Flower Shop Market Analyzer

Flower Shop Market Analyzer is an AI agent that researches the flower shop and florist market in any city and writes a market analysis report. Give it a city (e.g. "Prague, Czech Republic") and it searches Google Maps for local flower shops, computes real market statistics (shop count, average rating, total reviews, top-rated shop), and asks an LLM to turn that data into a readable report with concrete opportunities for a new or existing flower business. Run it on-demand via the Apify Console or API, schedule it to re-check a city monthly, or plug it into an integration (Zapier, Make, Google Sheets) to keep local-market research fully automated.

Why use Flower Shop Market Analyzer?

• Market research without manual digging - instead of scrolling through Google Maps and tallying ratings by hand, get a written summary and the underlying numbers in one run.
• Business planning - aspiring florists and franchise scouts can quickly gauge how saturated or under-served a city's flower shop market is before committing to a location.
• Content and lead generation - agencies and consultants can generate city-by-city market snapshots for clients, blog posts, or pitch decks.
• Repeatable and automatable - run it across a list of cities via the Apify API, schedule recurring runs, and pipe the output straight into your CRM or spreadsheet.

How to use Flower Shop Market Analyzer

1. Open the Actor's Input tab.
2. Enter the City / location you want analyzed, e.g. "Austin, Texas".
3. Optionally set Max flower shops to analyze and pick an LLM model.
4. Optionally fill in the author fields (webpage URL, resume/bio text, avatar picture URL) if you want the generated report to include a byline - handy when republishing the report under your own name.
5. Click Start and wait for the run to finish. Under the hood, the agent calls the Google Maps Scraper to fetch real flower shop listings for the city, then an LLM analyzes the results.
6. Open the Output tab to read the report, or grab it as a Markdown file from the key-value store.

Input

The Actor accepts a JSON input with the following main fields (see the Input tab for the full form):

• locationQuery (required) - the city (optionally with country) to analyze, e.g. "Prague, Czech Republic".
• maxShopsToAnalyze - how many flower shops to pull from Google Maps for the city (default 20).
• modelName (required) - which LLM (routed through the Apify OpenRouter proxy) writes the analysis.
• webpageUrl, authorResumeText, authorAvatarUrl - optional author profile fields rendered as a byline at the end of the report.
• debug - enables verbose logging.

{
    "locationQuery": "Prague, Czech Republic",
    "maxShopsToAnalyze": 20,
    "modelName": "deepseek/deepseek-v4-flash"
}

Output

Each run pushes a single item to the dataset with the full report and the structured data behind it. You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. The report is also saved as REPORT.md in the run's key-value store for easy reading or sharing.

{
    "locationQuery": "Prague, Czech Republic",
    "report": "# Flower Shop Market Analysis: Prague, Czech Republic\n\n...",
    "structuredResponse": {
        "shopCount": 20,
        "averageRating": 4.4,
        "totalReviews": 3821,
        "topShops": [
            { "name": "Kvetinarstvi U Radnice", "rating": 4.8, "reviewsCount": 210, "website": "https://..." }
        ],
        "marketSummary": "Prague's flower shop market is dense in the historic center...",
        "opportunities": ["Same-day delivery is underserved outside the city center", "..."]
    },
    "author": {
        "webpageUrl": null,
        "resumeText": null,
        "avatarUrl": null
    }
}

Data table

Field	Description
locationQuery	The city that was analyzed
structuredResponse.shopCount	Number of flower shops found on Google Maps
structuredResponse.averageRating	Average Google rating across shops with a rating
structuredResponse.totalReviews	Total number of Google reviews across all shops
structuredResponse.topShops	Name, address, rating, reviews, and website for standout shops
structuredResponse.marketSummary	Narrative overview of the local market
structuredResponse.opportunities	LLM-identified gaps or opportunities in the city's market

How much does it cost to run Flower Shop Market Analyzer?

This Actor uses Pay Per Event pricing: a flat fee when the run starts and a flat fee when the analysis completes (see the Pricing tab for current amounts). On top of that, the Actor calls the Google Maps Scraper Actor and an LLM through the Apify OpenRouter proxy, both billed per their own usage-based pricing to your Apify account - a typical run analyzing 20 shops in one city costs a small fraction of a dollar. Apify's free tier includes monthly platform credits, so you can try it at no cost before committing to a paid plan.

Tips and advanced options

• Lower Max flower shops to analyze for a faster, cheaper run when you only need a quick pulse on a market.
• Use a more capable modelName for cities with many shops or when you need a more nuanced write-up; use a lighter model for quick, cheap checks.
• Combine with the Apify scheduler to re-run this Actor monthly and track how a city's flower shop market evolves over time.

FAQ, disclaimers, and support

This Actor only reads publicly available Google Maps listing data through the Google Maps Scraper Actor; it does not scrape private or personal data beyond what's already public on a business listing. Ratings, review counts, and market commentary are a snapshot at run time and may shift as new reviews come in. The generated analysis is written by an LLM and should be treated as a research aid, not financial or legal advice - always verify important figures before acting on them.

Found a bug or have a feature request? Open an issue in the Actor's Issues tab. Need a tailored version of this Actor (different city sources, extra data fields, custom report formats)? Reach out through the Issues tab or the developer's Apify profile for custom development.