Case study / 01

See what your
friends are craving.

Munch is a food delivery app concept built around one idea: ordering is more fun with friends. Designed for Gen Z and millennial users who get bored eating the same thing on repeat.

Outcome
100% task success in usability testing
Role
UX/UI Designer
Timeline
Bootcamp project
Tools
Figma, Google Surveys

Friend activity: live preview

4.5 James James's PF Chang's order
James ordered
PF Chang's
4.2 Hannah Hannah's Addis Vegan Kitchen order
Hannah ordered
Addis Vegan Kitchen
4.2 Miguel Miguel's Meaty Buns order
Miguel ordered
Meaty Buns
4.7 Fred Fred's Dishoom order
Fred ordered
Dishoom

Problem statement

Users kept ordering the same three things — and knew it.

"I tend to get bored of eating the same food. It'd be great if I could see what my friends order instead."

That single line from an early interview became the north star for the whole project: build discovery around trusted recommendations from people you know, not just star ratings from strangers.

Process framework: Double Diamond

I structured the project around the Design Council's Double Diamond, alternating between opening up (diverging) and narrowing down (converging) twice, so every design decision below traces back to a research finding rather than personal taste.

Discover

Diverge
Competitor analysis, surveys, interviews

Define

Converge
Red route analysis, personas, problem statement

Develop

Diverge
Crazy 8's, low → mid → high fidelity wireframes

Deliver

Converge
Usability testing, style guide, final UI

Business research

Competitor analysis: UberEats, Deliveroo & JustEat

Before designing anything, I mapped the features already considered table stakes, so Munch could meet expectations while still standing apart on the social layer.

FeatureUberEatsDeliverooJustEat
Navigation styleBottom barDropdown menuBottom bar
Send a gift to a friendYesNoNo
In-app table bookingNoYesNo
Collection optionNoNoYes — highest rated
Visible offers & promosYesYesYes

Finding

All three apps share the majority of their core features — a clear case of Jakob's Law: users expect your app to work like the apps they already know.

Finding

JustEat's higher store rating traced back almost entirely to one feature — collection — proving small conveniences can outweigh a bigger feature set.

Finding

None of the three surface a friend's order history. That gap became the opening for Munch's core differentiator.

Why competitor analysis first

Starting here, before talking to a single user, meant I could separate "expected" features (nav bar, offers, reordering) from genuinely open territory. Jakob's Law states that users spend most of their time on other products, so they prefer yours to work the same way. That let me spend design effort on the social gap rather than reinventing checkout or search.

User research

Surveys, interviews & a red route analysis

A team brainstorm produced a long list of candidate features. Surveys and interviews with regular fast-food-app users told me which of those actually mattered.

62%
survey response rate across the target user group
90%
of spend goes on food, more than any other category
75%
use a delivery app at least weekly
50%
wanted a way to split a group order automatically
#1
UberEats was the most-cited favourite app

Red route priority: what users rated as essential

Order again
92%
Account details
88%
Favourites list
74%
Split the bill
50%

Why a red route analysis

A red route maps the highest-frequency, highest-value tasks in a product: the paths users take most often to get real value, borrowed from Transport for London's "red routes" that must never be blocked. Ranking features this way stopped the brainstorm's full wishlist from diluting design effort, and confirmed the brainstorm's instincts with actual user data rather than assumption.

Personas

Designing for three different appetites

Rather than invent archetypes, I clustered the interview transcripts by motivation for ordering: impulse and occasion, time pressure, and content for others — and built one persona per cluster so every design decision downstream could be checked against a real behaviour pattern, not a guess.

EE

The Eating-Out Enthusiast

Always on the move

Orders on impulse between plans with friends. Wants inspiration, not just a search bar.

Discovery-ledSocial proof
YP

The Young Professional

Working late, ordering fast

No time to cook most weeknights. Values speed, saved favourites and a frictionless reorder.

EfficiencyRepeat orders
CC

The Content Creator

Chasing the next food trend

Documents every meal. Wants a platform that showcases where they ate, not just what they paid.

SharingTrend-driven

Ideation

Crazy 8's, then three fidelity passes

Eight sketches in eight minutes forced quantity over perfection early on. From there, the same three screens (Home, Friends activity and Split bill) were wireframed in greyscale at the final layout and size before colour and photography went in.

Why Crazy 8's

The eight-minute constraint is deliberate: it's too short to get precious about any one idea, so it breaks fixation on the first solution and forces genuinely different layouts onto the page. I then took the strongest elements from different sketches rather than picking one sketch outright.

Why three fidelity stages, not one

Wireframing at the final layout and size kept feedback focused on content and flow, not colour or brand. Participants weren't distracted into commenting on visual polish before the structure was right. Visual and brand decisions were locked in last, once the underlying structure was already validated.

Wireframes: same layout and size as the final build, no colour yet

Home

Munch!
Explore your friends' favourite cuisines
Order Now →
Your favourites
Banana Tree
4.5 · 20-25 min
Tayyabs
4.2 · 15-20 min
Friends recommendations
Tinseltown
PF Chang's

Search sits in the bottom nav, matching the pattern UberEats and Deliveroo already trained users on (Jakob's Law).

