Understanding frictions in a user support journey
My role: Lead user researcher
Team: Product manager, designer, 2x data scientists, tech lead, operational product managers.
Context:
The customer support department for a Southeast Asian hotel booking platform wanted to reduce the number of incoming support requests (email, phone, chat) from hotel partners, and improve overall partner experience.
Brief:
Identify frictions in the user flow when hotel partners try to access support. Understand the root causes behind hotels making contact.
Outcomes
Identified cost saving opportunities of $600,000 per year.
Gained leadership approval for two scrum teams to work on development of new recommended support channels.
Delivered insights on root causes of partner issues and unknown frictions in the user journey to relevant teams.
Initiated investigation into and fixing of company software bugs following evidence collected in research.
Process
I held a kick-off workshop with all relevant stakeholders to surface questions and assumptions related to the hotel support journey.
I then partnered with a data analyst.
We looked into:
which hotels, in which countries, showed the highest rate of support requests per number of bookings,
how requests varied by channel type (phone, email, chat).
the rate of repeat requests by channel type and reason for escalation.
From this data analysis, I selected a set of hotels across three countries (Thailand, Malaysia, Taiwan) for my team to learn from.
I conducted in-depth interviews with hotel staff, allowing them to recall their experience trying to contact the hotel booking platform for support. They showed us various documents that enriched this description, such as incident reports.
We observed participants using various channels for different hotel booking platforms to understand how raising support requests fit into their workflow. This surfaced the affordances of different channels and frictions they experienced.
I designed an open card sort activity to understand how hotel users named and categorised their issues. This highlighted the differences between how users explained their needs versus how we named them internally.
After team analysis, we walked through a possible new support journey using rough sketches.
I worked with our designer to create a paper prototype for testing the flow in our next round of interviews.
User journey mapping with the team.
Testing paper prototypes in the users’ context.
I held multiple group analysis sessions with the product manager, designer, data scientists and tech leads before agreeing on a set of findings and next steps to deliver to senior leadership.
We affinity sorted the qualitative data collected in the field into themes.
Working with data analysts, we investigated the flow of support requests through different databases to trace and identify potential bugs.
As a team, we prioritised a set of insights to inform the design of new support channels.