Best Practices for Amazon PPC Split Testing

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Amazon PPC Split Testing.
In the world of Amazon PPC advertising, A/B testing is a game-changer. By comparing different versions of your ads or campaign elements, you can uncover insights that help you optimize your campaigns and achieve better results. In this blog post, we will dive into the best practices for Amazon PPC split testing.

Before You Start

  • Before diving into A/B testing for your Amazon PPC campaigns, it’s important to ensure you have a solid foundation in place.
  • Additionally, make sure you have a clear understanding of your campaign goals and objectives. Are you trying to be profitable right away or are you looking to spend a little more to start ranking a new product?
  • Get familiar with the different types of campaigns and ad formats available for Amazon ads.

Overview

Understanding A/B Testing

A/B testing, also known as split testing, involves creating two variations, A and B, of a specific element in your PPC campaign.

It allows you to measure the impact of different variables and identify what resonates best with your target audience.

By conducting controlled experiments, you can gain valuable data-driven insights and make informed decisions to enhance the performance of your Amazon PPC campaigns.

Setting Clear Goals

Before embarking on A/B testing, it’s essential to establish clear goals and objectives.

Define what you want to achieve through your tests, whether it’s improving click-through rates (CTR), increasing conversion rates, or reducing ACoS.

Clear goals will provide a framework for your testing strategy and help you measure the effectiveness of your experiments.

Here are a few example scenarios to get you started in the right direction:

  • Your listing already has a great conversion rate and you have a low ACoS.
    • If this resonates with you, then your main objective should be to increase your CTR.
    • Assuming that the search volume of your product’s main keyword remains relatively constant, the best way to increase your sales is to increase the number of people landing on your product page.
    • If you already have a pretty good conversion rate and low ACoS, then convincing more people to click on your ads is the best approach; hence, improving your CTR should be your primary focus.
  • Your listing’s conversion rate is low/average and you have a high ACoS.
    • If this statement applies to you, then your first course of action should be to improve your listing’s organic conversion rate before split testing with Amazon PPC.
    • If you have already done so and you believe that you have reached your listing’s maximum conversion rate, then the next best thing that you should do is test different creatives (headlines, calls-to-action, and hero images) on your Sponsored Brands/Sponsored Display campaigns in order to maximize the conversion rate of the ads themselves.

Choosing Variables to Test

When selecting variables to test, focus on elements that have the potential to significantly impact your campaign performance.

This could include headlines, ad copy, images, and even different calls-to-action.

By isolating one variable at a time, you can accurately measure its impact and make informed decisions based on the test results.

Remember, a strategic approach to variable selection will lead to more meaningful insights and improvements in your Amazon PPC campaigns.

Here are a couple of questions to ask yourself when deciding on a variable to test:

  • Do I want to increase my CTR and thus, the amount of traffic going into my listing? If so, then start with split testing your main image.
  • Do I want to increase ROAS on my campaign? If so, then start with split testing different headlines (available only with Sponsored Brands/Sponsored Display) to find one that really speaks to your target market.

How to Split Test with Amazon PPC

Sponsored Products

Since the visual elements of Sponsored Products ads are limited to just your main image, title, and price, there are limited options for split testing with Sponsored Products.

With that said, it’s still possible! A commonly used technique for A/B testing on Sponsored Products campaigns is simply changing any one of those visual elements (title, main image, or the price) and measuring the difference in your ACoS afterwards.

In any event, the beauty of split testing with Sponsored Products campaigns is that no changes to your Amazon PPC campaigns will be necessary! This is because you will only have control over the title, main image, and price of the product(s) being advertised, which is all separate from Amazon Advertising.

To make sure that you get reliable results, always be sure to run your Amazon PPC split test for at least a 14 day period. Moreover, longer periods are always better, so if you have the option to, opt in for an even longer testing period for both variations.

Sponsored Brands and Sponsored Display

Split testing with Sponsored Brands and Sponsored Display ads are where it gets a little more fun!

With either of these campaign types, you have more options for variables to control:

  • A headline
  • An image (with Sponsored Brands)
  • Videos
  • Main image, title, and price (just like Sponsored Products split testing)

On that note, I would recommend starting off with split testing different headlines with Sponsored Display ads, along with both different headlines and hero images with Sponsored Brands ads.

With the recent release of Adgroups for Sponsored Brands campaigns, it’s easier than ever before to test different variations of your creatives with Sponsored Brands.

All you have to do is create a new adgroup within the same campaign of the products that you want to split test with and change any element of the creative to whatever you would like. Afterwards, just measure the difference between the metrics that you chose to measure for this split test after an assigned period.

That said, since you have the ability to create multiple adgroups in Sponsored Brands campaigns now, you don’t need to run two different campaigns one after the other in order to conduct your split test (like you do with Sponsored Products split testing)!

Analyzing Results from an Amazon PPC Split Test

Once you’ve completed your A/B tests, it’s time to analyze and interpret the results.

Look for statistically significant differences between the variations to determine which one outperforms the other, based on the metrics that you care about for this split test.

In addition to that, keep in mind that testing is an ongoing process, and you may need to iterate (likely over and over again) and refine your campaigns based on the insights gained from each test.

By continuously analyzing and applying the learnings from your A/B tests, you can drive continuous improvement in your Amazon PPC campaigns.

Here are a few questions to ask yourself when analyzing results from an A/B test:

  • Did my CTR improve?
  • Did my ACoS reduce?
  • What can I do for the next split test?
  • If there was any sort of improvement, then is there an underlying theme hidden within the good performance that I can leverage for another test?

Summary and Next Steps

In conclusion, Amazon PPC split testing is a powerful tool for optimizing your ad performance.

By following the best practices outlined in this blog post, you can conduct effective split tests that provide valuable insights into your target audience and campaign performance. Remember to set clear goals, choose the right variables to test, conduct controlled experiments, and analyze the results to drive continuous improvement. With these tips in mind, you can take your Amazon advertising strategy to the next level and achieve better results than ever before.

To get started with A/B testing, take some time to review your current Amazon PPC campaigns and identify areas for improvement. Use the best practices outlined in this blog post to create a testing strategy that aligns with your goals and objectives. And remember, testing is an ongoing process that requires continuous iteration and refinement.

By consistently applying the learnings from your A/B tests, you can optimize your campaigns for maximum performance and ROI.

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