External data (also known as “alternative” or “third-party” data) is any data that an entity acquires beyond its four walls. Most companies are aware of the value they can gain from their own internal data such as consumer demographic information and purchase history. However, no company possesses the perfect, entirely comprehensive dataset that contains all the information to build the most accurate predictive models. This is why it is beneficial to incorporate external data in order to improve machine learning and analytics models.
By linking internal data with external data (i.e. data generated, gathered, and shared by third parties), companies can enrich their existing insights, fine-tune their operations, and unlock further growth.
Some examples of external data:
Company Data: The company data refers to information about any organization. These can include small, medium to large businesses, non-for-profit organizations that can be your customers, partners, or competitors.
People Data: This includes information about individuals that can be B2B contacts, consumers, customers, clients, guests, professionals such as physicians, or members of various organizations.
Geospatial Data: This type of alternative data provides geographical and location-specific information
Time-based Data: This set of data includes data values that vary and are monitored on a timeline
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