Context & Background
Rolling Chow is a platform designed to simplify the process of hiring food trucks for events by connecting users with curated vendors through an online experience.
Despite strong user interest, the platform faced a critical challenge: low completion rates on the booking submission form, particularly on desktop where most users were engaging with the product.This gap between user intent and completion represented a significant missed opportunity for the business and highlighted the need to better understand the user experience across the booking journey.
As a UX Researcher, my role was to identify where users were experiencing friction and uncover opportunities to create a more seamless and effective path to submission.
The ChallengeHow might we reduce drop-offs and increase form submissions…
while determining whether the experience requires a full redesign or targeted UX improvements?
Specific Goals
- Understand the key friction points causing abandonment
- Evaluate whether incremental improvements or a full redesign would have the greatest impact
- Gather actionable insights to optimize the submission flow and increase conversions
- Analyze competitor experiences to identify opportunities for differentiation and improvement
Key Metrics & Signals
To validate the scale of the problem and identify key friction points, I analyzed a combination of quantitative and qualitative signals across the experience.
- 87% drop-off rate across the submission flow
- CSAT score of 3.9/5, indicating friction in the experience
- 46% of customer inquiries were follow-ups seeking clarity on next steps after submission
Methodology: Two-Phased UX Evaluation
Phase 1: Funnel & User Friction Analysis
Purpose: Understand where and why users were abandoning the submission journey.
This phase included:
✓ Google Analytics funnel exploration
✓ Drop-off analysis by device especially mobile
✓ CSAT / satisfaction survey insights
✓ User behavior observations from recordings
This phase answers:
“Where is the experience breaking down for users?”
Phase 2: Competitive Benchmark Analysis
Purpose: Understand how similar food truck/catering platforms support booking decisions and identify opportunities to improve or differentiate Rolling Chow.
This phase included:
✓ Competitor review
✓ Navigation and category comparison
✓ Booking/form flow comparison ✓Trust signals, such as reviews, FAQs, pricing clarity
✓ Vendor discovery patterns
This phase answers:
“What can Rolling Chow learn from the market, and where can it create a better experience?”
Key Findings & Opportunities
Insight
Friction in the Submission Flow Reduces Completion
Evidence
Funnel analysis in Google Analytics revealed significant drop-offs across the submission journey, particularly on mobile. These findings were reinforced by Hotjar session recordings, which showed users struggling with repetitive form inputs and inefficient navigation patterns (e.g. back-button behavior forcing users to restart the process).
Lack of Transparency Creates Hesitation
Limited Trust Signals Impact Decision-Making
Lack of Post-Submission Clarity Reduces User Confidence
Through collaboration with the CX team, we analyzed customer inquiries and support tickets to identify recurring concerns. Combined with insights from CSAT surveys (1–5 scale with open comments), this revealed a clear need for upfront information, particularly around pricing, vendor availability, and expected response times.
The absence of reviews and social proof reduced user confidence when selecting vendors. Users lacked reassurance around vendor quality, leading to hesitation and increased likelihood of abandoning the process before submitting a request.
Analysis of customer inquiries revealed that 46% of emails were follow-ups related to response times, indicating that users were unsure about what would happen after submitting a request.
This lack of clarity reduced confidence in the process, making users less likely to complete the submission.
Benchmark Analysis
The benchmark analysis showed that competitors focus primarily on large events and provide limited support for early decision-making. While reviews and social proof exist, they are not effectively integrated to build user confidence.
This reveals an opportunity for Rolling Chow to differentiate by supporting smaller events, improving transparency, and guiding users more effectively throughout the booking process.
Identifying Friction Points in the Booking Journey
The journey map revealed that abandonment was not caused by a single issue, but by compounded friction across the experience.
Key breakdowns occurred during vendor discovery (limited filtering and unclear pricing), form completion (high effort), and post-submission (lack of response expectations).
These insights point to a clear strategic direction: reduce friction, increase transparency, and strengthen user confidence to drive higher completion rates.
Defining Opportunity Areas
Based on insights from the different methodologies, I translated key friction points into a set of opportunity areas aimed at improving the booking experience.
Rather than following the linear user journey, these opportunities are prioritized based on their potential impact on conversion—starting with reducing friction in the submission flow, followed by improving decision-making during vendor discovery, and finally reinforcing user confidence through clearer expectation-setting.
This approach ensures focus on the most critical barriers affecting form completion while addressing the experience holistically.
Reduce Friction in the Submission Flow
To reduce drop-offs, the submission flow was redesigned into a multi-step experience that breaks the process into manageable steps.
By minimizing repetitive inputs and grouping related information, the form reduces cognitive load and makes completion faster and more intuitive.
Improve Transparency and Build Decision Confidence
To reduce uncertainty during vendor discovery, I introduced filters for budget and guest count, along with clearer pricing guidance and stronger trust signals such as ratings and vendor reliability.
This enables users to quickly identify suitable vendors, improving confidence and reducing friction before submission.
Clarify Expectations Across the Booking Journey
To address user uncertainty—highlighted by a high volume of follow-up inquiries—I introduced clearer expectation-setting across the booking journey, including a “How it works” section before submission and improved confirmation messaging after submission.
This helps users understand what to expect, increasing confidence and reducing hesitation.
MoSCow Conclusions
Through collaboration with Product, Engineering, and CX, we aligned on a set of prioritized solutions based on their potential impact on conversion and implementation feasibility.
Reducing friction in the submission flow emerged as the highest priority. The introduction of a multi-step form and the elimination of repetitive inputs were identified as critical to addressing the high drop-off rate observed during form completion.
In parallel, we identified the need to set clearer expectations across the journey. Enhancing the confirmation experience and introducing lightweight expectation-setting (e.g. “How it works”) were considered high-impact, low-effort improvements to reduce uncertainty and improve user confidence.
Improvements to vendor discovery—such as filters for budget and guest count, pricing guidance, and stronger trust signals—were prioritized as secondary enhancements to support better decision-making without delaying the implementation of core conversion improvements.
This prioritization ensured focus on solving the most critical user and business problems first, while creating a foundation for future experience enhancements.
The following concepts were developed as low-fidelity proposals to validate key improvements and align with the team. Final visual design and implementation were later refined in collaboration with UI and engineering.ress the key friction points identified during research, a set of potential design directions was explored.
Impact
Impact was observed over an approximate period of 3–4 months following the implementation of the proposed UX improvements. Performance was monitored using Google Analytics and customer feedback channels, comparing user behavior before and after the changes.
The results reflect improvements in form completion rates and reduced user friction, aligned with the key issues identified during the research phase.
Conclusion
This project highlights how focused UX improvements can significantly impact business outcomes without a full redesign.
By addressing key friction points and aligning solutions with user and business needs, the experience became more intuitive, transparent, and effective—resulting in higher form completion and improved user confidence.