E-commerce · Fashion · Mobile + Web

Aanchal — ethnic wear, sized to you

A premium ethnic wear shopping app that celebrates tradition with modern convenience. This case study walks the full design process in ten stages, from the problem statement to a clickable prototype, a usability test kit and an iteration from v1 to v2.

Role: UX researcher & UI designerPlatform: mobile app + web Type: self-directed conceptTools: Figma

Open the clickable prototype Download Figma plugin (builds the native file)

01 Problem 02 Users 03 IA 04 Flows 05 Wireframes 06 High-fidelity 07 Prototype 08 Testing 09 Iteration 10 Outcome

About this case study

Aanchal is a concept project. Personas and the empathy map are research-based hypotheses, not interview data. The heuristic evaluation is an expert review, not user data. The usability test is planned, not yet run, so no test results or outcome metrics are claimed. Market figures come from published reports cited in the project research and are labelled as estimates or projections. Illustrations are original drawings; sample prices and dates are illustrative.

01 — Problem statement

Shoppers cannot tell how ethnic wear will fit before they pay

Ethnic wear is bought for weddings, festivals and daily use, in India and across the diaspora. Online, shoppers guess a size from inconsistent charts, return orders and sometimes miss the event they bought for.

Obstacles to buying online

No personalisation

Clothes do not fit

Sizes do not match across brands

For shoppers

Fit problems lead to returns

Cannot inspect the garment

NRI buyers struggle most with sizing

For brands

High return rates add cost

Low loyalty after a bad fit

Limited adoption of AR and 3D

Problem statement with how-might-we questions, goals and constraints

02 — Understanding the user

Research, audience, personas and the insights that drive the design

Market and competitors

India and global ethnic wear market size, 2023, 2024 and projected 2030

Verification notes Review

The stated growth rates match the endpoints and the India and global figures sum to the stated totals. The figures themselves could not be checked against the publisher from this environment, so confirm them in the original report before publishing. A claim in the source deck that India is 50–75% of the global market contradicts its own numbers (about 17% of the combined 2023 total), so it is left out.

Urban Indians, 30–60

Professionals and business owners buying for weddings and festivals; value convenience and accurate fit.

Millennials and Gen Z, 18–30

Mobile-first shoppers who want trendy and fusion looks, with personalisation.

NRI community

High demand for weddings and festivals; fit is hardest when ordering from abroad; willing to pay for custom fit.

Positioning map of competitors by fit personalisation and ethnic specialism

Illustrative, based on the feature benchmarking table: ethnic specialists have range but standard sizing; fit-tech providers personalise but do not sell ethnic wear. The top-right is open.

Personas, empathy map and insights

Four key insights with design implications

03 — Information architecture

Five areas, with fit, delivery dates and privacy added

The original structure covered home, categories, product and account. Dashed items were added to support the insights: a fit recommendation on the product, a fit-profile area in the account, a delivery date at checkout and order tracking.

04 — User flow

Sign in late, and never dead-end the fit profile

Browse, sign in and buy

Shoppers browse, add to bag and press Buy now before they are asked to sign in. OTP verification handles both new and returning users, and the flow returns them to checkout.

Fit profile

Consent first, then video or manual entry. If capture fails twice it falls back to manual measurements. Low confidence offers two sizes or made-to-measure.

User flow for browsing, signing in and buying

05 — Wireframes

Structure first: where fit confidence and dates live

Grayscale wireframes settle hierarchy before colour. Two decisions were made here: a “Find your fit” entry on Home and a fit-help block on the product page, and an arrival date next to the price.

Home · Listing · Product detail · Fit consent · Checkout · Order tracking

06 — High-fidelity design

Version 2: maroon, clear prices, and fit built into the product page

These are the v2 screens, designed after an expert review of v1 (see stages 08 and 09). They use original illustrations and sample data.

Entry

Browse and choose

Fit profile and size recommendation Concept

Buy and track Concept

Design system

07 — Prototype

Click through the whole flow

08 — Usability testing

An expert review now, and a test ready to run

Real user sessions have not been held yet, so no user results are reported. What exists: an expert review of the v1 screens against Nielsen's ten usability heuristics, and a complete test kit.

