Movesmart

2025

UX Designer

Figma, FigJam, Docs, Zoom

Movesmart Homepage
Movesmart Homepage
Movesmart Homepage

Overview

Movesmart is a AI-powered platform that match users with movers through Intelligence assistant.

Instead of endless Google searches or phone calls, users simply chat with an AI assistant that understands their needs and instantly recommends suitable movers with transparent pricing. Users book moving services in minutes, not hours.

Kick Off

Problem: Moving Shouldn't Be This Stressful

Moving consistently ranks as one of life's most anxiety-inducing experiences. For urban dwellers who frequently relocate, whether for job transitions or lease ends, finding reliable movers promptly becomes crucial.

But the current experience is broken:

  • Unexpected price increases that blind side users

  • Untrustworthy moving companies with hidden fees

  • Constant back-and-forth phone calls

  • No easy way to compare options or understand what's included

The real issue is we have no reliable, transparent way to find and book movers. They're left googling random companies or begging friends for recommendations, never knowing if they're getting a fair deal.



Understanding Moving Day Pain

I analyzed how existing services approached the moving problem:


  • Updater, Mover, Lugg: These platforms integrate multiple moving tasks digitally with clear pricing and service choices. Users appreciate the transparency and control.

  • Piece of Cake: A traditional moving company requiring phone bookings. While they focus on addressing the physical moving and storage.

Existing platforms either overwhelm users with too many options or force them through tedious phone calls. No one was creating a truly conversational, guided experience that felt easy and human.



I interviewed four participants (ages 30-65) who had recently moved or had prior moving experience. I wanted to understand their aspirations, frustrations, and what would actually make moving easier. Quote from them:


  • "There have been cases where costs increased unexpectedly." - Ray

  • "I hope I won't have to worry about anything and engage in too much communication." - GC

  • "I often use Google search and ask people with moving experience." - VG

  • "If furniture needed to be reassembled, I would expect the movers to handle that as well." - YW



I organized interview insights into themes to identify patterns:


  • Moving is exhausting: Both physically and mentally draining

  • Price anxiety is universal: Unpredictable increases create deep mistrust

  • Communication breakdowns are common: Late arrivals, ignored instructions, endless phone tag

  • Discovery is broken: Google searches and friend recommendations are the only options


  • Users want consolidation: A single platform handling multiple moving tasks

  • Personalization matters: One-size-fits-all solutions don't work for diverse moving needs

  • Mobile matters: Users need tracking, communication, and scheduling on their phones

  • Trust requires transparency: Clear pricing and service details reduce anxiety

Define

Who Am I Designing For?

I created proto-personas to focus on three primary user needs:


  • Quick Searching: No time for endless research

  • Transparent Costs: No surprise fees

  • Small-Scale Service: Not everyone needs a full-service moving company



How Might We?

I framed the design challenge with two questions:


  • How might we streamline the search process for users?

  • How might we provide personalized moving solutions tailored to individual needs?

Personas
Personas
Personas

Design

"At this stage, I explored how people naturally seek help in daily life. I noticed that AI assistants with simple prompts provide instant answers, dramatically reducing search time and cognitive load."


My concept

Create a user-friendly AI assistant that guides users through booking by understanding their needs in natural language, then mapping those needs to structured mover options with transparent pricing.


Core features:

  • AI chatbot that captures user intent through natural conversation

  • Personalized mover recommendations based on user input

  • Transparent, itemized pricing for all services

  • Support for small-scale, personalized moving needs



Concept to Reality

User Flows

I mapped out the complete journey from AI conversation to successful booking. This helped me understand each decision point and ensure the flow felt natural, not forced.


Low-Fidelity Wireframes

I started with quick sketches to explore the conversational interface concept. These rough wireframes let me experiment with structure without getting attached to visual details.

Once I had solid concepts, I brought my Low-Fi wireframe to my mentor and design group for critique. Their feedback helped me improve usability, remove unnecessary elements, and define the product's fundamental framework.

The guidance I received pushed me to answer: What's truly essential for booking a mover through conversation? What can we eliminate?

