It can be difficult to know which marketing strategies and techniques work best for your audience. A/B testing, combined with other conversion methods, allows you to test different variations of any piece of content, whether it’s a banner, email, landing page, or ad headline, to improve the content and achieve higher conversions faster.
In this article, we’ll take a detailed look at how A/B testing works, why it’s important to test hypotheses, and how to properly implement tests in your marketing strategy.
What is A/B testing and why use it
A/B testing is a testing method that enables data-driven decision making by comparing variations of the same marketing campaign element and choosing the best option in terms of conversion. This approach allows you to evaluate audience response to different variations of the same element, improve user experience, enhance content phone number library quality, and reduce bounce rates.
The methodology is based on a simple idea: simultaneously test two options under equal conditions and use the data obtained to select and further implement the more effective of them. Testing allows you to quickly find working elements, relying on accurate data, rather than guesswork.
At the same time, A/B testing is not as simple as it seems: the interpretation of test results must rely on statistics and mathematical probability theory to confirm whether the differences in performance are significant.
As a result of the experiments, you will have a deeper understanding of user behavior, which will help optimize marketing strategies. Let’s move from theory to practice and talk about the stages of preparation that need to be completed in order omnichannel marketing – examples of successful application to launch a split test.
Stages of A/B testing
Step 1. Defining the purpose of the test
Before you start testing, clearly formulate its purpose. This could be, for example:
- increasing conversion from lead to sale from 1.5% to 2%;
- increasing the average check in the online store by 1.5 times;
- doubling the time spent on the site.
Try to set specific, achievable, and understandable goals for all participants in the process. This method of setting goals is also called SMART goals.
A SMART goal should be:
- S — Specific — specific;
- M – Measurable – measurable;
- A — Achievable — achievable;
- R — Relevant — significant;
- T —Time bound — limited in time.
This way, you will know how much time you need for the test, you will be able to compare the results with expectations after completing the text, and understand what benefit you get from the testing.
Stage 2. Formation of a marketing hypothesis
A marketing hypothesis is formed based on data and observations. It is not simply an assumption that some changes will lead to improved results. When formulating a hypothesis, it is important to clearly state several key points:
- What we’ll do: describe a specific action, such as changing the color of the “Buy” button from blue to red.
- When we do it: indicate in what period japan business directory the experiment will be conducted.
- How long to test: determine the duration of the test and the amount of data needed for analysis (for example, the number of clicks, impressions or conversions).
- What we will consider as a result: specify what level of deviation will be considered statistically significant. For example, a difference of 10% with 10 conversions may be random, but with 1000 it is already a significant change.
- Testing a single variable: To reach accurate conclusions, it’s important to test only one change at a time. For example, changing the copy of an email or changing the audience segment are different tests that shouldn’t be combined.