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Lecture 4

Week 4

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Ryerson University
GEO 301
Joseph Aversa

Week 4: Customer Spotting Techniques Converse Breakpoint Method - This simple gravity model is a modification of Reillys law of retail gravitation o Based on Newtonian gravitational principles, it explains how large urbanized areas attract customers from smaller rural communities. - The method uses size and distanceof the retail centres in order to compute the trade area - Together these two variables are thought to adequately measure the relative utility of the centre which is seen to decrease with distance and increase with size - Size measures could be: number of stores, square footage of the centre, number of employees, number of parking spaces etc. ~ These level of attractiveness vary amongst people ~ Measure of attractiveness ~ Determining the distance customer is willing to travel to get to store ~ store y will have a smaller trade area because vs. Store x that level of attractiveness. The breaking line will adjust Converse Breakpoint Application - For shopping centres, stores and towns that vary in size - If they are the same size then the application of this model will produce the same result as the Thiessen polygon method Assumptions - Fully informed rational consumers (eg. We are not informed of which mall has more stores, we are not rational because we find different things attractive, we do ridiculous things everyday) - It also assumes that some measure of size is an adequate measure of the attractiveness of a centre Criticisms - To what extent does the real world meet these assumptions? - Is a size measurement an effective surrogate measure of all aspects of attractions? No, there are other factors that come into play - Does size effectively measure service and aspects of image in attraction? Bigger does not mean it is pretty - What about the ambiance and design of the centres? - Produces Spatial Monopoly- no overlap in market areas. (eg. It assumes that if you live closer to a mall, you will only go to that mall and people outside that box will not visit the further mall) Customer Spotting - Simply Defined as observing and mapping the origins of actual customers - What are potential data sources? o in-store surveys o point-of-sale query (e.g. Postal Code) o bank cheque information o redeemed coupons that had been mailed with the customer's address - The mapping is easy with GIS, as is the subsequent analysis to define a continuous market area or market penetration: Divides the entire region into zones (Census tracts, block groups, etc.). ~ Small cluster some people dont shop where they live, maybe they dont have that store where they live, maybe they work there ~ This show where you can market your campaigns The Applebaum Technique: Market Penetration - This originated as a pre-GIS method from the 1950s - Takes into account actual customer or dollar density of penetration based on distance and also distance decay ~ Distance decay: decrease in use with increase of distance - Example:o First step would be to interview random customers from a store regarding amount spent o The interviewee must be a person which spends $100 dollars weekly at the store chosen o This would make each spotted point equal to $100/week How to Compute Applebaum Technique - Divide the area into grids (200x200m, 500x500m, or using Dissemination Areas) - Place the same grid over the customer spotting map - Count the number of spotted customers in each cell - Divide the number of customers in each cell by the cells total population - The ratio or percentage is regarded as a measure of market penetration - If sales are known from the customer data, the number of customers can be translated into sales, and salescan be divided by total disposable income in the cell to develop a ratio. - Outward from the store location, the number of cells is counted until 60% or 80% of the customers or sales are reached. These cells form theprimary and secondary trade areas. - With this method, there may be some holes which have no data or no customers; or some outliers whichhave a significant number of customers. It is the analysts decision to include them or exclude them. Huff Model - The Huff Model is a spatial interaction model - It calculates gravity-based probabilities of consumers at each origin location patronizing each store in a store dataset. - As a gravity model, the Huff Model depends heavily on the calculation of distance. - This tool can use two conceptualizations of distance - traditional Euclidean (straight-line) distance as well as travel time along a street network. - To account for differences in the attractiveness of a store relative to other stores, a measure of store utilitysuch as sales volume, number of products in inventory, square footage of sales floor, store parcel size, or gross leasable area is used in conjunction withthe distance measure. - Potential store locations can also be input into the model to deter
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