User Flow
User Flow
User Flow
Low-Fi Wireframe
Low-Fi Wireframe
Low-Fi Wireframe

Validate

Testing & Refining

Low-Fidelity Usability Testing

I conducted early testing with four participants, focusing on flow navigation, information clarity, and booking process understanding. This was critical: I needed to validate the AI interaction pattern before investing in visual design.


What went wrong:

  • Users didn't understand the review card's purpose

  • No one noticed that clicking prompt cards added them to the chatbox

  • The homepage felt cluttered and overwhelming

  • The AI lacked clear direction: users felt lost

  • Mover cards lacked sufficient detail

  • Information layout on mover cards felt disorganized

  • Service options were too limited

These findings were gold. They showed me that users wanted guidance, but they also needed clear visual cues and structured options - pure conversation wasn't enough.



High-Fidelity Usability Testing

I refined the design based on Low-Fi feedback and conducted a second round of testing. This time, I asked users to complete four key tasks:


  1. Enter requirements into the AI chatbot

  2. Chat with AI and choose a mover from recommendations

  3. Review the mover profile and select preferred services

  4. Review booking details, confirm payment, and finalize


The results were better. Users described the experience as "interesting," "simple," and "straightforward." But testing also revealed specific interaction issues that needed fixing.


  1. Unclear AI Prompts Interaction Patterns

    Based on testing feedback, I transformed prompt buttons into radio buttons and checkboxes, making it visually obvious which options allowed multiple selections versus single choices.

    I also enlarged the "Confirm" button so users clearly understood how to advance the conversation.


  2. Mobile Input Friction (Booking Section)

    Small input fields and tiny preference checkboxes for move location and details. Users accidentally tapped the wrong things, causing frustration.

    I enlarged input fields and preference options, changed them to horizontal scrolling, and reduced visual congestion. For time selection, I replaced the cluttered interface with a horizontal scroll picker.


  3. Information Overload (Booking Section)

    Users found the dropdowns distracting and couldn't quickly make a decision.

    I replaced dropdowns with number selectors and displayed prices directly beneath each item. The list format reduced visual clutter while making selections more direct and transparent.

    Half the users suggested combining date and time selection, so I consolidated those sections.

Interation
Interation
Interation

Final Mobile Version

Hi-Fi Wireframe 1
Hi-Fi Wireframe 1
Hi-Fi Wireframe 1

Final Desktop Version

Hi-Fi Wireframe 2
Hi-Fi Wireframe 2
Hi-Fi Wireframe 2

Prototype

UI Kit
UI Kit
UI Kit

Results & Impact

The final Movesmart experience delivers on its promise: making moving feel manageable through intelligent, empathetic assistance.


The AI Conversation Flow

Users open the app and are immediately greeted by a friendly AI assistant. Instead of filling out boring forms, they simply answer questions in natural language or select from suggested prompts.

The AI asks:

  • Where are you moving from and to?

  • When do you need to move?

  • What items are you moving?

  • Do you need additional services like packing or furniture assembly?

As users provide information, the AI confirms understanding and guides them toward the next decision, creating a flow that feels more like helpful conversation than data entry.


Personalized Mover Recommendations

Based on user input, Movesmart instantly matches them with suitable movers. Each mover card displays:

  • Clear ratings and reviews

  • Transparent, itemized pricing

  • Available services (packing, assembly, etc.)

  • Availability for the requested date

Users can tap any mover to see detailed profiles, read reviews, and compare options side-by-side.


Streamlined Booking

Once users select a mover, they review and customize services with clear pricing visibility. The checkout flow confirms:

  • Move details (date, locations, items)

  • Selected services with individual costs

  • Total price with no hidden fees

Users complete booking in minutes with complete confidence about what they're paying for.

Reflection

Designing Movesmart fundamentally changed how I think about AI in user experiences.

My initial designs treated AI like a text interface. But users wanted something that felt more like a helpful guide - someone who understood their stress and walked them through decisions.

Conversational AI works best when it combines natural language flexibility with structured visual options. Pure text conversation is actually harder for users than guided prompts with clear choices.


Mobile-First means Thumb-First

Early designs had tiny tap targets and cluttered layouts that worked fine on my laptop but were frustrating on actual phones.

I learned design with thumbs in mind. Horizontal scrolling, larger touch targets, and reduced density are must-to-haves on mobile. They're essential for usable experiences.