Worthington, OH – 7/27/2017 – Prosper Insights & Analytics™ announces its Local Market Profiling Service which allows end-users to drill down into specific geographic segments of the Prosper data, as granular as DMA, MSA, and zip codes, as well as create proprietary aggregate areas and consumer personas with those geographic codes.

Local Market Profiling can be used for geo profiling by creating consumer personas based on geographic areas. It can be utilized in propensity modeling by estimating consumer psychographic variables for any list that contains zip code or larger geo attribute and targeting applications. It can also be used for merging datasets by providing a method for merging Prosper data with other data sets that have zip codes (e.g. transactional data).

Local Marketing Profiling can be used with Prosper’s unique datasets including the Monthly Consumer Survey and Media Behaviors & Influence Study™ to further identify local market segments that are most apt to purchase a particular type of good or service. By complimenting Prosper’s predictive first party datasets with transaction data, SMB’s and large enterprises can enhance competitive market intelligence and improve the propensity for positive post event analytics.

Prosper Insights & Analytics™
Prosper Insights & Analytics is a global leader in “consumer intent” data serving the financial services, marketing technology, and retail industries. We provide global authoritative market information on US and China consumers via curated insights and analytics. By integrating a variety of data including economic, behavioral and attitudinal data, Prosper helps companies accurately predict consumers’ future behavior to help identify market behaviors, optimize marketing efforts, and improve the effectiveness of affiliate, mobile, email, print, and social-media demand generation campaigns. To learn more: www.ProsperInsights.com

Chrissy Wissinger, Director, Communications
Stacie Nelson, Director, Customer Success

Prosper Announces Local Market Profiling Service to Further Enhance Its Datasets

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