Given customer files containing ZIP Code or more detailed address information, from either over-the-counter, mail or electronic (Internet) transactions, we build demographic and product-preference profiles of the consumers in such files and identify specific segments for opt-in Internet or traditional direct promotions of special catalogs, sale and premium offers, cross-sale, trade-up and new product alerts and dedicated or vertical message tailoring for incrementing sales of existing product lines.
We predict national, metropolitan and local sales potential and profile, segment, rank, index and size markets ranging from local trading territories up to the entire United States. Our estimates are based upon custom models using geodemographic and geoeconomic indicators describing small areas to predict both sales penetration and expenditure level for specific products and services. Outputs can be obtained which are optimally ramped for mapping at any level of geography.
Expanding your "bricks and mortar" operations to the internet? Counts of retail shoppers or dollar sales of specific merchandise by ZIP Code for a sample or universe of your stores can be standardized in respect to the distance (or travel time) of the customer to the outlet by a new patented Ricercar gravity model. Demographic and economic local context data are able, then, to predict absolute sales (sales at zero distance) for any geographic unit anywhere in the United States. This estimate of sales potential based on retail data can then be used to target promotions of internet sites, mail catalogs or other advertising not affected by the spatial distribution of customers in respect to a store. Absolute sales potential also permits proactive site location, exactly indicating all of the points with high concentrations of your potential shoppers over a broad territory, not merely evaluating one site at a time with vague and loosely relevant "radius" data.
We also pinpoint the strongest geographic concentrations of prospects identified by prior research or working knowledge to occupy highly specific predetermined demographic market segments. These targeting models are derived from non-standard tabulation of huge files of census and other government survey microdata. The defining boundaries of these segments can be expressed in very fine detail (over seven-hundred occupational categories, for instance).
We build geodemographic retail site selection and evaluation models, performing territorial microanalysis which includes the effects of distance or drive time of shoppers to a prospective store (gravity gradients), sales transfer to competitive or own stores and local economic conditions;
For direct marketers possessing past promotion and response data by list, we use geographic summaries of these data as dependent variables to produce geodemographic name selection models. The resulting Response Quantiles® (RQ's®) are appended to address records in mailing lists or provided as geographic selection files in order to extract high response potential names or names with high present value in terms of continuation, renewal and payment.