Lecture 8: March 5
Market Penetration Techniques: "Customer Spotting"
What proportion of the residents/households in a given area shop at the subject store/shopping centre? ie
what is the market penetration? These approaches differ from the normative models such as Thiessen and
Huff because they attempt to meausre the actual performance (penetration) rather than suggest "what
should be" given certain assumptions.
In order to apply market penetration techniques we need:
A list of customers who actually use the store from areas (eg CTs, FSAs) around the store:
"Customer Spotting" (Applebaum 1968) eg affinity cards: air miles. and
For the same spatial units (CTs, FSAs): the total number of potential customers.
Customer spotting data can be obtained by compiling sales slips, in store contests, affinity cards, surveys,
vehicle registrations, credit cards, retailers, own credit cards, data mining, etc.
Total potential number of customers can be obtained from: CTs, EAs, FSAs, FAMEX (family
expenditure data), enumeration areas.
Actual Performance in particular areas (compare these two data sets)
Primary market: first 60% of customers (grid cells are ranked by penetration rate and aggregated to first
Secondary market: next 25%
Compare to spatial monopoly normative models.
Disadvantange is that getting data is expensive and data doesnt answer what if questions.
Site Seletion Approaches (Ch. 11)
1. Rules of Thumb: intuition, experience, observation, "gut feeling", trial and error.
2. Descriptive inventories: list of key factors, which site has most?
3. Ranking: rank sites on the basis of key factors thought to be important.
4. Ratios: of existing outlets, eg. population per store, sales per square foot. (how are variables/factors ID
above?) how do you know those factors are important?
5. Regression models: simple regression, multiple regression.
6. Location Allocation: best set of sites to serve existing population. Firehall strategy. Public sector vs
private sector. Often used in public sectors (ie hospitals)
Qualitative vs Quantitative
Subjective vs Objective
Verification of the relevance of factors.
Regression Models: Simple Regression