure successful business results.
Some A/B testing goal types are page/site visitors, website clicks, revenue generated, and form submissions.
Which areas require A/B Testing?
While many people know what A/B testing is on social media, they don’t know which areas to test. Thus, they test irrelevant parameters, failing to utilize the full benefits.
This is a common scenario. Even experienced social media marketers don’t know which A/B testing in social media parameters requires the most attention. Depending on the required details, the scope of A/B testing is endless. Here are some examples:
How to execute your social media A/B tests?
Executing and analyzing your A/B testing in social media is extremely important. However, what’s more important is following the correct execution process.
Remember, the A/B testing process is highly error-prone. To ensure you’re not making mistakes, here’s how you need to execute and analyze your A/B testing.
1. Implement your variations
First, you need to test different variants of your ad or post. The most straightforward way to do A/B testing is using a tool like Google Optimize, which automates your testing.
You can also do it manually using spreadsheets, posting content via a scheduler, or running ads directly on various platforms. But a tool made to run A/B tests will eliminate all the hassles.
2. Run the tests and analyze the outcomes.
Once your tests are running, collect data on how posts or ads perform for each variation. Once you have enough data, you can analyze which variation performed better.
Results will also be affected by the duration of the tests. Audience size can also be a huge factor. You will need a large enough sample size to be 100% certain of your test result.
3. Implement your learnings
For instance, you were testing different colors in social media graphics. You know one is a clear winner because it gained more impressions and engagement. Now, try to switch up your A/B testing. Post the winner graphic, but this time with a different graphic copy, or try to post it at a different time or on different days.
As you go on, A/B testing will optimize your content and continue to give you the best results possible.
4. Maintaining best practices
Eventually, having a data-driven process to optimize your social media content is exciting, but take your time with the excitement.
Always try to make the variations as similar as possible, with only one difference being the variable you want to test so that you can separate the effect of that variable on your metrics.
Always remember to run your tests for a long enough period and with a big enough sample size to ensure the best results. Finally, track your results carefully and analyze them properly to maximize the use of your social media content.
Common mistakes to avoid in social media A/B testing
Sometimes, you may not get the desired results from your A/B testing. In such cases, you may wonder what steps you can take to achieve a better outcome.
Many businesses make common A/B testing mistakes, wasting time and effort. Most of these mistakes occur because they lack experience running the tests properly. Here are some common social media A/B testing mistakes you need to avoid.
1. You always split test the wrong pages
One of the biggest mistakes in A/B testing on social media is splitting the tests on the wrong pages. Many businesses make this mistake and fail to utilize the full potential of A/B testing. You must ensure you’re not wasting time and effort with pointless split testing.
However, you may not have an idea of which pages to test. This is true, especially when you’re running a small business. The best testing pages are where you will see noticeable differences in sales and conversions.
If the page is not valuable in your sales and marketing, I recommend you avoid testing it. But if you notice a significant traffic spike on one page, you can prioritize split testing it.
2. Your hypothesis is invalid
This is another standard A/B testing social media mistakes you must avoid. Without a valid hypothesis, you’ll face numerous problems.
But what is an A/B testing hypothesis? It’s one type of theory explaining why you receive specific web page results. It will also indicate how to improve such results.
Remember that you’ll need all the essential elements for a valid hypothesis. From data observation to speculation, you need to know how to fix it. This way, you can measure the results after a fixed implementation.
3. You split test multiple times
When you split the test into too many items, you will face many problems. You may think you’re saving time, but the results are the opposite. For instance, you can’t know what changes improved or degraded the results.
This is why you don’t need to rush things with split testing. A good strategy is changing one item at a time. Then, test it again with its other version. If you need to change multiple items simultaneously, you need to consider multivariate multiple tests.
4. You run too many split tests simultaneously
Keeping things simple is an essential part of A/B testing. However, many businesses forget this. They run more than four split tests at a time, which causes improper results.
For example, you can test three different CTA versions and get meaningful results. Running simultaneous tests isn’t the same as running multivariate testing. You will still be changing one item at a time.
But, as the A/B testing variation increases, the sample size also increases. As you send more traffic to each version, the results become unreliable.
5. You work with the wrong traffic
Last but not least, you must avoid working with the wrong type of traffic. If you want meaningful results from your A/B testing in social media, you need healthy traffic to your web pages.
If your website receives high traffic, your split testing process will be completed earlier. Do you know why? It’s because your site will receive constant traffic flow. However, your tests will become longer if the website traffic is lower.
Additionally, make sure you split your website traffic properly so you know what you’re testing it against. You can allocate the traffic manually using some A/B testing tools.
Ready to conduct social media A/B testing?
That’s everything you need to know about A/B testing in social media. While you may have a data-driven social media strategy, social testing will add another weapon to your arsenal. However, don’t get carried away.
Therefore, only test one variable at a time. This way, you can pay close attention to the metrics and know what’s working in your favor. Also, make sure the variations are as similar as possible.
What’s your opinion on social media A/B testing? Do you find it beneficial for your social media marketing campaign? Let me know in the comments below.
