As human beings, many times, we fail to choose the right path. We keep on changing our preferences and end up in confusion. As we move further, many divergences come our way, and eventually, things get complicated.
How long will your trust be intact in this situation? The business world is packed up with many twists and turns. If you are new, can you withstand it? Definitely!
The above introduction is to tell you that today you will learn about something simple and strategic when it comes to choice makings in running an email campaign. If you are following us, then mark that it's time to watch your business rise.
Before we come down to our business, we should know what we are speaking about. So let's solve the first mystery.
A/B testing also referred to as split testing or bucket testing, is a process where two versions of a single application or the webpage are compared and determined which one works better. It is an important experiment in which the users are randomly given two different pages to compare at once.
A certain goal is set to judge the variants, and with the help of statistical analysis, one can choose the better one.
You can verify your current experience and ask relevant questions and changes required in the website or application easily by just conducting an A/B test that directly weighs it up against a variation.
Testing assures to remove all the guesswork from website optimization and allows decisions based only on actual data. Track the changes on the metrics, and certainly, every change will produce desired results.
How does A/B Testing Work?
Now that you are aware of what A/B testing is let's take a quick insight into how it works.
- Firstly, you have to select a web page or a screen of any app. Now, just create another version with it. How?
- This is as simple as breaking a stick. You have to just modify either a single headline or some button. For better results, you can even redesign the page completely.
- After this, half of your visitors are given the original one referred to as control and the other half with a modified one known as the variation.
- Now, these visitors will rate your page. Their engagement rate with each version is calculated and collected. It is then statistically analyzed thoroughly.
In this way, figure out the impact according to visitors' behavior. Was it positive, negative, or neutral?
Why should you include A/B Tests in Email Campaigns?
The result we get through this testing can help you improve the user experience and bring required changes. Brands and companies can create a synopsis and framework to decide how their email campaign should be. You can avoid elements that users deny.
Apart from using it just to settle down a disagreement or to derive a solution, it can increase the overall performance of an entire campaign. Isn't it the best way to improve engagement rates, or can we say success rates?
Setting up an A/B Test
After reading the above stuff, aren't you excited to start one? You can convert an email campaign into A/B testing at any point. Before that, you have some tasks to perform.
1. Decide your primary goal.
Before going for an A/B test, what if you don't have a specific goal? Will you keep modifying everything? This would nevertheless intensify your job. In this context, you can aim for:
- Attracting more crowd to your website
- Encouraging readers to act. Here your goal is to try and look for more visitors opening your email.
- Improving click-through percentage by inviting them to the website. This will ultimately increase the engagement rate.
- Inviting them to a specific URL. This is done when there is an impactful CTA. Here the page with the highest number of clicks would win.
You should be certain about the next move. This will allow you to work in a single direction and bring winning metrics to your campaign.
2. What is it you need to test?
Now decide on what basis you want to compare version A and version B. Emotions of your experiments should be based on different subjects, senders, and designs.
The content in both versions should be the same except for its subject lines. This is the best way to analyze customers' interests.
You can try:
- Experimenting with two polar opposite subject lines, one general and the other amusing.
- Adding personalization is one of them. Greet them with their first name and check the result.
- See what offers to fascinate them more: "Coupons of purchase" or "30% off".
- Lastly, keep subject lines identical and just change the preview texts.
It is important to provide the sender's details as many people won't open an email if they do not recognize it. Try testing with different From names and email addresses of both versions. Consider adding the name of the product or brand. Determine which works better.
Here, keep the content similar while you can change the template used. This will govern the article length, images and CATs used.
3. Choose Recipients
After setting up both versions, your job is to choose people to whom you want to send this. Before stepping forward, check your subscribers' list. If new subscribers have joined you after the test has been started, they should be kept out of the campaign for the time being. These subscribers should be welcomed and treated separately.
4. Test before starting
It is essential to mend errors, if any, before starting the A/B Test because it will not be possible to change anything midway. Before letting it reach others, give it a quick test and get the previews of how the versions will reach people.
When should you Draw the Inference?
You can choose to run A/B testing from one hour to five days. Once this time elapses, the system will now consider the data gained for both versions. The winner is highlighted based on the parameters set. Then the winning versions should be then added up and sent to other customers. Otherwise, you can also analyze the results obtained manually and predict the winner.
Now you are set to start A/B testing and write your success journey with email campaigns. But while planning, remember a tip at a time; you should test only one aspect for both versions. Avoid involving too many changes at once. In this way, you can pinpoint the rise and fall in graphs for versions A and B. Once everything is judged carefully, you can combine all the winning chances to finally launch an ideal version of your email.
When will you implement A/B testing in your email campaign? Is there something obstructing you?
Join us, and nothing will stop you from executing this.