Competitive Intelligence Agent
Pricing
$7.00 / 1,000 single competitor ai analyses
An AI-powered competitive intelligence tool that extracts and analyzes data from Google Maps and social media to uncover competitor strengths, customer sentiment, and market gaps.
Type what you’d normally search for in the Google Maps search bar, like English breakfast or pet shelter. Aim for unique terms for faster processing. Using similar terms (e.g., bar vs. restaurant vs. cafe) may slightly increase your capture rate but is less efficient.
⚠️ Heads up: Adding a location directly to the search, e.g., restaurant Pittsburgh, can limit you to a maximum of 120 results per search term due to Google Maps' scrolling limit.
You can also use direct place IDs here in the format place_id:ChIJ8_JBApXMDUcRDzXcYUPTGUY.See the detailed description.
Define location using free text. Simpler formats work best; e.g., use City + Country rather than City + Country + State. Verify with the OpenStreetMap webapp for visual validation of the exact area you want to cover.
⚠️ Automatically defined City polygons may be smaller than expected (e.g., they don't include agglomeration areas). If you need to define the whole city area, head over to the 📡 Geolocation parameters* section instead to select Country, State, US County, City, or Postal code.
For an even more precise location definition (especially when using City name as a starting point), head over to 🛰 Custom search area section to create polygon shapes of the areas you want to scrape. Note that 📍 Location settings always take priority over 📡 Geolocation* (so use either section but not both at the same time).
For guidance and tricks on location definition, check our tutorial.
Number of results you expect to get per each Search term, Category or URL. The higher the number, the longer it will take.
If you want to scrape all the places available, leave this field empty or use this section 🧭 Scrape all places on the map*.
Results details will show in this language.
You can limit the places that are scraped based on the Category filter; you can choose as many categories for one flat fee for the whole field. ⚠️ Using categories can sometimes lead to false negatives, as many places do not properly categorize themselves, and there are over 4,000 available categories which Google Maps has. Using categories might filter out places that you’d like to scrape. To avoid this problem, you must list all categories that you want to scrape, including synonyms, e.g., divorce lawyer, divorce attorney, divorce service, etc. See the detailed description.
Restrict what places are scraped based on matching their name with provided 🔍 Search term. E.g., all places that have chicken in their name vs. places called Kentucky Fried Chicken.
Scrape only places with a rating equal to or above the selected stars. Places without reviews will also be skipped. Keep in mind, filtering by reviews reduces the number of places found per credit spent, as many will be excluded.
Skip places that are marked as temporary or permanently closed. Ideal for focusing on currently open places.
Set the country where the data extraction should be carried out, e.g., United States.
Enter the city where the data extraction should be carried out, e.g., Pittsburgh.
⚠️ Do not include State or Country names here.
⚠️ Automatic City polygons may be smaller than expected (e.g., they don't include agglomeration areas). If you need that, set up the location using Country, State, US County, City, or Postal code.
For an even more precise location definition (, head over to 🛰 Custom search area section to create polygon shapes of the areas you want to scrape.
Set a state where the data extraction should be carried out, e.g., Massachusetts (mainly for the US addresses).
⚠️ Always combine State with other Location types, otherwise you will scrape the whole state!
Set the US county where the data extraction should be carried out, e.g., Madison.
⚠️ Always combine US county with other Location types, otherwise you will scrape the whole county!
Set the postal code of the area where the data extraction should be carried out, e.g., 10001.
⚠️ Combine Postal code only with 🗺 Country, never with 🌇 City. You can only input one postal code at a time.
