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What is split testing?
Split testing (or A/B testing) is a simple method of determining the most effective web page (or individual element of a web page) from two options offered to users.
Benefits of split testing:
- an objective understanding of which option is more effective
- the costs of conducting the test are minimal
- use of existing traffic on the site (no need to attract additional traffic)
- the ability to return to the best new zealand telegram data option in 5 minutes
What can be tested on the site?
- lead forms
- CTA elements
- design decisions (for example, the old version of the landing page in relation to the new one)
- sliders, videos, images
- Headlines
- text content
- the arrangement of various elements on the site
What do we need to conduct A/B testing?
- Google Analytics account
- test and original version of the web page
- programmer’s time to implement edits
- SEO specialist time to set up the test
Let’s consider the situation: you are the owner of an online store, there are sales on the site, but the conversion rate is very low. When analyzing data in Google Analytics, it turned out that when placing an order, 60% of users leave the site.
Let’s get started with testing:
Step 1. Select the test object
In our case, this is the product gambler data purchase form. The order page contains the form:
We create a test form of the following type:
Step 2: Create an experiment
We go to Google Anlytics, select the required view, open the report “Behavior” — “Experiment”:
Let’s create a new experiment:
At this stage, you can select the percentage of traffic that will participate in the experiment.
To obtain a reliable result, it is necessary that as many users as possible (amount of traffic) participate in the experiment. At the same time, it is necessary to remember that if 100% of traffic participates in the experiment and the test option is unsuccessful, then you will lose profit.
Advice: start the experiment with 5-10% of traffic participating in the test. And gradually increase it to 50% or more percent – while tracking the conversion.
Step 3. Set up the experiment settings
Step 4. Setting up the experiment code
Google Analytics automatically generates the code for the experiment. You only need to give the code to the programmer and specify where to implement it.
Step 5. Launch the experiment
After installing the code on the original updating your native pages tags and test pages, click the “Start Experiment” button.
Our experiment has been launched, all that is needed at this stage is to wait for the results of the experiment, while simultaneously tracking the conversion and increasing the % of traffic participating in the testing.
As a result, the Google Analytics system will automatically stop the experiment when the best result is achieved and show the results:
From the results of the experiment, we can conclude that the Checkout page outperforms the original version with a conversion rate of 2.78%.
Once the experiment is complete, you will need to delete the test version of the pages and the Google Analytics experiment code. Leave the version that was the most effective on the site.
Optimize landing pages with split testing to increase conversions.
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