{ CASE STUDY DETAILS }
The problem, the decisions we made, and what actually changed for the client after launch
PROJECT NAME:
QuickBite — Food Delivery App
INDUSTRY:
Food & Delivery
ENGAGEMENT:
Customer app build + launch
DESIGN:
Sabariya Muzumder
TOOLS USED:
React Native, Node.js, PostgreSQL, Socket.IO, Stripe
LOCATION:
Dhaka, Bangladesh
Ordering food on a phone is a sequence of small decisions — where to deliver, what to eat, from whom, how to pay — and a customer can abandon the order at any one of them. We built QuickBite as a single uninterrupted path through those decisions: ten screens where each one resolves its question and hands over the next, from the address at the top of the home screen to the courier’s name on the tracking map.
Food Apps Lose People Between The Screens, Not On Them
A delivery app is judged on how little thought it takes to get from opening it to eating. The individual screens are rarely where that goes wrong — a menu is a menu. It goes wrong in the joins: an address asked for twice, a cart that forgets why an item was added, a payment step that leaves the app, an order that disappears the moment it is placed. We had to treat the whole sequence as the product, on a phone, in a category where every competitor is one tap away.
Key issues identified:
One Path, Carried By The Same Three Elements
Discovery opens on the delivery address rather than a logo, because it is the one fact every price and delivery time below it depends on — change it and the whole screen requeries. Search sits under it for people who already know what they want, and a promotion rail, a category row and a featured list sit under that for people who do not. The restaurant screen keeps the same shape as the home screen — photograph, rating and delivery time, then items — so moving between restaurants never means relearning a layout.
From the cart onward the app stops selling and starts confirming. Quantity steppers stay on every line to the last screen, the delivery address and estimate repeat at checkout rather than being taken on trust, and three payment routes — saved card, Apple Pay and cash on delivery — resolve in place through Stripe without the customer ever leaving the app. Placing the order drops straight onto a live map: courier positions arrive over a socket, the four-state timeline advances off those same events rather than off a poll, and the courier’s name, rating and vehicle are on screen from the moment the restaurant accepts.
Repetition Is What Makes A Flow Feel Short
The screens that work hardest in this build are the ones that repeat something the customer has already seen. The address appears on the home screen, again in the cart, again at checkout; the order total appears beside the checkout button and again in the summary; the delivery estimate appears on the restaurant card, the cart and the tracking map. None of it is new information, and that is the point — each repetition removes a reason to scroll back and check, which is the most common way a food order stalls.
What this project reinforced:
Checkout Completion
+34%
Keeping the quantity controls and the delivery estimate on the checkout screen cut the carts abandoned at the total.
Repeat Orders
62%
Of first-time customers ordered again within a month, with the saved address and payment method already in place.
Time To Order
90s
Median time from opening the app to a placed order, measured across the three busiest restaurant categories.
Support Contacts
-41%
The live map and its four-state timeline removed most of the messages that used to follow a confirmed order.
We do not just finish projects — we stay on after launch. Here is what the teams we shipped for have to say.
We were selling groceries, pharmacy items and household goods out of systems that did not talk to each other. They built one basket over the lot of it and gave operations a live view of orders, riders and stock across all four locations.
Boshir Ahmed
Signature Bangla
They scoped it honestly, told us which features were not worth paying for yet, and shipped on the dates they gave us. The questions they asked before writing anything were the useful part.
Shafin Ahmed
Textalyz AI
Every update arrived when they said it would, and we could open the thing they had built at the end of each one. After launch they stayed on it rather than sending a handover email and disappearing.
Redwan
Rongobuy
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// A focused MVP usually ships in 8–12 weeks. Larger SaaS platforms and multi-tenant systems run 4–6 months, delivered in two-week increments so you see working software throughout rather than at the end.
