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Kuwala Pricing & Cost

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About Kuwala

Learn more about Kuwala’s data sources, use cases, and integrations.

Kuwala in a Nutshell

Kuwala is a data provider offering Location Data, Foot Traffic Data, Point of Interest (POI) Data, Mobile Location Data, and 4 others. They are headquartered in Germany.

Headquarters
Germany

Use Cases

Our data is used to conduct Mobility Demand Forecasts. Furthermore, the data is used for energy and location simulations. A comparison of POIs and demographic segments is also possible. Thus, e.g. marketing and advertising surveys can be solved. The data is also partly updated on an hourly basis so that the data can be used for anti-crowding monitoring. Lastly, we track POI changes back to the year 2008 which is especially relevant for gentrification analysis and the real estate industry.

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Frequently asked questions about Kuwala

What does Kuwala do?

Kuwala enables data teams to use the power of location data through seamless integration via API.

What kind of data does Kuwala have?

Location Data, Foot Traffic Data, Point of Interest (POI) Data, Mobile Location Data, and 4 others

What data does Kuwala offer?

We provide standardized and anonymized frequency data with which we can provide information about the popularity of any location. Besides, part of the data is updated every hour. The popularity is provided in the form of arrays. Metadata about places such as addresses and categories are retrieved individually. All queries can additionally be filtered by city and/or category. Lastly, we also provide metadata about each POI up to the year 2008.

What are the best use cases for Kuwala’s data?

Our data is used to conduct Mobility Demand Forecasts. Furthermore, the data is used for energy and location simulations. A comparison of POIs and demographic segments is also possible. Thus, e.g. marketing and advertising surveys can be solved. The data is also partly updated on an hourly basis so that the data can be used for anti-crowding monitoring. Lastly, we track POI changes back to the year 2008 which is especially relevant for gentrification analysis and the real estate industry.