Alternatives to A/B Testing in SaaS: How to Improve Product and User Experience
A/B tests are a well-known technique for testing UX elements but is it the only one? Are there any alternatives to A/B testing for product managers?
Plenty actually, and that’s what we explore in the article!
Interested? Let’s dive in!
- A/B tests are experiments in which you present two different versions of your product to an even number of users and check which of them performs better.
- A/B testing and split testing are very similar and people use the terms interchangeably.
- While A/B testing tests one alternative solution at a time, multivariate tests involve multiple versions of multiple elements.
- A/B testing is often used to optimize a landing page to improve its conversion rate.
- You can also use it to improve product usability and in-app engagement by testing the effectiveness of different in-app messages.
- A/B tests are not much use when you don’t have enough users to make the results statistically significant.
When we’re seeking to make small improvements, there are more cost-effective alternatives to A/B testing:
- Product usage and user behavior tracking can help you identify the happy path, so you don’t need to run experiments to find it for other users.
- Heatmaps and scroll maps are visual representations of how users engage with your UI.
- Thanks to session recordings you can follow every cursor move a user makes to find UI elements that are causing friction.
- There are various usability testing techniques like eye-tracking, 5-second tests, or first-click tests. PMs harness them to investigate how easy to navigate their products are.
- Collecting user feedback via surveys is another alternative to A/B tests. You can also use them to collect qualitative data, just like in user interviews.
- To obtain real-life data on product usability before launching it, run beta tests.
- Feature flagging is a practice of disabling UI elements to see how they impact user experience.
- Fullystory is a digital intelligence tool. It offers session recording functionality, tagless usage analytics, heatmaps, and scroll maps (and more).
- Userpilot allows you to track product usage, visualize feature engagement with heatmaps and collect user data.
What is A/B testing?
A/B tests involve comparing two items or variations to one another to see which one drives better results.
To carry out the test, you enable the new feature or UI element for half of your users. Next, you collect data on its effectiveness compared to the previous one.
Split testing vs A/B testing
A/B testing and split testing are pretty much the same things. In both cases, you show two versions of your product to different groups of users to check which of them gets a better response.
A/B tests are normally used to test small variables, like different UI color patterns. A split test can be used to test two very different products, like two different websites.
However, they both rely on the same principle.
If there’s any difference, its emphasis is within the name. A/B stresses the comparison side of the test, ‘split’ focuses on the way traffic is diverted to different products.
What’s more, split tests aren’t necessarily limited to two versions.
Multivariate testing vs A/B testing
Multivariate testing is split testing of multiple different versions with multiple different elements.
In A/B tests, we make only one change and enable it to the treatment group, while the control group has access to the old one.
It’s easier to single out the elements that really move the needle in A/B tests. However, this means potentially running multiple tests, which takes time. Multivariate tests can render quicker results.
Main use cases for A/B testing in SaaS
A/B tests are one of the best-known kinds of experiments. Let’s look at situations when they are most suitable.
Improve conversion rates and attract more users
A/B testing is commonly used to optimize the conversion rates of landing pages.
For example, you could use it to find the best position for the demo button to increase the number of bookings.
However, in SaaS, the application of A/B testing goes well beyond the optimization of your website.
Drive in-app engagement and improve usability
Just like with websites, you can experiment with changes to different aspects of UI to find the best configuration.
So apart from button placement, you could use it to identify font styles and sizes, color patterns, or UI copy that provide the best user experience.
Test messaging impact on user behavior
Message testing is not limited to in-app contexts. For example, you can use them to test ads in your marketing campaign to see which versions will drive more conversions.
When should you NOT use A/B testing?
Although it’s a useful tool, A/B testing has limitations that restrict its application.
Not enough statistical significance due to a lack of data
For A/B tests to work, your website or product needs to have enough users.
If the sample size is too small, any findings won’t be reliable enough to make informed product decisions.
In fact, relying on such results is probably worse than not doing any testing because it gives you a false sense of certainty.
When the cost is not worth it for the desired outcome
Not every decision we make needs to be based on data or test results.
Some things are obvious. You can be pretty sure that a website with no CTA button is going to perform worse than one which has it.
A/B testing may sound uncomplicated, and you don’t need to be a data scientist to use them effectively. However, they can take a lot of resources and time to set up.
