This area was new to me, so I began by thoroughly collecting and analyzing existing data, research, past A/B experiments, and our technical capabilities. I drafted and proposed a plan of action, consulting with the Group Product Manager and the Directors of Design & Product to align on timelines, scope, and deliveries.
Communication was crucial due to the project's large scale and its impact across different business verticals. I created a stakeholder map to strategize communication effectively and developed a comprehensive communication plan that included sending emails, publishing updates on the workplace platform, and conducting demos and playbacks with stakeholders.
I also collaborated closely with the Senior Product Manager from one of Trip Types teams responsible for the discovery phase of the user journey to identify business opportunities. I faciliteted and contributed to a SWOT analysis to better understand the risks and opportunities, which would guide our investment decisions.
Based on existing knowledge and research I identified existing pain points our users have:
To generate a variety of ideas and opportunities related to this overarching concept, I conducted a workshop involving the entire Trip Type track (3 teams), which included designers, product peers, engineers, and stakeholders from data science and machine learning functions (over 30 people in total). Our strategy was largely dependent on existing data sources and machine learning models, so their involvement in a co-creation session was crucial for leveraging their expertise and securing early support.
I organized and facilitated a Big Ideas: ideation workshop, where we crafted How Might We (HMW) statements to steer our ideation around specific themes: Personalization, Intent Collection, and Connected Trip.
This process led us to develop several high-level ideas that achieved our goal of enhancing destination discovery for flexible customers and capturing their intent to deliver more personalized content.
I scheduled and organised stakeholder playbacks to present these ideas and ensure alignment with company and departmental goals. This helped us gather feedback and incorporate it in the next steps, leading us to pursue both a visionary North Star vision and immediate, actionable solutions to validate our direction through short-term experiments.
For the North Star vision, I facilitated a workshop with + 15 members of the UX Community to ideate & visualise prioritised ideas using exercises like "The Worst Idea Ever" and "Crazy Eights." This workshop generated multiple viable ideas for future development.
From user research, I learned that to provide a personalized product, the experience needs to be relevant, convenient, and transparent, and the user needs to be able to have control. Based on these learnings, I drove and guided discussions with different crafts on how we might achieve this.
Machine Learning and Data Science - I worked with specialists from these crafts to define how we might provide relevant recommendations in our experience. We factored in seasonality, availability, and relevant content availability (being able to show destination photos in the relevant season). These discussions led to MVP for our data & ML settings and highlighted potential lines of further experimentation.
UX Writing - I led a conversation with a UX writer exploring how we might meet users' expectations for visibility and clarity on how and why we use their data, and how we can incorporate this messaging in our experience.
Engineering - Together with the Engineering Manager and Data Scientist, I helped explore capabilities and flows that will help us store information about users' trip preferences (within and outside of sessions), and how we might ensure transparency and control for users within their User Profile.
These conversations helped me ensure user-centricity and laid the foundations for further creation of the design strategy and timelines aligned with other crafts.
Together with the Product Manager, I created a vision deck that summarized our findings and showcased a story on how we might solve it for our users. Our vision was to create an end-to-end delightful experience for flexible users who might have their trip type in mind but are undecided on a destination. We planned to achieve this by providing a delightful and relevant travel recommendation experience, personalized to our users' trip intent.
Throughout this project, clear communication and engagement with all stakeholders from the start ensured that our vision was well-received and laid a solid foundation for strategic and design developments moving forward.
I created a design strategy and a roadmap for the design, research, and content writing functions to help us plan our actions accordingly. It covered:
The first initiative we planned to test in production was the introduction of the Quiz feature. After discussions with the Product Manager and Marketing Team, we decided to launch it through various entry points, including an email campaign, the homepage, and mid-funnel stages, targeting different segments. One of these segments included individuals we had previously identified as "trip type" travelers.
In this initial iteration, our objectives were to understand user behavior and to test the hypothesis that creating an engagement loop would help retain customers and improve recommendations, ultimately leading to more and better-matched bookings.
I developed a straightforward flow for the first version of the Quiz, consisting of four steps and a destination recommendation page. We utilized existing product patterns in this first iteration, making only minor adjustments and focusing on the content and logic of the experience to enable faster learning and time to market. Additionally, we used the Quiz to collect data on people's choices, which would allow for enhanced personalization for returning users.
As an iteration of our quiz, we opted for a different approach: promoting our quiz with preliminary recommendations on the homepage for known customers, allowing them to customize these suggestions using destination filters.
This second iteration proved successful, showing increased engagement with the feature and greater utilization of the filters. Users were presented with all options at once, eliminating the need for a multi-step process and allowing them to decide how many filters to apply. We conducted additional user testing sessions to understand potential filters and factors that customers consider when selecting a travel destination, which provided valuable insights. One crucial factor identified was budget, prompting us to plan further iterations to include a budget filter.
