Empower Moving Service

Empower
Moving Service

Empower
Moving Service

Redefining moving services through both multi-touchpoint channels, delivering a confident experience for first-time users, and ultimately increasing the conversion rate from first-time users to loyal consumers.

Bianca Falcão | Camille Zhang | Conti Fan | Hailin Chen | Ravali Maheshwaram

Bianca Falcão | Camille Zhang | Conti Fan | Hailin Chen | Ravali Maheshwaram

Bianca Falcão | Camille Zhang | Conti Fan | Hailin Chen | Ravali Maheshwaram

Sep, 2025 - Nov, 2025 10 weeks

Sep, 2025 - Nov, 2025 10 weeks

Sep, 2025 - Nov, 2025 10 weeks

Get an overview of our project

Design Process

Design Process

Empathy

  • Online Review Analysis

  • User Interviews

  • Field Observation

Define

  • Ecosystem Map

  • User Archetype

  • Customer Journey Map

  • Multi-Channel Planning

  • Service Blueprint

Ideate & Prototype

  • Conversational Design

  • Cardboard Prototyping

  • Information Architecture

  • Machine Learning Model

  • Kano Model Analysis

  • Interaction Flow

Test

  • Desktop Walkthrough

  • Wizard of Oz testing

  • Usability testing

Empathy

  • Online Review Analysis

  • User Interviews

  • Field Observation

Define

  • Ecosystem Map

  • User Archetype

  • Customer Journey Map

  • Multi-Channel Planning

  • Service Blueprint

Ideate & Prototype

  • Conversational Design

  • Cardboard Prototyping

  • Information Architecture

  • Machine Learning Model

  • Kano Model Analysis

  • Interaction Flow

Test

  • Desktop Walkthrough

  • Wizard of Oz testing

  • Usability testing

Empathy

As first-time movers ourselves, we’ve experienced the uncertainty that comes with preparing for a move—navigating logistics, packing belongings, and facing the unfamiliar task of driving a large rental truck.


This personal experience sparked a deeper question:

Are others going through the same sense of overwhelm? At which point in the journey do they feel the most uncertain, and what support do they actually need?

We began with reviewed nearly 1,000 user reviews on the Google Play Store, clustering common keywords and sentiments to identify recurring frustrations.


To validate our initial findings from review analysis, we conducted in-depth interviews with

5 users who had rented U-Haul truck

2 employees from local U-Haul stores.

These conversations gave us a more nuanced understanding of both user frustrations and internal service gaps.

By combining app review analysis, user interviews, and in-person staff conversations, we identified six core issues that frequently disrupt the U-Haul rental experience.

By combining app review analysis, user interviews, and in-person staff conversations, we identified six core issues that frequently disrupt the U-Haul rental experience.

By combining app review analysis, user interviews, and in-person staff conversations, we identified six core issues that frequently disrupt the U-Haul rental experience.

Define

Who is our target user? What is their psychographic?

Pain point

Goal

Swipe above to explore more details about the user archetypes.

Although our archetypes represent different backgrounds, motivations, and levels of confidence, they converge at key friction points throughout the U-Haul rental experience.

What unites them is not who they are, but what they experience.

Across all user types, we identified a consistent set of unmet needs and recurring frustrations, especially related to confidence, clarity, and coordination. These shared pain points became the foundation for reframing the core problem we aimed to solve.

Driving Anxiety

The stark differences between standard cars and U-Haul trucks (larger blind spots, unique control systems) cause hesitation and worry.

Decision Overload

Confusion in choosing the correct truck size leaves users overwhelmed, unsure about matching their cargo with available options.

Time Pressure

Tight moving schedules amplify anxiety, reducing users' capacity to prepare adequately.

To better understand how these shared frustrations unfold throughout the rental journey, we mapped the customer experience from planning to post-return.

By layering user thoughts, emotions, and actions along key service touchpoints, our Customer Journey Map reveals when and where confidence breaks down, expectations are unmet, and users are left unsupported.


To better understand how these shared frustrations unfold throughout the rental journey, we mapped the customer experience from planning to post-return.

By layering user thoughts, emotions, and actions along key service touchpoints, our Customer Journey Map reveals when and where confidence breaks down, expectations are unmet, and users are left unsupported.

To better understand how these shared frustrations unfold throughout the rental journey, we mapped the customer experience from planning to post-return.

By layering user thoughts, emotions, and actions along key service touchpoints, our Customer Journey Map reveals when and where confidence breaks down, expectations are unmet, and users are left unsupported.

Click below to see how the pain points unfold throughout the journey.

Through research, we uncovered a consistent gap between first-time renters’ expectations and the level of support currently provided by U-Haul.

Despite being a dominant player in the rental truck industry, U-Haul’s service for first-time users shows clear opportunities for improvement, particularly in confidence-building and the overall ease of driving and renting.

So how might we minimize the barriers for first-time renters to maximize efficiency and deliver a seamless experience throughout the journey?

Ideate & Prototype

Desirability Testing - Conversational Prototype

To quickly evaluate potential service flows and validate their desirability with first-time renters, we adopted a conversational prototype approach.

Through simulated dialogues and scenario-based interviews, we tested early-stage user flows and interactions—capturing immediate user reactions, clarifying misunderstandings, and uncovering preferences in real-time conversations.

Ocerall Service Flow 1.0

Refined Service Flow

Refined Service Flow

Refined Service Flow

Building on this validated flow, we moved forward to develop a more tangible prototype, bringing the experience to life through screens, interactions, and service touchpoints that users could directly engage with.

Prototyping Question

What features from the app prototype you find helpful and intuitive?

Conversational Prototype

Digital Prototyping

Are the new renting recommendation options appealing?

Digital Prototyping

The Wizard of Oz

Were there any step of the process that you found unclear or challenging?

Digital Prototyping

The Wizard of Oz

Are the online + physical instructions enough to give you the confidence before driving?

Desktop Walkthrough

Cardboard Prototyping + Card Sorting

Digital Prototype

Physical Space Prototype

Machine Learning System

For the recommendation system, Orange 3 was used to validated the prediction, based on information previously collected during the truck booking in the app and stores.

Test

How we evaluate the success?

User Feedback

Online Service Feedback

For Online Service

For Online Service

  • Users strongly suggested avoiding repetitive manual entry of personal details at different points during the booking process.

  • Users requested explicit, easy-to-understand explanations for why personal information is needed, emphasizing transparency and trust-building.

  • Users recommended providing access to driving tutorials directly from the moment they place their order, continuing through to the key pick-up stage.

In-store Feedback

For In-store Experience

For In-store Experience

  • Users felt frustrated when redirected multiple times between employees or resources, preferring clear, concise assistance in one interaction.

  • Users requested clearer visual guidance in-store, such as graphics or displays, to help them select appropriate moving boxes based on their specific needs.

These feedback weren’t just support functional improvements, they directly help us figure out users’ emotional needs for clarity and control.

"Honestly, I didn’t think I could do it by myself, but now I feel ready."

— A First-time U-Haul renter, post-prototype test

The Comeback

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