Restaurant Gap Analysis
Restaurant Gap Analysis
We aggregate and analyze restaurant data to reveal underserved markets and cuisine gaps. Our gap analysis combines review sentiment, pricing distribution, density mapping, and cuisine coverage to identify high-potential locations. Data-driven site selection reduces opening risk significantly.
Technical Architecture
Our restaurant intelligence layer scrapes and normalizes listings from Yelp, TripAdvisor, Google Maps, and local directories. We geocode locations and build density heatmaps by cuisine type, price point, and rating. Sentiment Analysis on nearby restaurant reviews reveals unmet customer needs—what cuisines are missing, what complaints recur across existing options. We cross-reference this with demographic data and foot traffic patterns to score opportunity potential.
Data Quality & Validation
Restaurant listings decay quickly—closings, rebrandings, ownership changes. Our data pipeline validates existence through periodic freshness checks. Data Normalization standardizes cuisine tags, price symbols, and cuisine categories across sources. We implement Deduplication for restaurants listed on multiple platforms with different names or addresses. Geocoding accuracy gets validated against street-level mapping.
Compliance & Ethical Standards
We aggregate only publicly available business listing data and reviews. No private consumer data is processed. GDPR and DPDP Act 2023 compliance extends to any personal data accidentally exposed in public reviews—we implement automatic PII redaction before analysis. Our location-based insights never target individual consumers.