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VERIFYT ECOMMERCE PLUG-IN: Shoe Recommendation Display

My Role
User Research:
Qualitative & Quantitative

Company
 

Team
1 researcher (me)
2 UX/UI designers
App + web developers

Date
May 2022 - July 2022

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Client + Product Summary
NetVirta is a B2B2C SaaS company who has created several smartphone-based, 3D body scanning technologies that serve an array of industries. Examples include CurveCapture®, a mobile 3D scanning app used to scan patients heads, aiding in the creation of custom cranial orthotics, and Verifyt®, a full-body and foot scanning app used to suggest best fittings shoes and apparel. These scanning apps are complimented with: (1) an end-consumer facing eCommerce plug-in that connects with the scanning app to suggest best sizes and styles directly on a partnering brands' eCommerce site, and (2) a business-facing customer intelligence portal used as a 3D model database and analytical tool.

Project Goals + Research Questions

The goal of this project was to iterate upon the shoe fit-recommendation display of the Verifyt® plug-in found on brands' eCommerce websites. To do so, we set out to answer the following research questions:

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  • After having scanned their feet, what information do users expect to see and find most helpful when deciding which size shoe to purchase?

  • Do users need to see how the shoe fits at different points of the foot?

  • Do users need the ability to see how all sizes fit on their foot or just the recommended size/s?

  • Does the user benefit from seeing their foot measurements?

  • Does the colored scale help the user in understanding the foot graphic?

  • Is just the recommended size enough information?

  • How many sizes plus the recommended size are sufficient for this visual?

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Verifyt eCommerce Plug-In

Verifyt App (Post Scan)

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Tools Used

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Userinterviews.com
Participant recruitment

Microsoft Teams
Conduct and record virtual interviews

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Microsoft Excel
Create notes sheet, compile notes from all user interviews

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Mural.com
Note themes, analyze data, present findings

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Microsoft Powerpoint
Present my findings

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Discovery Phase

1. Identified Design Problems
Discussed as a team to identify current design issues and established objectives and goals of the study, based on our assumptions

2. Competitive Analysis
Conducted an analysis of similar solutions

3. Participant Criteria
Established the criteria participants must meet to take part in our study

4. Data Collection Methods
Decided which data collection methods to use based on the problem we are trying to solve and the questions we are trying to answer

The Process

1

Recruitment
Used a screening survey to:

  1. capture demographics of users

  2. identify participants who own an iPhone and are okay with using a 3D body scanning app


Chose 12 participants of ranging ages, genders, races/ethnicity, and household incomes

2

Scheduling + Introduction
Sent an introductory email, including:

  1. a calendar invite for date and time of interview

  2. a request for the signature and return of the attached non-disclosure agreement

  3. instructions to bring a fully charged iPhone and piece of US Letter paper to interview

Comparative Usability Testing
Conducted virtual interviews with all participants using the following layout:

3

Part 1: Introduction

 

  1. Welcomed participant

  2. Gained consent to record the interview + set up recording

  3. Introduced session details

Part 2: Pre-Test Questions

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  1. Identified participants shoe shopping habits

  2. Identified participants shoe-fit tendencies

Part 3: Tasks

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  1. Had users conduct a foot scan using the Verifyt app

  2. Identified participants' expectations for post-scan results (what information they would expect to see after scanning)

  3. Show post-scan results of Verifyt solution and gain feedback

  4. Show post-scan results of competitor's solution and gain feedback

Part 4: Post-Test Questions

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  1. Asked participants to compare the two solutions

  2. Concluded the study + distributed incentive

Findings Summary

Positive Findings

  • The information showed was as expected

  • All participants said there was enough information to trust the size being recommended and would help them make a purchase

  • 11/12 participants were able to identify their recommended size, mainly due to the explicit callout, “Your recommended fit”

  • On a scale of 1 (easiest) – 5 (most difficult), the average of how easy/difficult it was to find their recommended size was a 1.42

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Opportunities For Improvement
Add

  • Participants want to see how multiple sizes would fit on their foot

  • Suggest styles specific for that user’s foot

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Change

  • Should have all information in one spot, either on the app, on the web plug-in, or same information mirrored on both

  • Should still allow user to see the shoe they are shopping for in the background

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Takeaway

  • Don’t need to name areas of the feet: self-explanatory

  • Fit scale does not help users – if anything, it confuses them

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Detailed Findings

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Mural Board Link

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Mock-up for Design Team

The Final Product

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Future Features

  • Suggest styles specific for that user’s foot

  • All information to be in one spot, either on the app, on the web plug-in, or same information mirrored on both

  • eCommerce plug-in to pop-up from the side instead of center of the screen, allowing user to see the shoe they are shopping for in the background

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© 2023 by CHELSEA MORGAN.

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