Move Cost Calculator
A Self-Service Quoting Experience that Converts Intent Into Action
Overview
The Move Cost Calculator was the least effective sales tool on the Ship Smart site, with the highest bounce rate. It failed to meet the needs of digital-first users, resulting in frustration and missed opportunities. Many users abandoned the quoting process to call for help, which increased support workload and slowed sales.
I redesigned the Move Cost Calculator from the ground up to reduce friction, support self-service quoting, and answer top customer questions before they had to call. The result is a mobile-first, guided experience that increases conversions, improves lead quality, and builds trust through clarity and integration with Ship Smart’s new tracking system.
KPI’s
↑ 24% Quote completion rate
↑ 18% Conversion to booked shipments
↓ 22% Quote-related support tickets
↓ 25% Average time on form
Role: Lead UX & Product Designer
Responsibilities: Research, Systems Thinking, Visual Design, UX Writing, Prototyping, Testing, Mobile-First Design, Collaboration with Dev & Sales
Timeline: 12 Months
Tools: Figma, Google Analytics, Screen Recordings, User Interviews
My Process
Design Question
How might we transform Ship Smart’s highest drop-off sales form into a guided self-service experience that builds trust, reduces friction, and increases conversion?
Research & Discovery
Reviewed Google Analytics to identify bounce rates and drop-off points
Analyzed screen recordings to observe real customer friction
Conducted stakeholder interviews
Analyzed 2,783 live chats (95% confidence sample)
Comparative research across industries
Voice of Customer
Key Insights
I identified six major flaws contributing to system failure, including a chat bug that resulted in a 10% lead loss and unmet expectations among digital-first users.
Search Friction
Dead-End Workflow
Missing Details = Broken Quotes
No Way to Customize
High Drop Rate
Language Didn’t Match Users
Searchability
I rebuilt the backend system by organizing item names, adding common aliases, and creating searchable categories. I analyzed user chat transcripts to gain a better understanding of how people describe their belongings and ensure an intuitive experience.
Personas
Building on the previously identified gap in digital-first users, I developed nine personas to capture the full range of customer behaviors and needs. This project specifically leveraged the missing Millennial and Gen Z segments to create a dedicated persona that shaped a more modern and intuitive quoting.
Revised User Journey
The revised journey presented a clear blueprint that outlined the design's goals and essential benchmarks, from inventory input to transparent pricing, guiding users confidently from quote to conversion.
Wireframe
I began with wireframing to outline the complete quoting flow and pinpoint where users encountered issues or abandoned the process, particularly on mobile devices. At this stage, the emphasis was on information hierarchy, sequencing, and decision points.
Low-fidelity Prototyping
The prototype aimed to streamline inventory building, addressing the slow manual entry that caused user drop-offs. I tested a new model that let users quickly select predefined item groups based on space types (e.g., House, Apartment). This phase also included contextual questions under section headers, answering common queries from sales calls. This approach reduced uncertainty, supported self-service, and kept users engaged in the flow.
MidFi Prototyping Free-Text Search
At this stage, the focus shifted to enhancing speed and accuracy with a search-first inventory experience. The inventory field was redesigned as a free-text search bar preloaded with popular items based on historical data. As users typed, the system provided real-time, refined suggestions that corrected spelling and narrowed down results. This interaction reduced guesswork, helping users quickly find common items and preventing errors that led to hesitation or abandonment.
MidFi Prototyping Category Search
The design adopted a guided, browse-driven approach for inventory entry, acknowledging that not all users prefer to start with a search. Items were categorized by room and category, enabling users to make selections in a familiar manner. This approach helped users feel more oriented, reduced decision fatigue, and built early momentum, aiming to see if structured discovery could decrease abandonment for those needing reassurance before committing details.
Final Design
Results & Business Impact
The redesigned Move Cost Calculator transformed Ship Smart’s most frequently abandoned touchpoint into a guided, mobile-first quoting experience. By simplifying the process, addressing common questions upfront, and integrating backend tracking, this tool evolved from being a sales bottleneck into a high-performing self-service asset.
KPI’s & Improvements
↑ 24% Quote completion rate
↑ 18% Conversion to booked shipments
↓ 22% Quote-related support tickets
↓ 25% Average time on form
Built user confidence and improved trust in the quote process
Reduced support burden by minimizing calls and follow-ups
Modernized the quoting funnel to meet digital-first expectations
Eliminated most user complaints about item search confusion.
What I Learned
This project changed how I think about user input and conversion design. I learned that quoting tools aren’t just forms; they’re the first moment of trust. When users can’t find what they’re looking for or don’t feel guided, they leave. Real impact occurs when you design around how people actually search, make decisions, and self-serve.
