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Panorama: Because location still matters.

Posted by on Apr 9, 2020 in Blog | No Comments

Building on over three decades of experience in the creation and use of geodemographic segmentation systems in both Canada and the United States, Applied Geographic Solutions created a truly location-centric segmentation system, Panorama. Building on and integrating the existing suite of AGS modeling and analytical tools, Panorama creates actionable perspective on an increasingly complex and rapidly churning demographic landscape.

To create Panorama, one hundred and fifty variables were used to determine the segments. We limited the range of variables to base demographics and spatial context attributes in order to have a purely geo-demographic system. The wide range of ancillary data that AGS creates were used primarily in the validation process.

Panorama consists of sixty-eight segments. While most segmentation systems include a second order grouping, we instead encourage users to create groupings of segments tailored to their own customer profiles. All too often, the default groups are used to simplify presentations rather than to enhance analysis.

Panorama is fully documented with detailed presentation quality descriptions and caricatures of each segment including its geographic characteristics, demographics, and behavioral attributes. Panorama is paired with the industry leading GfK MRI survey in order to provide the essential linkage between neighborhood demographics and consumer behavior, creating actionable analytics for site location, neighborhood description, target marketing, and advanced analytical models.

Together with unique AGS tools like Site Signature and data such as CrimeRisk, Retail Gap, and Demographic Dimensions, Panorama is an essential tool in the analyst’s arsenal. Our new Snapshot API data delivery engine provides a suite of segmentation functions that make analysis using Panorama a snap.

To read more on the philosophy and methodology of Panorama, head here.

To read more about our view on household classification versus neighborhood segmentation, and when each is appropriate, head here.

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