STRATA it is a revolutionary new retail location solution that effectively avoids the retail cluster trap. It uses a system of trade area layers to model the complexity of consumer purchase behaviour over multiple trade area shopping centres. The trade areas allow the accurate measurement of supply and demand across vastly different trade areas. This allows every retail opportunity to be compared across every trade area, big or small, in Canada. This guarantees that STRATA, not only avoids the over competitive clusters, but finds the very best opportunities while ensuring none are missed.
1. Supply and Demand Data - The Foundation. The inclusion of both supply and demand data through a unique model of seven realistic overlapping trade area layers is the underlying framework of STRATA. Without both supply and demand data, you can't accurately measure the opportunity and therefore can't avoid the retail cluster trap. Figure 1 illustrates the demand, supply and trade area layers for Toronto.
Demand: We model our own consumer spend, wealth and demographic data for Canada. We specialize in modelling data to ensure its accuracy and completeness drawing on decades of economics, statistical and mathematical model building experience. We license our data to clients independently from our custom services and solutions. Please see our data products for more detail.
Supply: We start by licensing competitor point of interest (POI) data from our partners and then enhance and augment it to include the size of the business. This is critical to the evaluation of competition and the overall accuracy of STRATA. Competitor data is then grouped into over 70 retail categories.
Figure 1: Demand & Supply Data and Trade Areas Layer Types
2. Trade Area Model - Explaining Consumer Choice: Accurately measuring retail opportunities requires an accurate model of both consumer purchase behavior and retail profitability. This is the foundation and brilliance of STRATA trade area layers. STRATA estimates seven unique overlapping trade area layer types. Trade areas effectively simplify the complexity of consumer shopping behaviour by deconstructing each type of shopping trip as a unique trade area type. Consumers choose the retail offerings in a trade area type based on the trade-off between convenience and the size of the retail offering. The larger the retail offering, the larger the trade area type and the more consumers are willing to be inconvenienced and vice versa. The choice to shop a particular class of shopping centre represents a travel pattern that defines a trade area layer. Multiple choices create multiple trade area layers. The list of consumer choices effectively builds a natural shopping path for each consumer household as they purchase goods and services from different trade area types.
Figure 2 illustrates how trade area types are used to build a natural retail shopping path for households. The brown trade area that is classified as a Small Community trade area called Yonge Eglinton Centre. Note how the region in the middle of the trade area is overlapped by higher order trade areas including a Large Community (green), Regional (blue), and Super Regional (black) trade areas. Households in this region will naturally migrate from Yonge Eglinton Centre to the SmartCentres Leaside trade area (green line) if the goods and services are not conveniently available, and then to the Manulife Centre (blue line), and then to the shopping district of Lawrence Allen and Yorkdale Shopping Centre, respectively. Shopping districts are a common occurrence in many larger shopping centres where there is a mall (Yorkdale) and a power centre (Lawrence Allen) that make up the trade area.
Figure 2: Natural Shopping Path Example
3. Calibration - Supply and Demand Accuracy: Calibration is what gives STRATA its accuracy. Trade areas typically overlap each other because consumers typically purchase goods over multiple trade areas. Advanced equilibrium modelling is used to estimate the share of wallet for each individual trade area based on the actual location and strength of the relative retail offerings of all competitors. This simulates consumer's choice to shop at a specific trade area based on the availability of retail competitors within each potential trade area shopping centre. The share of wallet estimates are then used to allocate consumer spend into each individual overlapping trade area. This effectively reconciles supply and demand and ensures that demand is double counted. This produces a new level of accuracy conventional methods simply can't match.
3. Analysis - Measuring and Comparing Opportunities: A system of realistic trade area layers coupled both calibrated supply and demand data allows accurate measurement and comparison of retail opportunities across vastly different trade areas, regardless of the size or complexity of the market. This separates STRATA from other data providers as a complete location solution. This gives STRATA the ability to compares, score and rank the performance and opportunity across almost 5,000 trade areas in Canada and over 65 retail categories. This guarantees no more over competitive retail cluster traps and the identification of the best opportunities, while ensuring none are missed.