For starters, some of the A/B testing tools are pricey. What’s more, the engineers need to build the alternative version, you need to release it, wait for the app store to approve it, and then for users to download it. All of that before you even start collecting data.
That’s why you need to run tests only when they can have a big impact on generating user behavior insights. Otherwise, look for more cost-effective alternatives.
When data analysis can give you enough relevant insights
For example, you can see that your power users use features in a certain sequence. That’s how they get the best results. You just need to make the other user segments with the same JTBDs emulate their behavior and see what works for them.
If yes, that’s sorted. If not, then of course you can try other ways of testing your hypothesis.
Alternatives to A/B testing
User behavior tracking
You can easily track how users interact with the product and make others follow the same path. Once they do it, you collect more data to verify if it works for this user cohort as well.
Modern analytics tools allow you to track literally every move your user makes in your product.
For example, color-coded scroll maps show you how far your users reach on your page. This will help you identify its optimum length and find the best place to present key info.
Click tracking heatmaps, like the own below, give you insights into how each user group interacts with the tagged UI elements (your product’s features).
You can use it to find the most popular features for each user segment, including your promoters. You can then guide your detractors with similar objectives to those features and help them achieve better results.
Heatmaps are best used with session recordings that give an even more detailed picture of what users do.
In session recordings, you can see literally every single cursor move. Again, you can use it with user segmentation to see how most and least successful users engage with the product.
Usability testing is another A/B testing alternative used for UX research.
Techniques like guerilla testing, screen sharing, eye-tracking, 5-second tests, or first-click tests can reveal a lot about easy to navigate the product is.
Also, session recording can be used for usability testing as long as it has enough focus, like a specific task for users to complete.
User feedback surveys
You can trigger them contextually as soon as the user engages with the feature and ask them how they like it.
You can then segment users according to their answers and then cross-reference the results with product usage data to look for patterns.
To get an even deeper understanding, you can include qualitative questions in your surveys.
User interviews are an even better way to collect qualitative data about product usability and user experience. That’s because you can adjust your questions to the user and the context as you proceed.
Having said that, each set of interviews needs to have a clear purpose and so requires preparation.
Beta testing allows you to collect feedback from real users before you release the product to the wider public.
By giving access to the product to a sample of target users, we can reliably test its usability and identify any issues that need to be rectified before the launch.
This means that when the product or feature is finally out, there’s a good chance it will drive engagement and conversions.
Feature flagging involves showing and hiding features.
As you make the changes, you watch the impact they have on different users and how they engage with the product.
For example, removing a shortcut button on the screen can increase friction and increase the time to value.
However, removing the majority of buttons or taps can actually remove friction and speed up activation because users won’t get distracted by irrelevant features.
Best alternatives to A/B testing tool
Now that we know the alternatives to AB testing, let’s look at a couple of tools that can help you collect user data.
Userpilot is a product growth platform. It combines tools for collecting user data and acting on it to improve product adoption.
When it comes to product usage and behavior tracking, it allows you to tag features and then analyze how users engage with them. And by engagement, we don’t mean just clicks but also text inputs and even hovers.
You can then visualize users’ interactions with each of them on a heatmap.
The heatmaps can be filtered by user segments.
You can build user segments based on a range of criteria like individual feature usage or survey results. This allows you to target users with relevant in-app messages to drive their engagement.
Talking of surveys, designing them, and triggering them in a contextual way is dead easy. And that’s even without the Typeform integration which increases Userpilot’s data-gathering capability.
As this section is on alternatives to A/B testing, we’re not going to mention that you can use Userpilot to A/B test the effectiveness of your in-app onboarding patterns. That would be totally out of scope.
Fullstory is a well-known digital intelligence tool you can use to optimize the user experience.
It allows you to record user sections, collect engagement data without tagging, and create heatmaps and scroll maps of user actions.
No doubt, Fullstory is a powerful analytics tool. However, while you can use it to generate granular insights into user experience, you need other tools to act on them.
A/B testing is a powerful technique for optimizing UI and UX, but it has its limitations. When you don’t have enough users or the potential improvements will bring little value, they may prove too time-consuming and costly.
A/B testing alternatives like user behavior tracking or feature flagging can also help you assess the impact of the changes you’re planning to implement more quickly and without the expense associated with buying dedicated tools.
If you want to see how Userpilot can help you test your ideas and collect user data, book the demo!