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A/B testing of product ads
A/B testing is used for measuring the performance of different variations of the same variable. Mailing campaigns are also usually called Split test. The landing page is often used in marketing (when the customer clicks on the ad, so the given page is displayed for him), in email marketing and also in the ads themselves.
A/B testing monitors users behavior and how they complete specified goals. Subsequently, the individual variants are compared and evaluated. With the “landing page”, variants can be compared with the different buttons, text or images.
This pays off when testing A/B text product campaigns especially for larger campaigns, but the minimum testing time should be at least 2 weeks for maximum accuracy.
What exactly is A/B testing?
It’s a method and its aim is to increase the number of conversions by the help of the changes to the page. We will identify two variants for testing. Variant A (original) is displayed to the first half of the users and variant B (new) to the second half of the users. The variant with more conversions wins.
How to create A/B testing?
Who is A/B testing for?
It is intended for all websites/ e-shops/ posts on social networks. Everyone has some goal that is otherwise called a conversion, and the visitors should achieve it.
- Eshops want to sell more
- Companies that offer services want more completed forms
- Web services want more users who will be registered
- News portales, blogs or social media posts want to have more clicks or shares
How does A/B testing of product campaigns work?
A/B testing was tested with the client eXXpozed.de, which focuses on the sale of sportswear. The A/B test took place on campaigns for the Fjällräven brand, where two variants of campaigns were prepared for testing.
Campaign A
Campaign A used the production of longer keywords (Product type + Brand + Model) using Exact and BroadModifier matches.
Campaign B
Campaign B tested the achievement of results for shorter keywords (Brand + Model) using Exact and Phrase matches.
Campaign A
Campaign B
The results of our client in campaign A represent higher PNO, which paid off more. Based on these results, the client decided to use both product campaigns. You will find more details in our case study.
Process for A/B testing of text ads
The method is simple:
- Create 2 variants of product campaigns for product groups
- Monitoring of both variants
- Evaluation of results and their comparison
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