Location Scout

1. Landing page
2. Analysis input - Business + Location
3. Location analysis page - Summary metrics + Competitor space
4. Yelp AI neighborhood recommendations
5. Detailed neighborhood analysis dashboard
6. Customer review insights
7. Service offering insights
8. Responsive design

Inspiration

Location Scout was inspired by how messy and guesswork-heavy site selection is for small businesses. Most business owners rely on intuition, scattered Google searches, or expensive enterprise tools that are not practical for a single-location cafe, restaurant, or retail shop. The goal was to create a focused, self-serve tool that uses Yelp’s business data to give clear guidance on where to open and how to stand out.

What it does

Location Scout helps small business owners identify strong brick-and-mortar locations. Users enter a business type and city, such as “coffee shop” and “Boston, MA.” The app analyzes Yelp data to map competitor density, scores neighborhoods using AI for saturation and market gaps, and ranks top opportunities.

It also gives detailed analysis of recommended neighborhoods with interactive maps, demographic insights, competitor comparisons, review summaries, and service recommendations. This turns complex data into a clear checklist for differentiation.

Current Features

Input & Discovery

Simple input form with business type and controlled location autocomplete
Descriptive loading screens that show where the app is in the analysis process

High-Level Analysis

Competitor density mapping with markers and hotspots on interactive Leaflet maps
Yelp AI-powered neighborhood recommendations ranked by overall opportunity

Map & Exploration

Competitor hotspots with clustering and pin-level details
“Search This Area” interactions that update the URL and refresh the analysis based on the visible map region

Detailed Neighborhood Analysis and AI-Powered Insights

Full-screen neighborhood breakdowns with demographics, foot traffic patterns, competitor lists, and more
Market gaps extracted from competitors, along with recommended keys to success
Interactive customer review analyzer where Yelp AI pulls insights based on custom questions
Service offering suggestions tailored to each neighborhood’s gaps and customer expectations

User Experience

Fully responsive layout optimized for both desktop research and mobile scouting
Progressive loading with skeletons and spinners during API calls
A consistent design system built with shadcn/ui and Tailwind CSS

How I built it

The app was built with:

Frontend: Next.js, React, TypeScript
Maps: Leaflet for pins, clustering, and interactive bounds
APIs: Yelp Business Search API and Yelp AI Search API
AI Processing: Nvidia LLM for parsing and structuring data
UI: shadcn/ui and Tailwind CSS
Performance: Client-side caching to keep exploration fast

Challenges I ran into

Post-processing AI responses for the UI
The app needed structured outputs such as neighborhood scores and gap summaries, so I created parsing and validation steps to keep results consistent across different business types.
Optimizing API calls and caching
Each analysis required multiple Yelp and Yelp AI calls. Local caching with smart invalidation helped maintain a balance between speed, freshness, and API usage limits.

Accomplishments that I'm proud of

A smooth flow from data to decisions
Users can move from a single search to neighborhood scoring, competitor mapping, and clear action steps within minutes.
Turning Yelp AI into practical intelligence
Simple API calls now produce insights that support real location decisions for small business owners.
A fully responsive design
The app works just as well for detailed desktop analysis as it does for on-the-go exploration on mobile.

What I learned

Simple APIs can create meaningful impact
With the right structure, Yelp AI can provide the type of insights that were once available only to larger companies.
Clarity matters more than volume
Pulling large datasets is easy, but turning that information into useful guidance takes careful formatting and prioritization.
Thoughtful UX ties everything together
The flow from the landing page to the city overview, then into neighborhood detail views and personalized insights, feels natural even though the underlying logic is complex.

What's next for Location Scout

Custom analysis filters
Options for saturation, competitor density, foot traffic, budget ranges, and lease preferences.
User accounts and saved analyses
A logged-in experience with history tracking and cross-city comparisons.
AI-powered launch playbooks
Automatically generated 90-day plans for hours, pricing, marketing, and service strategy based on neighborhood needs.
Team collaboration
Shared analyses, comments, and collaborative launch planning.
Mobile-first exploration
Native iOS and Android apps with geolocation to support real-time scouting.