Intro

Omio is a travel ticket seller. Millions of people visit Omio every day, but around 95%* leave without making a step into the ticket sales process, let alone a purchase. This is where Product Design and UX Research come in.

*number changed for confidentiality reasons)

Multivariate Test

To find out how to increase conversion

1. From Google to Omio landing pages, and

2. From landing pages to the Omio ticket search

to ultimately reach an uplift of the unique booking rate (Key Metric), I designed a multivariate test.

First, I evaluated the current experience using Baymard and User testing.

Hypotheses

Once having identified several growth opportunities, I went on to write hypotheses to test.

Test Design

From there, I went on to design nine variants to test alongside the control. Each of them isolates one single change so that the effects can be measured and interpreted properly.

Test Results

After two weeks of runtime, the experiment returned statistically significant results.

1. Seven of the nine variants did not show a significant difference from the control.

2. Variants 4 and 6 however, showed significant uplifts in the key metric conversion to ticket search.

Secondary Metric

Another outcome worth mentioning is the secondary metric of App installs. While changing the position of the App USP (Download our app) did not have effects on conversion to search or booking, it did significantly increase App installs (Web to app conversion).

Next steps

The results both answered and posed new questions. The next steps will be:

1. A qualitative investigation on the impact of removing our brand illustrations on the customer experience. We know now, that it increases booking volume. But why is that? And what are the effects on the brand?

2. A quantitative test combining the two successful variants. Does that further increase the uplift, or will it have the opposite effect?