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Using SAS to answer the question: Where have all the meat buyers gone?. Chen Chen Dalhousie University Feb. 22, 2008. Agenda. Problem definition Methodology Results Implications Question time. Problem Definition . Retail grocery stores have noticed a decline in sales of some meats.
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Using SAS to answer the question: Where have all the meat buyers gone? Chen Chen Dalhousie University Feb. 22, 2008
Agenda • Problem definition • Methodology • Results • Implications • Question time
Problem Definition • Retail grocery stores have noticed a decline in sales of some meats. • How prevalent is this phenomenon? • What else do they buy to substitute meat? – Descriptive modeling
Objectives • Using SAS EM to explore any substitution effect on meat purchase based on two years transaction data. • Build a model to help the client store: • understand the nature of the switching behaviour, • the size of the switcher segment and • profile their shopping characteristics.
Methodology – Formulation of Variables • Use relative rather than absolute $ value to calculate consumption on each category. • Relative value: preference. • Absolute value: size dependent.
Methodology – Formulation of Variables 1. Target Variable • Meat_Switcher (Binary _1_0) • Definition: percentage change in relative meat consumption between two years. • Criteria: decline of relative consumption by 25%. • Example: assuming a person A’s relative spending on meat out of the total food spending is 20% in year 1 and 15% in year 2. Then A’s “percentage change on relative meat consumption” is = (15% - 20%)/ 20% = - 25% • Issue: expect half to decline year over year, therefore need to classify those who have major shift as meat switchers
Methodology – Formulation of Predictor Variables • Definition: the change in relative consumption in each category between 2005 and 2006. • E.g. –Seafood, vegetables, prepared meals, cheese, eggs, tofu. • The purpose of doing so is to find out any possible substitutes for meat. • For example, we may find that a meat switcher increased his relative consumption on seafood by 15% in 2006. In this way, we could say this person was substituting seafood for meat.
Methods of Analysis • During the data preparation phase, we will eliminate the shoppers who were not a meat shopper in both calendar years of 2005 and 2006 by preparing a joint file. This will allow us to compare customers against the two time periods. • Cleaning the data will also include removing the outliers that would skew the results. When analyzing meat percentage purchase of total expenditure, non-food categories will be removed such as cleaning products, flowers, and drug purchases as these are not food-related (consumption-based) departments.
Methodology – Sampling Approach • Select regular shoppers at the grocery store: those who met our criterion shopping level over the two years. • Select regular meat buyers in Year 1, that is, people that have relative consumption of meat greater than or equal to the average level of meat consumption. • Final sample of 7,000 people with 30% density.
SAS Modeling • Logistic regression & Decision Tree
Result • Three types of substitute for meat • Prepared Meals 2. Other protein 3. Snack
Targeted Promotion • Actual and Potential meat switchers can be identified using the resulting model. • Direct mail campaign or coupons at POS to facilitate purchase of substitutes. • Follow-up research to verify motives for behaviour
Thanks You Very Much! Questions?