Heuristic evaluation of v1 Expert review

#	Finding	Screen	Heuristic	Sev	Change in v2
1	Stock third-party logo on login and sign-up instead of the brand	Login, Sign up	H4 Consistency and standards	3	New Aanchal wordmark and rosette mark
2	OTP boxes appear before an OTP is requested; no “Send OTP” action	Login	H1 Visibility of system status	3	Send OTP, then a verify screen with a resend timer
3	Social sign-in is plain text, not tappable buttons	Login	H6 Recognition rather than recall	2	Tappable Google, Facebook and Apple buttons
4	Sign-up asks name, email, mobile and OTP on one screen	Sign up	H8 Minimalist design	2	Sign-up reuses the OTP screens; name and mobile only, email optional
5	Category labels misspelled	Listing	H4 Consistency and standards	2	Labels corrected; occasion chips replace category thumbnails
6	Trending cards show no price or rating	Listing	H6 Recognition rather than recall	3	Price, original price, discount and rating on every card
7	Title is a seller name; price has no original price shown	Product detail	H2 Match with the real world	3	Product name as title, seller secondary, ₹ price with original struck through
8	All colour swatches use the same photo and do not match the colour names	Product detail	H2 Match with the real world	3	Colour dots with names that match the image
9	Size is pre-selected, no selector, no fit guidance	Product detail	H5 Error prevention	4	No default size; “Select size” prompt and a Find my size banner
10	“Add to Bag” is grey and looks disabled	Product detail	H1 Visibility of system status	2	Add to Bag outlined, Buy Now primary
11	Magenta accents instead of the documented maroon	All	H4 Consistency and standards	2	Maroon scale used throughout
12	Light-grey text on pale backgrounds looks low in contrast (ratio to be measured)	Home, Listing	Accessibility (WCAG 1.4.3)	3	Darker text, 12px minimum; measure every ratio in Figma
13	No delivery date or pincode check near the buy buttons	Product detail	H1 Visibility of system status	2	Delivery line with an arrival date above the buttons

Severity 0–4 (4 = usability catastrophe). Findings cover the original v1 login, listing and product screens.

Usability test kit

Usability test plan with tasks and measures

Test results sheet to complete after the sessions

09 — Iteration

From v1 to v2: every change answers a finding

Trust and brand

Replaced the stock logo with the Aanchal mark; moved every accent to the maroon scale.

Clarity at decision time

Price, original price, discount and rating on every card; real colour options; a delivery date next to the buy buttons.

The core problem

Removed the default size and added Find my size, which leads into the fit profile and a recommendation with a reason.

The next iteration comes from the usability sessions: record each observed problem, the change and the screens it touches.

10 — Final outcome

What was delivered, and what to measure next

Delivered

Research, personas, IA and flows

Six wireframes and eleven v2 screens

Design system and clickable prototype

Heuristic review, test kit, iteration log

Key decisions

Fit confidence at the point of purchase

Occasion-first browsing with arrival dates

Late sign-in, optional and deletable fit data

Two-size or made-to-measure fallback

Measure next

Size-related return rate

Fit-profile completion

Try-on to add-to-bag conversion

Task success and SUS from the usability test

Open items Next steps

Run the usability sessions and record real results; measure colour contrast on every screen; confirm with engineering that body measurements can be estimated reliably from video; check privacy obligations for body data with legal counsel; clear the brand name (trademark and domain); verify the market figures against the original reports.

References

Sources

Grand View Research — ethnic wear market reports for India and global (market size, 2030 projections, CAGR), as cited in the project research file. Confirm report titles and years before publishing.
Competitor and technology-partner information (FabIndia, BIBA, Soch, Global Desi, W for Woman, Myntra, Ajio, Manyavar, Amazon, Flipkart, 3DLOOK, VTO 3D, Mirrorsize) — desk research from the same file.
Personas and empathy map — research-based hypotheses authored for this project; not interview data.
Nielsen, J. — “10 Usability Heuristics for User Interface Design”, Nielsen Norman Group.
Nielsen Norman Group — “Why You Only Need to Test with 5 Users” (rationale for small qualitative rounds).
W3C — Web Content Accessibility Guidelines 2.1, success criterion 1.4.3 Contrast (Minimum).
Sauro, J. and Lewis, J. — Quantifying the User Experience (System Usability Scale).
Government of India — Digital Personal Data Protection Act, 2023.
Items 4–8 were cited from memory and could not be checked online from this environment; confirm titles and wording before publishing.