Push notifications are indeed a competent marketing tool, and probably, the bests of all marketing tools in the market. However, when it comes to delivering the maximum engagements and driving improved conversions with best push copies, you can’t be sure which one to use. This is where push notification A/B testing can come in handy by giving push marketers deeper insight into regular push campaigns. Also called as Bucket testing or Split testing,
A/B testing is an ultimate technique to implement bests of the competent strategies after experimenting with multiple alternatives.
You see, A/B testing happens in a highly volatile environment on a controlled sample. Even the miniature alterations in the original test conditions can result in significant deviations in the test results. Push notification A/B testing is a skill that requires a lot of perfection.
Why it’s so important to A/B testing push notifications?
The success of push campaigns directly depends on the conversions made by them. The goals could be anything from generating a direct sale, getting a click-through, converting an abandoned cart, to just encourage the user to open your app.
For getting constructive results, marketers need to constantly learn better approaches and push tactics. Furthermore, they need to implement those better approaches by introducing new alterations in their push copies. However, even after using top push notification services from the market, you might just do the opposite and kill your campaign at this very point in time.
Adopting a new strategy or making an “ought to be” best modification in your push copies without A/B testing a gamble. A/B testing is a better approach for making an alteration or crafting a completely new strategy before actually implementing them on a large scale.
You can create two variants of the same campaign and test which one works better on a sample target audience. Then finally, you can implement that better variant on the large scale and always have a tried and tested strategy for your campaigns that twinsets the conversion goals as per your target audiences’ requirements.
After all, it would be the user who receives the notifications, so why not ask directly in the form of push notifications A/B testing?
How to push notifications A/B testing works?
We take a sample of the target audience from the subscribers’ list and create two equal segments from it. Then we create two copies of the same notification, one for each. The original copy is called as ‘Control’ whereas the other copy is called ‘Variation’.
The two copies remain exactly the same as one another, except we make only that element dissimilar which we want to test. The difference between the two copies could be anything we want to test. For example, the message text, the headline, the images, text of the CTA button, etc.
We test both copies for exactly the same amount of time for a specific set of conversion goals and record each one’s analytics. The one with better conversion analytics is called as ‘Winner’ and is selected for the final campaign to all the subscribers.
How to A/B Test Push Notifications?
Running a Push notification A/B test is not rocket science. Various push notification services in the market provide built-in A/B testing tools that one can use without any hassle. However, you can test your notification, even if your push notification service has not provided one as built-in. You just have to manage some scenarios manually and have to be extra careful to prevent any biased situation. Here is how you can do it.
Go to the dashboard of your push notification tool and create two segments with equal numbers of subscribers.
Say, Segment-1 with 1000 subscribers. We name it as ‘Original’.
And Segment-2 with 1000 subscribers. We name it as “Variation”
Now, create two separate campaigns for each of the segments. All you have to do is create a new notification and select the segment from the list (Original in our case).
Create a second copy of the notification for the other segment (Variation). Here, based on your testing goals, you need to make the changes and keep the rest of the entries as same as it was for the first notification.
For example, here we are testing the “Headline” of our notification, s we will just change the headline and keep rest as same.
To keep things simple and maintain coherence, you need to trigger both the campaigns at the same time. However, there is a catch. You will get the results of the test comparatively in a very quick time. Unlike A/B testing emails or landing pages, push notifications’ lifecycle is very short.
For example, if you wish to test a landing page, you need to run the test for at least 30 days to get confident upshots. However, push notification life cycle is only for a few hours or a day maximum. If your notification campaign does not perform during this time, there is no chance it will get any engagement after that. People generally check the notifications immediately or within a few hours.
That’s why you have got a good chance to run multiple tests within a short interval of time. To get best and confident results, you can even iterate the same test multiple times within a week or so.
Once, you run the test, you can check the analytics to verify the performance metrics. For example, our test got the following engagement metrics after the first run. We can see that the first version (Original) got most of the click-through. Hence, it’s clearly a winner.
What else can you A/B test in your push campaigns?
A/B testing does not confine to a preferred set of elements or features that you can test. You can test anything that you think is significant for your push campaigns. You can write a message text differently. For example, you can add an emoji in one of the versions and test if it’s making a difference. Here are a few more ideas for push notification A/b testing:
- Message text
- Text formatting
- Length of message or headline
- Choice of the banner and icon images
- Experiment with sounds
- CTA texts
- CTA buttons
There isn’t any specific rule for A/B testing push notifications, not even in the inbuilt tools of top push notifications services. It purely depends on your conversion goals. For example, in our sample A/B testing above, we wanted to test the impact of different headlines, so we created different segments and ran the text at the same time on different audiences. We could also do it another way. We could have run the test on the same segment but on two different days.
You see, there could be a number of factors that might influence the test results differently. That’s why it is always recommended to conduct multiple iterations and take the MEAN of the readings to get more precise results.
Some tested tips for push notifications
Here are some tips you can follow to generate unbiased and more accurate results. They will help you to avoid some common pitfalls of A/B testing.
- One variable: Test only one variable at a time. Testing multiple variables at a time can create confusion.
- Similar segments: Consider the demographics, locations, behaviors of the subscribers before creating the segments. Try to put a similar kind of audience in both segments.
- Large sample: Do not test on small sample size. Keep a significant size of the sample to get more accurate readings.
- Iterate: Do not settle on a single test result. Conduct multiple iterations of the tests.
- Overall Analytics: Do not forget to pay attention to the overall analytics. Click though alone is not enough. Compare the readings based on their overall effect on the primary conversion goals like revenue, app-engagement, sign-ups, etc.
- Best practices: Do not ignore the push notifications best practices even while A/B testing. Practices like short headline, good images, time constraints, and frequency, etc. should remain intact ensure a maximum engagement level.
Hopefully, this helped you gain some practical knowledge of the push notifications and how to A/B test. You don’t have to spend fortunes purchasing top push notifications services to get A/B testing features. With a little improvisation, even your self-hosted push notification tool can produce confident A/B testing results. It all depends on your creativity and how engaging you can be with your push campaigns. So, do not wait, and test your push campaigns today.
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