Loveholidays: Checkout Optimisation

Summary

Loveholidays serves its B2C customers by providing a unique way to search for their next holiday, ensuring that all customer needs are addressed in one place, including hotels, flights, city tours, and transfers. The search does not require customers to specify a date or destination before conducting a search, unlike many other travel websites. Instead, it allows customers to search based on what matters most to them, 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 website's sales, he aims to provide users with a seamless experience throughout the checkout funnel, ultimately enhancing the conversion rate.

As a UX and UI Designer, it was my responsibility to enhance the checkout experience and the conversion rate by effectively utilising research and data. I employed both qualitative and quantitative research techniques to understand users' behaviour, problems, and needs. I collaborated with senior stakeholders to establish realistic goals, liaised with the product owner to prioritise tasks and stories, created high-fidelity designs, and developed them with the help of the engineering team. Additionally, I set up A/B tests on Optimizely and analysed data patterns with a data scientist to make informed decisions.

When I joined Loveholidays, the company's testing strategy focused on the number of tests that went live within a week. However, after a few meetings with senior stakeholders, we shifted the emphasis of testing to a more rigorous process of user discovery. I exchanged the quantity of tests for the quality by testing and iterating on concepts, even if they did not succeed the first time. In doing so, I discovered significant gains that would have remained undiscovered without this process improvement.

Loveholidays was very pleased with the overall process and greatly appreciated my approach to data-informed design. I was the top performer on the leaderboard for several weeks, a method through which Loveholidays recognised high-performing teams and celebrated their weekly successes. The project resulted in over a 5.22% increase in checkout conversion following its release for direct customers and travel agents.

discovery

User and business needs

Loveholidays is the fastest-growing online travel agency in the UK. A key aspect of an organisation's value proposition is putting customers first, and one effective method for achieving this is through A/B testing, which helps create websites that better serve customer needs. Most of their traffic originates from search engines and expensive paid advertisements. The company aimed to increase conversions at the checkout and improve the return on its advertising expenditure.

In the past, the company had conducted numerous tests; however, the testing strategy was primarily focused on the sheer number of tests that went live. After several meetings with senior stakeholders and product owners, the business opted to prioritise quality over quantity by testing and iterating on concepts capable of resolving user issues and boosting revenue. I gained a solid understanding of the business goals. Subsequently, I conducted in-depth user research to understand user needs and objectives.

Research

Users of Loveholidays faced various issues. Each problem presents a potential barrier to conversion, so I aimed to identify them all by employing the following techniques:

• Usabilla feedback survey: I included a feedback survey on the checkout pages to help me ascertain why certain visitors were unable to achieve their goals.
• Exit survey: I added an exit survey to select pages, aiming to gather more information about specific issues.
• Live chat transcripts: I reviewed hundreds of lines of live chat transcripts to identify the concerns visitors had before booking.
• Lists of the most common inquiries: I requested the customer support team to compile lists of the most common inquiries. The customer support staff are often an overlooked source of valuable insights. The feedback from the customer support team aligned with what I had uncovered through other research channels, providing a deeper and more empathetic understanding of visitors' problems.
• Shopping cart abandoners survey: I asked the marketing team to send an email survey to shopping cart abandoners, inquiring about what had prevented them from completing their bookings.

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

• Users session recordings: I watched recordings of user sessions, which offered valuable insights into how users navigate the website and the points at which they experienced frustration and left.
• Funnel drop-off: I established various funnels to examine how drop-out points varied by user type.
• Form analytics: I installed Form Analytics, which enabled me to detect issues regarding user interaction with various form fields. This assisted me in optimising the checkout process.

User Problems

The research revealed a significant amount of detail about website visitors. For example, I discovered that visitors were encountering specific problems on the offer summary and checkout pages. One major issue was that visitors were unable to find all available rooms on the offer summary page. We take a detailed look at each of these below.

1. Zero flight results

Users arrive on the check availability page with zero flight results because they are unaware of how their current filtering options affect the number of available flights.

2. The hotel transfer opt-out

Users were uncertain about the placement of the opt-out option for hotel transfers, airport parking, and travel insurance at the bottom. It would be more logical to have the opt-out option at the top, which incurs no cost, with the upgrades listed underneath, sorted by price.

3. Incremental price per person on room types

Users struggle to understand the total price per person they must pay for the chosen room type.

4. Undefined party size

The room options do not specify the maximum number of guests that can stay in a room. This makes it challenging to find a room that can accommodate a family of four.

5. Inconsistent design

The offer summary page on mobile appears unprofessional; for example, the button displays various colours and styles. Some users find it challenging to grasp the functions of each button, which undermines their confidence in proceeding with bookings.

6. Difficult to view all available room options

Users find it challenging to view all the available room options for the booking. They proceed to the next page without selecting the "Show more rooms" link, believing it to be just a display of the room options rather than an interactive link.

Design

Although it is not glamorous work, the time I spent understanding the visitors paid off multiple times when it came to making improvements to the website. The research provided me with a clear understanding of the users' issues, which made it easier for me to design winning tests.

A/B Testing

I designed numerous concepts and conducted several tests to make improvements. However, it is tedious to cover them all. I will explain two of the tests that I found intriguing, as each involved a small change to the website that had a significantly large impact on user experience and business revenue.

Social Proof - Add Tripadvisor Ratings

Some new visitors expressed concern that they had never heard of Loveholidays before. I needed to find a concise way to demonstrate how trusted and popular Loveholidays is and how the hotels they offer are highly rated to instil visitors' confidence. The most visited and trusted source for reading about hotels is TripAdvisor. I added a TripAdvisor rating on the offer summary page in the footer, just beneath the "Continue" button, as shown in the variant below, which resulted in an increase of 30 bookings per day and a 5.4% uplift in checkout conversion.

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 indicate that more room options are available in the booking.

The test results show that clarity increased by 13 bookings per day and a 5.22% uplift in checkout conversion.