Google Maps Intelligence

Description

Understand the competitive landscape for any business type through Google Maps data — who's nearby, how they're rated, what customers say, and where the gaps are. Supports local scans, national footprint mapping, review deep-dives, and multi-brand comparisons. Works worldwide. Use it to scout locations before opening, benchmark against nearby competitors, or mine customer reviews for what people actually love and hate.

Core Capabilities

• Auto-mode detection: Claude reads the natural language query and selects the right analysis mode — no manual mode picker
• Ratings, reviews, and peak hours: star ratings, review counts, distribution, popular times histograms, opening hours
• Review sentiment analysis: theme extraction from customer reviews, complaint/praise patterns, owner response tracking
• Geographic coverage analysis: location clustering, regional distribution, coverage gaps
• Multi-brand head-to-head: side-by-side comparison of 3+ chains across a region, including shared-city matchups
• Price level mapping: Google's $/$$/$$$/$ categorization across competitors

Good Query Examples

• Query: "What coffee shops are near Alexanderplatz, Berlin within 2km?" → Mode 1 (Local Scan) — ~50 competitors with ratings, reviews, peak hours
• Query: "Where are all McFit locations in Germany?" → Mode 2 (National Map) — ~300 locations, regional distribution, no reviews
• Query: "What do customers complain about at Joe's Pizza in New York?" | Known Competitors: "Joe's Pizza" → Mode 3 (Review Dive) — ~50 reviews with sentiment analysis
• Query: "Compare McFit, FitX, and Fitness First in Cologne" | Known Competitors: "McFit, FitX, Fitness First" → Multi-Brand head-to-head in a single city
• Query: "Welche Baeckereien gibt es in Muenchen Schwabing?" → Mode 1 (Local Scan) — German-language query

Bad Query Examples

• Query: empty → no question provided. Fix: describe the business type, location, and what you want to know
• Query: "How much traffic does nike.com get?" → Google Maps has no website traffic data. Fix: use Website Traffic Analysis
• Query: "https://www.restaurant-example.com — analyze this business" → the form needs a natural language question, not a URL. Fix: "What are customers saying about Restaurant Example in Berlin?"
• Query: "Coffee shops within 1km in Berlin Mitte" → radius search needs a precise center point (landmark or address), not a neighborhood name. The agent will ask for clarification
• Query: "What age groups visit Starbucks in Munich?" → Google Maps has no audience demographics. Fix: use GWI Spark

Use-Case Ideas

• Local competitive scan — map all competitors within a radius before opening a new location
• National footprint mapping — visualize a chain's geographic coverage and identify expansion gaps
• Review sentiment deep-dive — understand what customers love and hate from their own words
• Franchise benchmarking — compare location performance across regions for a multi-location brand
• Multi-brand head-to-head — compare 3+ competitors across a region to find positioning opportunities
• Peak hours intelligence — compare foot traffic patterns for staffing or promotion timing

Limitations

• Google Maps data only — public listings, reviews, and popular times. No website analytics, no SEO metrics, no audience demographics
• National mapping has no reviews — Mode 2 maps locations only (ratings, addresses, categories). For review analysis of specific locations, run a separate Mode 3 Review Dive
• National mapping and multi-brand take significantly longer — these are large scrapes. Local Scan and Review Dive are much faster
• Place caps per mode — local scan ~50, national map ~300, review dive ~5 focused businesses. If the cap is hit, report includes a coverage note
• Not all businesses have popular times — Google only tracks foot traffic for locations with sufficient visitor data
• Category filtering — Google returns broadly related results (e.g., parking lots, HQs). Irrelevant entries are filtered, but edge cases may slip through

Input/Output Spec

Input:

• query (required): Natural language question describing the business type, location, and what you want to know. Mode is auto-detected from this field
• location (optional): Explicit location to supplement or override what's in the query (e.g., "London W1", "Munich, Germany")
• known_competitors (optional): Comma-separated business names to include or focus on

Output:

• Markdown report (structure varies by auto-detected mode):
• Mode 1 (Local Scan): Market Overview, Competitor Comparison, Peak Hours, Review Insights, Market Gaps, Recommendations
• Mode 2 (National Map): Coverage Overview, Locations by Region/City, Performance Variations, Geographic Gaps
• Mode 3 (Review Dive): Sentiment Analysis, Theme Analysis, Strengths & Weaknesses, Owner Engagement, Actionable Insights
• Multi-Brand: Brand Overview, Location Distribution, Performance Comparison, Head-to-Head, Review Sentiment, Strategic Insights
• All modes include: Executive Summary, Methodology Note, and mandatory Appendix A with complete raw data

Disambiguation Signals

This agent analyzes Google Maps listings — competitor locations, customer reviews, ratings, peak hours, and geographic distribution. It is location-first and data-driven — "What does the competitive landscape look like on Google Maps for this business type and area?"

• Route to SEO & GEO Researcher when: the user wants domain-level search visibility, keyword rankings, or AI search presence
• Route to Website Traffic Analysis when: the user wants website traffic volumes, traffic sources, or SEO authority comparison
• Route to Advanced Web Research when: the user wants broad competitive research beyond Google Maps data
• Route to Statista when: the user wants market size statistics, industry forecasts, or published research data
• Route to GWI Spark when: the user wants consumer survey data about audience demographics, media behavior, or purchase intent