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UberRetail Releases Insights Report on how Mobile Data Improves Sales Forecasting Intelligence
  • USA - English


News provided by

Radix Collective

Dec 08, 2016, 09:00 ET

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Pasadena, CA (PRWEB) December 08, 2016 -- UberRetail, a location-based analysis platform that transforms first-party data into more actionable business intelligence, today released an insights report on how businesses can improve their trade area modeling by leveraging consumer location data and visitation habits. This level of accurate mobile location data helps retailers, restaurants, and realtors make better decisions about future sites, analyze competitors, conduct cannibalization forecasts, and improve marketing.

Mobile location data enables a new and improved approach to analyzing real-world consumer behavior for a more informed marketing strategy

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One of the most important factors in business success – or failure – is location. The “Mobile Data: The Next Generation of Trade Area Modeling” report details how mobile location data is revolutionizing more antiquated and often flawed methods of trade area modeling with a far more reliable, data-driven understanding of how, why, and when consumers move toward purchase.

“In the past, a retailers’ ability to model trade areas and estimate the effects of competition were limited to using radial and drive-time methods or using expensive customer data from intercept surveys and loyalty programs,” said Eric Aledort, chief business development officer, UberRetail. “But mobile location data provides empirical data for determining true trade areas and enables a new and improved approach to analyzing real-world consumer behavior for more informed decision making and marketing strategy.”

Among the many insights provided in the “Mobile Data: The Next Generation of Trade Area Modeling” report is how mobile data can provide a more accurate approach to understanding real-time shopping patterns as a standalone modeling tactic or a supplement to other datasets. In addition, businesses can calculate trade areas before and after an event, such as the opening of a competing store. They can also use mobile data to analyze cross-shopping behavior to see what percentage of customers shop at competitive locations, or to design conquesting campaigns in which they serve mobile ads specifically to their competitors’ customers, further drawing on mobile data’s unique applications.

For more information or to request a copy of the UberRetail mobile data report, please contact Gabriel del Rio, ubermedia(at)radixcollective.com

Gabriel del Rio, Radix Collective, http://www.UberMedia.com, +1 3109889157, [email protected]

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