Google Maps is one of the biggest location based public database in the world !
As of 2022 there were more more 200 million businesses and places referenced on Google Maps.
Moreover, we can now leverage the power of generative AI and LLM models to easily enrich data extracted from Google Maps.
If you want to learn how to Scrape Google Maps, we’ve written a detailed tutorial.
Let's explore the 5 best use cases of Scraping Google Maps !
Here's what we'll cover :
- Find new customers
- Analyse brand sentiment
- Gather reviews to train a customer service AI model
- Extract and analyse businesses images
- Check hotel availabilities to identify local traffic picks
Find new customers
Generate leads based on location 🗺
One of the biggest use cases of Google Maps Scraping is the generation of new leads for your business.
Its huge number of entries and location based organisation makes it one of the biggest leads database in the world.
One of our real estate clients recently used our platform to target companies in specific areas to offer them additional coworking spaces for their offices. By crossing the data obtained with Linkedin, they were able to determine which companies were hiring the most, thus making them potentially interested in renting new space.
The last part was getting access to email contact data, which can easily be done with B2B enrichment tools.
Generate leads based on rate and reviews ⭐️
Targeting companies based on their positive or negative reviews on Google Maps can be an interesting sales strategy for several reasons.
When targeting companies with positive reviews, sales teams can emphasize the positive feedback in their pitches, highlighting the quality of products or services and the overall positive experience customers have had.
On the other hand, targeting companies with negative reviews presents an opportunity for sales teams to position their products or services as solutions to address the pain points highlighted in the reviews.
Analyse brand sentiment
By aggregating and analyzing the sentiments expressed in reviews, businesses can gain an understanding of how customers perceive and interact with brands.
Positive sentiments highlight areas of strength, while negative sentiments point to potential areas for improvement.
This data can be used to identify common themes, track trends, and benchmark brand reputation within specific sectors.
Such analysis can inform strategic decisions, help companies address concerns, and contribute to overall brand management by fostering a positive online reputation.
One of our clients used our tool to extract hundreds of thousands of reviews from Google Maps locations in order to detect the main aspects of satisfaction or insatisfaction about big companies products
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Gather reviews to train a customer service AI model
There are tens of millions of reviews on Google Maps, and you can use them to train or to apply AI models.
A startup building an AI customer service product recently reached out to us in order to create a pipeline to regularly obtain up to date clients reviews and fine tune their model.
The goal was to gather data to help the model better understand customer sentiment in order to improve and personnalise automatic reply to customer inquiries.
Also, by identifying common issues by sectors, they were able to offer their clients with specific customers expectations so they can improve their services beforehand.
Extract and analyse businesses images
Another interesting Scraping Google Maps x AI use case which we encountered was gathering businesses location images to automatically analyse their quality.
This more specific use case enabled our client to rate potential prospects to their AI picture enhancement product by images quality.
Quality of images being a very important factor for visitors, our client was able to build list of prospects based on the bad quality of their pictures to offer them their services.
They were also able to improve their outbound process by using real images obtained from Google Maps, making the marketing messages much more personal.
Check hotel availabilities to identify local traffic picks
This is a very specific one !
Let’s say you are a local business selling products or services to tourist. By automatically checking nearby hotels availabilities, you can detect variations of arrivals and thus adapting your offers, stock or even personal availabilities to be able to match the specific demand.
If there are 10 hotels around your location, each having capacity to host 100 persons, you can be sure a thousand tourists will be present if not a single room is available in the following days !
If half of the usual rooms are available, you can expect 500 persons around.
If almost every room is available, you can reduce your stocks, employ less temporary staff, and thus avoid spending money for no reason.