How TickX uses AB testing to create a great customer experience
Our AB Testing Philosophy
AB testing is at the heart of our new feature optimisation and roll out at TickX. As a fast moving SaaS company we can add significant value for our partners by rapidly testing new ideas and ensuring they have a positive impact without relying on assumptions or gut instinct.
Our Director of Product Tom Crowle has 8+ years experience in AB testing across the events, travel and accommodation sectors. He’s passionate about the importance of AB Testing:
"AB testing is a great tool to understand how customers behave at scale. Relying on gut is not good enough in such a competitive landscape. Data is the way forward!"
But what exactly is AB Testing?
A/B testing is a method of comparing two versions of a product or marketing campaign to determine which one performs better. It is commonly used in fields such as marketing, product development, and user experience design.
Here's how A/B testing works:
Choose a goal: Determine what you want to optimize or improve, such as website conversion rates or the effectiveness of a marketing message.
Create two versions: Develop two versions of the product or campaign that you want to test. These versions should differ in only one aspect, such as the design, language, or layout.
Test the versions: Randomly show one of the versions to a group of people (called the "test group"), and the other version to a separate group of people (called the "control group"). Collect data on how the test group and control group respond to the two versions.
Wait for statistical significance: This is when there is enough data from the tests that we can be confident the results will be accurate.
Analyse the results: Compare the data from the test group and control group to see which version performed better.
Implement the winning version: If one version significantly outperforms the other, implement that version and continue testing to further optimize and improve your product or campaign.
A/B testing allows you to make informed decisions about how to improve your product or campaign based on real data, rather than relying on assumptions or gut instincts.
How does TickX use AB testing?
We’re obsessed with understanding the impact of some of the changes we roll out to our purchase experience. We’ve had some great learnings over the years.
We were really excited by the idea that introducing a ‘Best Seats’ popup at the seat selection step for theatre clients, would mean that their customers found it easier to find the right seats for them. The theory was that this would then lead to less friction in the purchase journey and increased sales of tickets - but equally the extra click could hurt conversion. The only way to know was to test it. We proved that this led to a 2.96% increase in conversion over the baseline, meaning a significant win for our clients.
AB testing can also be used to understand the impact of an existing step, and what removing it might do. Lots of our clients include ‘Addons’ or ‘Merchandise’ options in their purchase journey. We make it easy to skip this step if you do not want to add an extra item, but our clients do make significant revenue each year from ancillary upsells to merchandise, drinks, etc. However, we wanted to ensure that this extra step did not cause an impact to conversion that led to overall fewer ticket sales, and therefore offset the gains made from selling ‘Addons’. AB Testing helped us prove that including this step led to no impact on conversion, so our clients can safely keep this step in place and enjoy the benefits of additional revenue through ‘Addons’.
We love working with our clients and delving into customer insights to find problems that can be solved by developing new features and functionality. And we also love validating our new features through testing.
It can take time to get to statistical significance, but we are able to leverage data from customers across all our clients which means everyone can benefit from the results more quickly.
If you would like to hear more about how we use AB testing, or have any suggestions about an idea you’d love to see tested in ticketing please get in touch.