What influences you the most when it comes to choosing where you might book a table at a restaurant? Is it simply a casual glance at the overall rating of the establishment or do you read individual reviews looking for comments about the quality of the food, service, or decor? Perhaps you want to know how much it’s likely to cost, what sort of amenities are available, how the food looks, or even how busy it gets at certain times of the day?
When making these sorts of decisions we now have a wealth of information available to us beyond simply where a place is and its opening hours. In fact quite often there can be a dizzying array of so-called sentiment data attached to individual locations, which is where effective spatial analysis comes in. We have previously looked at how sentiment data can be used in a range of use cases from identifying CPG demand hotspots to COVID-19 recovery analysis and pinpointing behaviors related to spending data. Having quick access to high-quality data from a range of providers and sources is crucial in these and other cases and we are always working to improve availability for our users.
In order to further enrich the geospatial analyses of our users in sectors such as CPG, Hospitality & Entertainment, Retail, and Real Estate; CARTO is pleased to announce our new partnership with The Data Appeal Company (TDAC), leaders in POI data and sentiment analysis, and the inclusion of their “Places & Sentiment” data in our Data Observatory.
When paired together, Places and Sentiment data are a powerful duo for Spatial Data Science. In essence, Places data refers to the detailed listing of any Point of Interest (POI), including but not limited to its business name, contact information, address information, available facilities, and its provided services. On the other hand, Sentiment data measures the level of satisfaction expressed online by users of a service, product, brand, or place. In detail, it defines the real customer perception of goods and services and pinpoints what may be influencing purchasing behaviors of current and future customers. Together, they provide competitive, market, and Location Intelligence to enhance site, neighborhood, and visitor selection along with business profiling and performance monitoring across sectors.
From today, CARTO users can start leveraging the “Places & Sentiment” data in their location intelligence analyses, with data available in multiple countries and in standardized formats. This database includes amongst others the following key variables (see The Data Appeal in CARTO’s Spatial Data Catalog):
One of the most common use cases of the Places & Sentiment datasets is the enrichment of business information for CPG companies. With this product, CPG players can complete their CRM information and better profile current and potential customers, and qualify sites and territories to distribute and launch new products. In the Hospitality and Real Estate sectors, this information is assembled in order to assess the popularity of sites, neighborhoods, and cities.
In partnering with CARTO, TDAC’s data can be accessed through CARTO’s Data Observatory, enabling organizations to easily leverage this alternative data and include it in their spatial analyses to improve decision making around site management, supply chain optimization, customer engagement, and much more. Our Data Partnerships Manager, Alejandra Aranzadi Elejabeitia, reflected on this partnership:
We are thrilled to have Data Appeal's data in our Data Observatory. The partnership has proven to be successful already and we can't wait to prove it's potential combined with our platform and features. We truly believe sentiment data is a game changer in the data field because of its reflection of the public's true experience
TDAC’s CEO and Founder, Mirko Lalli, also commented:
I'm delighted to enter into a formal partnership with CARTO. Together we have achieved much over the past year, aiding global food and beverage brands win market share, qualify leads and enrich the customer experience. CARTO's platform enables our data to be seamlessly visualized, filtered and segmented based on a customer's unique needs and requirements.
|This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 960401.|
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