PerfectFit
THE PROBLEM
THE SOLUTION
USER INSIGHT STATEMENT & PROBLEM STATEMENT
USER INSIGHT : Tiffany is a middle age, social, working professional who needs help to find clothes that suit her body and meet her fashion requirements. As a busy person, she does not have time to return ill fitting clothes all the time, and would benefit from more accurate way to choose here size.
PROBLEM STATEMENT : PerfectFit is an app for helping online shoppers find the right clothes that fit them perfectly without having to physically try them on. The app features a measurement system that gets your key body details which are then used to match your figure to the right outfit for you!
People frequently struggle to find their correct size when shopping online, leading to frustration and a higher likelihood of returns due to inaccurate sizing.
The PerfectFit app offers a comprehensive solution by allowing users to input their body measurements and receive accurate size recommendations. This reduces returns and enhances the shopping experience, ensuring that users receive products that fit perfectly every time.
"The PerfectFit project with the digital agency Great & Small provided me with the opportunity to work with cutting-edge technology and some of the most creative tech and marketing minds in the industry. Our most recent endeavor was the successful product launch of the JoBo app, a revolutionary tool that leverages advanced design and user-centric principles to deliver a seamless experience for its users."
This slide shows the process behind the PerfectFit app concept. It started with a brainstorming session where the team explored ideas like gym locators, gardening designs, and clothing fitting. The "Clothes fitting" concept stood out as a promising direction. In the low-fidelity wireframe phase, initial user feedback indicated that the card sizes were too large, there were too many buttons, and the overall flow could be simplified. This early insight guided the iterative improvements that followed.
This slide introduces our proto-persona, Tiffany Spears, created to represent the target users for the PerfectFit project. Her known habits include enjoying events outside of work, socialising, and sharing content on Instagram. However, she finds online shopping frustrating due to difficulties in finding clothes that fit correctly and the hassle of returning items. Tiffany seeks a better variety of well-fitting clothes that match her style, offering good value for money. This persona guided the development of PerfectFit to meet these specific goals.s early insight guided the iterative improvements that followed.
This slide outlines the research and interview plan for the PerfectFit project. The goal is to understand how users approach picking their size and their challenges with finding the right fit. Key research questions aim to uncover how often users feel disappointed with sizing choices and the pain points they experience. The draft research plan details objectives, assumptions, and data analysis methods, intending to explore existing apps, identify user frustrations, and gather insights for improving the sizing experience.
Our online shopping survey, with 17 responses, revealed that over half of participants sometimes struggled with receiving the right size, and nearly a quarter were often disappointed. Around 58.8% of respondents indicated interest in using an app that would let them virtually try on clothes after entering their measurements. This demonstrates the need for a solution like PerfectFit.
To synthesise the data collected from surveys and interviews, we created an affinity diagram and an empathy map. The affinity diagram groups common pain points, user behaviors, and desirable features, like difficulties finding fitting clothes online and navigating inconsistent sizing charts. The empathy map provides a deeper understanding of user motivations and challenges, highlighting insights such as the need for accurate size measurements and the frustration with returning ill-fitting clothes. Together, these tools inform the PerfectFit design strategy.
This presents the persona for Tiffany Spears, a 31-year-old architect based in Sandringham, Melbourne. Tiffany is passionate about her work and enjoys being creative, but she finds online shopping challenging. Her frustrations include inconsistent sizing across brands and difficulty finding clothes that fit well. She desires an app that offers accurate sizing recommendations and confidence in online shopping. Tiffany’s preferred brands include Kookai, Marimekko, Céline, and Zara, highlighting her need for a reliable sizing solution like PerfectFit.
The feature prioritisation matrix simplifies the process of deciding which features to focus on for PerfectFit. Immediate, easy-to-implement ideas (NOW) involve letting users input their measurements to find the best-fitting clothes. Unique and impactful features (WOW) include obtaining measurements via a picture and using filters to refine search results. The value proposition, "The right size, every time," captures the project's goal: ensuring users can find accurately fitting clothing quickly and easily.
This competitor analysis summarises the features, strengths, and areas of improvement of three services:
SizeCharter: Strengths include measurement instructions, while areas of improvement include an outdated interface and measurement accuracy.
MySizeID: Offers seamless integration with Shopify and Lightspeed, but has limitations like high cost and compatibility only with certain stores.
Size Me Up: Provides geo-targeted sizing and easy two-photo measurements, but is expensive and requires integration.
This analysis highlights potential gaps for PerfectFit to fill.
The user flow iterations for the PerfectFit app show a progression from sketching initial ideas to refining the flow in a structured diagram.
Sketch Phase: Highlights the initial concept with rough navigation paths, including signing in, creating a profile, and measuring fit preferences.
Refined Diagram: Defines a streamlined process with clear steps for inputting measurements, updating the profile, browsing preferred brands, comparing sizes, and making a purchase decision.
A user browses for clothes online but isn't sure about her size. She discovers a "Measuring App" that recommends the right fit based on her measurements. With her ideal size determined, she confidently returns to the store's website to purchase the dress, which ultimately fits her perfectly and makes her happy with her choice.
This structured flow allows the user to navigate seamlessly from onboarding to checkout.
These sketches visually represent various stages of the user journey for the PerfectFit app.
How to Measure Page: Users input measurements for accurate sizing.
Splash, Sign In & Sign Up: A welcoming splash page, followed by forms to sign in or create an account.
Measurement Edit: A dedicated section where users can edit their measurements.
Onboarding: Introduces users to the app's features and how to use them.
Landing & Profile: Displays profile information and personalised suggestions.
Search/Landing: Enables searching for clothing brands and products.
This slide provides a summary of user testing tasks conducted on a low-fidelity prototype. Six users were tested on the following:
Sign-Up Process: Users successfully registered by inputting their details.
Adding Measurements: Users efficiently added personal measurements to their profile.
Brand Sizing Search: Users searched for brand-specific sizes to find the best fit.
The success criteria included ensuring tasks were quick and straightforward, enhancing the user experience.
The initial low-fidelity prototype was tested on six users. Key insights included:
Positives: Users found sign-up straightforward and user-friendly.
Navigation Issues: The navigation bar was unclear, and the search bar was confusing and too low.
Visual Issues: Users suggested improving the app's aesthetics and adding clearer information on measurements.
Trust: Users expressed the need for trusting the app's recommendations more fully.
The updated iOS prototype included the following changes:
Search Bar: It was moved up for better visibility and given clearer instructions.
Functionality: The "X" button was fixed to ensure it worked properly, addressing previous issues.
Instructions: Additional guidance was added to help users understand how to navigate the search feature more effectively.
These adjustments resulted from user feedback to make the app more user-friendly.
The final PerfectFit prototype guides users through taking accurate measurements and provides tailored size recommendations for favorite brands. It's intuitive, streamlined design includes an onboarding process, a measurement guide, and easy navigation to user profiles and settings, ensuring a personalised shopping experience.