Overview
Background
Viator is a leading marketplace for travel experiences and a Tripadvisor company. Through Viator's app and website, they make it easy to explore more than 300,000 travel experiences—everything from simple tours to extreme adventures, and in their own words, "all the niche, interesting stuff in between."
Challenge
Provide Viator's app team with the insights and recommendations that would ultimately help drive significant user growth, feature adoption, and increase monthly active users.
My role
My involvement required me to understand Viator's business needs, identify their customers' pains, and validate solutions one of my Product Designers was creating. I tackled this with a wide range of generative and evaluative studies and BETA tests. From this, I fed the product team with a constant flow of insights and recommendations. And even on a handful of occasions, I presented my findings in 'all-hands' meetings to varying levels of the organisation.
Services
- User Research
- Gap Analysis
- Participant Recruitment
- Prototyping
- Customer Validation
- Usability Testing
Deliverables
- Research Plans
- Research Reports
- Journey Maps
- Prototypes
Approach
Process
Viator had many experienced researchers, yet they lacked a structure or system for how they went about research. I introduced the Atomic Research Framework (ARF) to systemise my own approach and hopefully to influence the wider team at large. ARF contains four simple steps starting with the study. From that study you collect data. With that data you create insights. From those insights you can make meaningful and purposeful recommendations.
Research tracts
Viator had many researchers working across similar problem and opportunity spaces at once. This meant there was a lot of overlap with varying context and use cases. Some would see this as wasteful; however, it actually helps build the entire business view of the customer in a more efficient way. This meant singular studies were lean, but always fed into another need across web and app. The first step any researcher had to do was conduct Gap Analysis across the repository.
Study №1
Nearby
In May 2022, I conducted a study on an app feature called Nearby, a way for users to pinpoint tours and activities in close proximity. My core objective was to understand user needs so I could ensure the feature's success. Before starting, I performed gap analysis across the research repository to ensure I didn't cover old ground.
I conducted the study with 86 participants in total (15 UK and 71 US), with a gender split of 44 males and 42 females. The participants completed 7 activities across 3 days. They included interviews, contextual enquiry, sorting exercises, and preference testing.
My findings revealed how participants feel towards the feature, providing recommendations for how it should be designed, specifically insights on naming, terminology, information architecture, and content strategy.
Study №2
First-time users
In July 2022, I conducted a Naturalistic Observation Study using the mobile app with a mix panel of participants. My goal was to understand where in the sales funnel travellers were having difficulty and how they go about making purchases.
The study consisted of first-time Viator customers/app users. I provided participants with a $100 voucher code to make a live purchase using the app. Overall, participants found the app user friendly, easy to use, and intuitive. They also believed Viator to have a good brand perception.
Yet, there were several key issues observed; participants didn't see value in allowing certain permissions; they felt there was an overwhelming number of search results and the filters, making it hard to find right-fit products; they couldn’t establish the level of product value, eg. "am I just paying for operator transport fees, or the actual tour itself?"; participants expected to find certain information at timely and relevant moments, however, they were often missing; and, some contradicting information blindsided participants causing distrust.
Study №3
Product display page
A product display page (PDP) is one of the most important pages on any website or app. Get this wrong and you can jeopardise millions in revenue. With this part of the journey scheduled for some TLC, it was my job to figure out what we could improve. I started this by performing a gap analysis leading to recommendations on how the designs could be improved.
With a new PDP design and a prototype ready, I conducted a study in September 2022 with a mix panel of participants to understand users' reactions. Overall, the PDP performed as expected and was considered well organised and digestible. However, there were some areas to improve, such as confusing messaging, seemingly in the wrong position, and two entire components requiring immediate attention. I noted a critical UX issue that left users bewildered, making the purchase decision harder and the products less compelling.
I conducted a fast follow-up study late October 2022 to answer any remaining questions or concerns with the updated proposed designs. Using qualitative moderated 1:1 depth interviews, including a card sorting activity and a prototype of proposed designs. My primary objective was to identify the correct information architecture (IA) to increase the likelihood that user would make purchase decisions, with a secondary objective to ensure the redesigned components met user expectations. Luckily, my previous recommendations for improving the IA and designs led to a position where only but a few minor tweaks were required.
Study №4
Wishlist
In April 2022, a study into trip planning and wishlist functionality for the Viator website established that there was value in Viator offering a place where travellers can save, organise and make decisions about experiences.
Come July 2022, I conducted a BETA programme study on the topic of wishlist with app users. My aim was to uncover current behaviours, expectations, and desires when saving, sharing, and collaborating on wishlists. Using this opportunity, I gathered feedback on day 0 designs finding that participants were interested in sharing things to do on trips with family and friends, with the aim to reach an agreement on what to do via Facebook Messenger, text message, and WhatsApp. Through this study, gained confidence in the day 0 designs, with participants believing them easy to use, useful and fun, while having the right information.
The final study in October looked to validate an assumption that users would relish in the ability to share and collaborate on wishlists with their friends and family. To do this, I planned a study with the intention of conducting user interviews and an activity to map out the customer journey so I could make recommendations for the user experience. With my attention required else where, I passed on the research intent document and plan onto another researcher to perform with success.
Conclusion
Working with Viator in a research-only capacity was a real eye-opener. There were great operational learnings with some opportunities to make their practice even more efficient and valuable. To date, I still haven't worked with a team better then their's from a research-only perspective. Seeing continuous discovery in action and how it feeds into continuous delivery, has helped shape how I ensure precision and predictability across many work tracts and business needs.
