This model is designed to project sales trends of individual stores considering store attributes and the surrounding trade area.

INTAGE’s model for estimating potential by segment spares clients the burden of data conversion, sub-categorization, matching with market data and analysis reporting. It supports clients’ sales activities (hypothesis/implementation/validation) by comparing and analyzing POS/ID-POS data with the consumer panel data and the retail panel data in corresponding areas and identifying effective promotion patterns.
| Segment Model for Standard Trade Area |
Analyses are made based on six customer segments—singles, elderly, young families, kids, families—for a standard trade area. Our retail panel researches are also conducted under these attributes, allowing clients to instantly see which categories and types of products are supported by each customer segment. By using our trade area analysis software AreaManager, clients operating chain stores can easily confirm which segments their individual stores fall into. |
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| Segment Model for Original Trade Area |
We can develop store segment models incorporating sales trends of particular categories of products. As in the standard trade area segment model, clients can customize this model and can identify the types of their stores based on the categories and types of products supported by our retail panel data. |
| Marketing Target List | This solution develops models to estimate the sales of particular categories and brands based on the store attributes, population and quality of corresponding trade areas, and the competition indicated by our retail panel data. This model is useful for developing retail sales strategies by applying it to retailers’ master data. It helps to pinpoint, for individual categories and brands, those stores with larger sales potential and stores that require more promotion. |
| SCI-based Model for Estimating Market Size |
Our consumer panel data show that different categories and products are supported by households with different age groups, family sizes and income levels. This solution estimates future sales of different categories of products for individual stores by combining data on population by age group, number of households by family size, and number of households by annual income level. |