Checkout conversion case study

Checkout Conversion

Love Holidays is the fastest-growing online travel agency in the UK. The checkout optimization increased sales by 5.22% year on year.


Love Holidays serves its B2C customers by offering a unique way to search for their next holiday, ensuring that all customer needs are catered to in one place. The search doesn't prompt customers to specify a date or destination before they can perform a search unlike many other travel websites, but it allows customers to search by what matters to them the most such as budget, board basis, star rating, type of property, facilities, and even temperature.

The eCommerce Director had an ambitious growth strategy; to increase conversion, grow online revenue and expand further into international markets. To boost the sales of the website, he wants users to have a hassle-free experience from cart to checkout to improve conversion rate.

As a UX and UI Designer, it was my responsibility to improve the checkout experience as well as the conversion rate by using research and data effectively. I used qualitative and quantitative research techniques to understand users' behaviour, problems, and needs. I worked with senior stakeholders to establish realistic goals, liaise with the product owner to prioritise tasks and stories, create high-fidelity designs and build them with the help of the engineering team, set up A/B tests on Optimizely, and observe data patterns with a data scientist to make informed decisions.

When I joined Love Holidays, the company's testing strategy was focused on the number of tests that went live in a week. However, after a few meetings with senior stakeholders, we altered the focus of testing to a more rigorous process of user discovery. I traded the number of tests for the quality of tests by testing and iterating on concepts even if they did not pan out the first time. In doing this, I find enormous gains that would have been left undiscovered without this process improvement.

Love Holidays was greatly pleased with the overall concept and highly appreciated the approach I acquired for the data-informed design. The project observed a 5% increase in conversion after its release for direct customers and travel agents.

The Approach

User and business needs

Love Holidays is the fastest-growing online travel agency in the UK. Part of an organisation's value proposition is to put customers first, and one way to put customers first is with A/B testing, to create websites that better serve customers. Most of their traffic comes from search and costly paid ads. The company wanted to increase conversions on their checkout and get a better return on their ad spend.

The company had done a lot of testing in the past, the testing strategy was focused on the number of tests that went live. After having a few meetings with senior stakeholders and product owners, the business agreed to trade the number of tests for quality tests by testing and iterating on concepts that could resolve user problems and increase business revenue. I had a good understanding of business goals. Next, I dived deep into user research to understand user needs and goals.


Love Holidays visitors had a wide range of problems. Each problem is a potential conversion killer, so I sought to identify them all, using the following techniques:

a) Usabilla feedback survey: I added a feedback survey on the checkout pages to help me determine why certain visitors were not able to accomplish what they set out to do.

b) Exit survey: I added an exit survey to specific pages where I wanted to learn further details about specific problems.

c) Live chat transcripts: I read hundreds of lines of live chat transcripts to discover what concerns visitors had before booking.

d) Lists of the most common inquiries: I asked the customer support team to create lists of the most common inquiries. The customer support people are an often-overlooked source of valuable insights. The feedback from the customer support team was consistent with what I had discovered through the other research channels, and they helped me understand visitors' problems in a deeper, more empathic way.

e) Shopping cart abandoners survey: I asked the marketing team to email a survey to shopping cart abandoners, asking them among other things what had prevented them from completing their bookings.

I also gained many useful insights from Hotjar. For example,

User problems

The research revealed a huge amount of detail about website visitors. For example, I identified that visitors were facing particular problems within the offer summary and checkout pages. One of the major problems was visitors were unable to find all available rooms on the offer summary page. We take a detailed look at each of those below.

1. Zero flight result: Users land on the check availability page with zero flight results as they don't know what effect their current filtering option has on the number of available flights.

Zero flight result

2. The opt-out option at the bottom: Users were not sure why the opt-out option for hotel transfers, airport parking, and travel insurance is at the bottom. It is logical to have an opt-out option on top which doesn't cost anything and then upgrades underneath sorted by price.

Default selection at bottom

3. Incremental price per person on room types: Users find it difficult to understand how much the total price per person they have to pay for the selected room type.

Total price per person

4. Undefined party size: The room options don't show how many guests can stay in a room. It is a challenge to find a room which can accommodate a family.

Guest per room

5. Inconsistent design: The offer summary page on mobile looks unprofessional, e.g. the button has various colours and styles. Some users find it hard to understand which button does what, and don't feel confident to continue with their bookings.

Inconsistent design

6. Difficult to see all available room options: Users struggle to see all the available room options for the booking. They continue to the next page without clicking on the "Show more rooms" link. They thought that it was not a link but a selection of the room options.

Hidden more room options


Though it is not glamorous work, the time that I spent understanding the visitors paid off many times over when it came to making improvements to the website. The research gave me a clear understanding of the users' problems, which made it easier for me to design winning tests.

I designed many concepts and ran several tests to make improvements. However, it is laborious to cover all of them. I will explain two of the tests, which I found interesting because each of them involved a small change to the website that had a disproportionately large impact on user experience and business revenue.

Social Proof - Add Tripadvisor Ratings

Some new visitors voiced concern that they had never heard of Love Holidays before. I needed to find a concise way of showing how popular Love Holidays is, and how the hotels they sell are highly rated to gain visitors' confidence. The most visited and trusted place to read about hotels is TripAdvisor. I added a Tripadvisor rating on the offer summary page in the footer just underneath the "Continue" button as shown in the variant below which increased 30 bookings per day and a 5.4% uplift in sales.

Add Tripadvisor hotel rating Social proof a/b test result

Clarity - Change the link into a button

The research revealed that many visitors were struggling to see all the available room options on the offer summary page. There was an opportunity to sell high-end rooms. I changed the link to a button with an icon to illustrate more room options are available in the booking.

The test result shows that the clarity increased 13 bookings per day and a 5.22% uplift in sales.

Change link into button Clarity a/b test result

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