Friends activity

Friends activity
Stories
Russ
Jess
Jay
James2 h
Ordered PF Chang's · 4.5
"Lovely food and a great price"
Hannah5 h
Ordered Addis Vegan · 4.2
"Enjoyable food, highly recommend!"

Real names replace anonymous rows. Testing moved from "is this readable" to "would I trust this friend's pick".

Split bill

Split Bill
Banana TreeTotal: £85.50
FrequentSee all
Hannah
Fred
Split Bill
You
+
Amount
−
Fred
+
Amount
−
Confirm & Split

The +/− stepper appears here: exactly what 50% of survey respondents asked for.

→

Brand colour and real photography come next. See the full-colour high-fidelity builds below.

Final UI

Four screens, one social loop

Home surfaces friends' favourites first, the activity feed makes their recent orders scannable at a glance, and split bill turns a group order into a one-tap settlement — closed by a push notification that lands on a friend's phone the moment they're asked to pay.

Home

Munch!
Y
Food photo on the Munch home screen
Explore your friends' favourite cuisines
Order Now →
Your favourites
Banana Tree dish photo
Banana Tree
★ 4.5 · 20-25 min · £2.50
Tayyabs dish photo
Tayyabs
★ 4.2 · 15-20 min
Friends recommendations
Tinseltown
Tinseltown
★ 4.5
PF Chang's
PF Chang's
★ 4.5
Patty & Bun
Patty & Bun
★ 4.5
Honest Burgers
Honest Burgers
★ 4.5

Friends activity

Friends activity
Y
Stories
Russ
Russ
Jess
Jess
Jay
Jay
Moe
Moe
James
James2 h
Ordered PF Chang's · ★ 4.5
Lovely food and a great price
Hannah
Hannah5 h
Ordered Addis Vegan Kitchen · ★ 4.2
Enjoyable food, highly recommend!
Miguel
Miguel8 h
Ordered Meaty Buns · ★ 4.2
Nice food but small portion
Carl
Carl2 d
Ordered Wagamama · ★ 4.2
Can't go wrong with Wagamama
Fred
Fred3 d
Ordered Dishoom · ★ 4.7
Best butter chicken I've had in ages
You're all caught up

Split bill

Split Bill
Y
BananaTree
Total: £85.50
Subtotal£72.00
Delivery£4.50
Service fee£9.00
Total£85.50
FrequentSee all
Hannah
Hannah
Miguel
Miguel
Carl
Carl
Fred
Fred
Invite a friend to join Munch!
›
Split Bill
Y
You
+
Amount
−
Fred
Fred
+
Amount
−
Miguel
Miguel
+
Amount
−
Confirm & Split

Notification

9:41
Monday, 27 July
M
Munchnow
Fred requests £28.50
Your share of the Banana Tree split, tap to pay
Replay

Hit Confirm & Split on the split bill screen. Fred's phone picks up a push notification for his share, closing the loop on the group-order flow.

Validation

Testing the high-fidelity prototype

Four task-based scenarios run through Figma Mirror with participants unfamiliar with the design.

5
participants, moderated remotely one at a time
4
core tasks, each timed and observed without prompting
0
prior exposure to the designs — first-click testing

Method

Each session was think-aloud and moderated: participants narrated their reasoning as they navigated, which surfaced why a screen worked rather than just whether the task was completed. Sessions were run one-to-one to avoid groupthink skewing the results.

View favourite restaurants

Completed quickly by every participant, with positive reactions to the carousel format.

Share what you're ordering

All participants found their way to the friend-activity feed without prompting.

Manage personal details

Successfully completed by every participant with no hesitation.

Overall impression

Feedback was consistently positive — participants described the app as easy to pick up.

UI phase

A style guide built for one hand and low light

Munch's in-app typeface is Lato, chosen for its comfortable reading weight at small sizes and its familiarity across similar apps. Below is the palette and core components that came out of the high-fidelity pass.

Coral / CTA

Teal / Social

Gold / Ratings

Surface

Base

Lato: Headline, semibold

Order more of what your friends love.

Lato: Body, regular

Set at 16px with generous line height so restaurant descriptions stay legible one-handed, on the move, in low light.

Accessibility & heuristics

Checked against Nielsen's heuristics, not just visual taste

Visibility of system status

Order state (placed, preparing, on the way) is always visible on screen rather than buried in a notification, so users never have to guess where their order stands.

Recognition over recall

Favourites and recent orders surface on the home screen rather than requiring users to remember and re-search for a restaurant name.

Error prevention

The split-bill screen shows the recalculated total live as amounts are adjusted, so a mistake is visible before it's confirmed, not after.

Colour contrast

Body text on the dark surface sits at a 13:1 contrast ratio and the coral CTA at 4.6:1 against its background. Both pass WCAG 2.1 AA for their respective text sizes.

13:1 · AAA
4.6:1 · AA

Conclusion

Did it solve the brief?

  • A friend-activity feed lets users find their next order through people they trust, not anonymous ratings.
  • An invite-a-friend reward turns referrals into free credit, encouraging organic growth.
  • Every flow was tested against real users and refined against their feedback, not just internal opinion.

Self-assessment

What I'd carry forward

Strongest muscle: turning a scattered brainstorm into a ranked, evidence-backed feature list. Next time: sharper usability testing that captures friction in the moment, not just end-of-session sentiment — and, with more time, a live A/B test on the friend-activity feed's actual impact on reorder rate.