Context An outboard motor manufacturer is looking to quantify the number of potential consumers in North America that may be interested in its products based on where they live. Challenge The company mainly wanted to target customers with a second home near a waterway, since they have a socio-demographic profile that is favorable to the purchase of a boat equipped with an outboard motor. But how do you go about adequately estimating the number of second homes across the continent? Innovation To address this issue, Indicia has developed a methodology based on the overlay and analysis of several different data sources. First, Indicia used the hydrography files to map water bodies in North America in combination with cadastral databases to locate land and buildings corresponding to second homes. This information was then cross-referenced with web extractions of real estate ads of houses and land for sale, allowing the selection criteria to be further refined. Finally, Indicia integrated data from the Canadian and U.S. censuses to isolate only single-family properties with garages. Thanks to this methodology, it has become possible to precisely map and quantify the residences that meet the established criteria. Results Through this in-depth analysis, the company obtained a reliable estimate of the number of potential consumers in North America corresponding to its target market. This data has enabled it to optimise its distribution strategy and define its marketing actions with a high level of precision.

Context A local pet food delivery company is seeking to identify its key customer segments to reduce spendings in its advertising efforts and local product deliveries. Challenge Since approximately 55% of households own a cat or dog, how can we precisely determine which of these households would be interested in a delivery service and would benefit the most from it? Innovation Indicia conducted a customer analysis to identify the main segments that have used the service over the past three years, focusing on recurrence. Three key segments emerged: owners of large breed dogs, busy large families, and elderly owners of small animals. The segments were geolocated using cadastral data on land size (to accommodate large dog breeds), census data on household size (to identify large families), and population age data (to identify elderly individuals). This information was then cross-referenced with pet ownership data to pinpoint the optimal neighborhoods for targeted postal and digital advertising, as well as to create more efficient delivery routes. Results Thanks to the targeted advertising efforts, the company was able to reduce its annual marketing budget by 35%, while increasing its revenues by 7%.