Why You Should Be A/B Testing Your Creative
As a business owner or marketing professional, it's important to constantly strive for improvement in your advertising and marketing campaigns. One way to do this is through the use of A/B testing, also known as split testing, for your creative media.
A/B testing allows you to compare two different versions of a piece of creative media, such as a banner ad or email subject line, to see which one performs better. This is done by showing each version to a randomly selected group of people and then measuring the response rate or engagement. The version that performs better is the "winner" and can be used in future campaigns.
But why is A/B testing important for creative media?
Here are a few reasons:
A/B testing allows you to make data-driven decisions about your creative media. Rather than relying on gut instinct or personal preference, you can use hard data to determine which version is more effective at achieving your campaign goals.
A/B testing can help you optimize your creative media for maximum engagement and effectiveness. By testing different versions, you can identify small changes that can have a big impact on how your audience responds to your ads. For example, you may find that changing the color of a call-to-action button or the placement of an image can significantly increase the click-through rate of your ad.
A/B testing can save you time and money. By using A/B testing, you can avoid wasting resources on creative media that may not perform well. Instead, you can focus on the versions that have been proven to be effective, which can help you get the most out of your advertising budget.
How Do You Get Started With A/B Testing?
To start, define your goals for the A/B test. What do you want to achieve with the test, and how will you measure success? For example, if you're testing a banner ad, your goal might be to increase the click-through rate, and your measure of success would be the number of clicks on the ad.
Next, create two versions of your creative media. These versions should be as similar as possible, with only one or two small differences. For example, you might create two banner ads that are the same except for the color of the call-to-action button.
Show each version of the creative media to a randomly selected group of people, also known as a sample group. This is important because it ensures that the results of the test are not influenced by external factors, such as the time of day or the audience's demographics. Measure the response rate or engagement for each version of the creative media. This will allow you to determine which version is the "winner" and performed better.
Use the winning version in future campaigns, and consider using A/B testing again in the future to continue optimizing your creative media. While that particular winner may be the higher-performing creative now, consumer trends and behaviors change and you should always be looking for ways to improve!
What Is Some Popular Software to Use for A/B Testing?
Google Analytics is a popular and widely used tool that allows business owners to track and analyze the performance of their websites. It includes features for A/B testing, such as creating and comparing different versions of web pages.
Optimizely is a dedicated A/B testing platform that offers a range of tools and features for testing different aspects of a website, such as layout, design, and content.
Unbounce is another popular A/B testing platform that allows business owners to create and test landing pages, pop-ups, and other types of web pages.
Visual Website Optimizer is a tool that offers a range of features for A/B testing, including heatmaps, user recordings, and customizable reporting.
Adobe Target is a powerful A/B testing platform that integrates with the Adobe Experience Cloud suite of tools and offers advanced features such as machine learning and real-time personalization
How Can You Run an A/B Test With Product Photography?
If you're testing product photos, your goal might be to increase the number of purchases, and your measure of success would be the number of product sales. For example, you might create two versions of a product photo, one with the product against a white background and one with the product against a colored background.
An example split test we have performed with product images was with the main images on Amazon. One was a simple, classic isolated image with the product against a white background. The second was the same product and white background but in the bottom right corner, we included an additional graphic to entice interest from customer scrolling through the search results page.
After running the split test for 6 weeks, we found that the image with a small additional graphic increased conversion rate and sales by nearly 10%! Of course, we’ve performed other split tests where the original image outperformed the Version B image. This is still a win in our books because it means as far as we know, through the data, the client is using the most optimized product images for their eCommerce store! As stated before, making data-driven decisions not only helps improve underperforming media and products, it helps us make more informed decisions when launching new products in the future!
A/B testing is an important tool for anyone looking to improve the performance of their advertising and marketing campaigns. By using A/B testing, you can make data-driven decisions, optimize your creative media for maximum engagement, and save time and money. So if you're not already using A/B testing for your creative media, it's definitely worth considering. To start a/b testing, though, you need content! Reach out to through the button below to get a custom quote for your product and commercial photography needs.
