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Mobile Applications
Beauty & Grooming

Walk-In Check-In and Wait-Time App for a 60-Shop Barbershop Franchise


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Overview

What we built

A 60-shop barbershop franchise ran entirely on walk-ins and paper sign-in sheets, with queues stretching past 40 minutes at peak hours. We built the app that let customers check in before they arrived.

In plain terms: every one of the franchise's 60 shops operated on walk-ins only, with a paper sheet at the door as the entire queue management system. A customer had no way to check how long the wait would be before showing up, so peak-hour queues routinely stretched past 40 minutes, and plenty of people simply walked out once they saw the line, a loss the franchise had no way to even count, let alone recover.

We built native iOS and Android apps with remote check-in that holds a customer's place in the queue before they arrive, live wait-time estimates per shop, barber preference selection, and push alerts as their turn approaches, backed by an in-shop tablet queue board and a franchise-wide staffing analytics dashboard. Peak-hour walk-outs dropped from 14% to 6% within 3 months, remote check-ins reached 57% of all visits within 6 months, and average waiting time fell by 11 minutes.

The Problem

Blind walk-ins, long queues

Running 60 shops entirely on walk-ins and paper sign-in sheets meant every queue started from zero information. A customer arriving at any shop had no way to know whether the wait would be five minutes or fifty, so the only way to find out was to show up and look, and by peak hours the answer was often a queue stretching past 40 minutes.

Walk-outs were the predictable result, and the invisible cost. Customers who saw a long line and left were never recorded anywhere, so the franchise had no count of how much business it was losing to wait time alone, let alone any way to win those customers back once they had gone elsewhere for a haircut.

Staffing decisions suffered from the same blind spot. With no demand data beyond a franchisee's own memory of busy days, barber schedules across the week were built on instinct rather than evidence, leaving some shifts overstaffed and others unable to keep up with the queue at the door.

Paper-only queue management

All 60 shops ran on paper sign-in sheets, giving customers no way to check a wait time and staff no digital record of who was waiting.

Queues past 40 minutes

Peak-hour queues stretched past 40 minutes with no visibility for customers deciding whether to wait or walk away.

Uncounted walk-outs

Customers who left rather than wait were never recorded, so the franchise had no measure of how much business the queue itself was costing.

Staffing built on guesswork

Franchisees had no demand data to plan barber staffing across the week, relying on memory of busy days rather than evidence.

What it was costing them

Every uncounted walk-out across the 60 shops was a haircut the franchise lost without ever knowing it happened, and every 40-minute peak-hour queue was a customer deciding whether to stay or try somewhere else. Without demand data, staffing decisions could not respond to the pattern behind those queues, so the same peak-hour crunch and the same walk-outs kept repeating week after week.

The Solution

Check in before you arrive

We built native iOS and Android apps centred on remote check-in, letting a customer hold their place in the queue before they even leave home. Live wait-time estimates per shop, modelled from historical service times, replaced the show-up-and-see approach with an actual number a customer could plan around.

Barber preference selection let customers request the person they usually saw, and push alerts as their turn approaches meant nobody needed to sit in the shop watching the door to avoid missing their slot. An in-shop tablet queue board kept walk-in customers and remote check-ins visible in the same queue, so nobody working the floor lost track of who was next.

Behind the customer-facing app, a franchise-wide staffing analytics dashboard finally gave franchisees the demand data they had never had, turning barber staffing across the week from a guess into a decision grounded in how each of the 60 shops actually filled up hour by hour.

Key decisions

01

Remote check-in before arrival

Customers can hold their place in the queue remotely, replacing the paper sign-in sheet with a system that starts working before they even reach the shop.

02

Wait times from real history

Live wait-time estimates per shop are modelled from historical service times, giving customers a real number instead of a guess based on how the line looks.

03

Barber preference built in

Barber preference selection let customers request who they usually saw, carrying a personal touch of walk-in booking into the app experience.

04

Push alerts as the turn nears

Push alerts as a customer's turn approaches meant nobody had to wait inside the shop watching the door to avoid missing their slot.

05

One queue, two dashboards

An in-shop tablet queue board and a franchise-wide staffing analytics dashboard gave staff and franchisees the visibility paper sheets never provided.

Measurable Impact

What changed after launch

Peak-hour walk-out rate dropped from 14% to 6% within 3 months of rollout, direct evidence that customers who could see a wait time before arriving were far less likely to leave once they got there. Remote check-ins grew to 57% of all visits across the franchise within 6 months, showing the habit spread quickly once customers trusted the estimates.

Average in-shop waiting time was cut by 11 minutes as arrivals spread out to match the live estimates instead of clustering at the same peak hours. The app is rated 4.6 stars across App Store and Google Play, with 85,000 downloads in its first year, a channel the franchise never had before at any of its 60 shops.

Queue management

Paper sign-in sheets at all 60 shops

Remote check-in reaching 57% of visits in 6 months

Wait times

No visibility, queues stretching past 40 minutes

Live estimates, average wait cut by 11 minutes

Walk-outs

14% peak-hour walk-out rate, uncounted

Walk-out rate down to 6% within 3 months

App reach

No digital channel of any kind

Rated 4.6 stars with 85,000 downloads in year one

Headline results

Peak-hour walk-out rate dropped from 14% to 6% within 3 months of rollout

Remote check-ins grew to 57% of all visits across the franchise within 6 months

Average in-shop waiting time cut by 11 minutes as arrivals spread to match live estimates

App rated 4.6 stars across App Store and Google Play with 85,000 downloads in the first year

Tech & Tools Used

What powered the build

Every tool below earned its place in this engagement. Here is the part each one played.

React Native logo

React Native

Built the native iOS and Android check-in app used across all 60 shops, from remote check-in through to push alerts.

TypeScript logo

TypeScript

Typed the app and backend code behind queue state, wait-time estimates and staffing data as the rollout scaled across the franchise.

Node.js (NestJS) logo

Node.js (NestJS)

Served the API behind remote check-in and the live queue, keeping each shop's wait-time estimate current as customers joined and were served.

PostgreSQL logo

PostgreSQL

Stored check-in records, historical service times and staffing data, the source behind both the wait-time model and the analytics dashboard.

Redis logo

Redis

Held each shop's live queue state, keeping remote check-ins and walk-ins visible together on the in-shop tablet board in real time.

Socket.IO logo

Socket.IO

Pushed live queue updates to the in-shop tablet board as customers checked in remotely or were served.

Firebase Cloud Messaging logo

Firebase Cloud Messaging

Delivered the push alerts that told customers their turn was approaching, without requiring them to wait inside the shop.

AWS ECS

Hosted the backend services running remote check-in and wait-time estimation reliably across all 60 shops.

Datadog logo

Datadog

Monitored the check-in and queue services, giving the team visibility as remote check-in usage grew to more than half of all visits.

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