Task #1:In this case you will practice the six steps of the analytics of segmenting, targeting, and positing (STP) for Chipotle. In this process, you will run a cluster analysis on either Excel, R, or Python. This case analysis should take you about 45 to 85 minutes. You will need to download these two files:Chipotle Questionnaire and Data Key (student).docx Download Chipotle Questionnaire and Data Key (student).docxChipotle Excel Sheet (student).xlsx Download Chipotle Excel Sheet (student).xlsxNote, if you want to use R or Python instead of Excel, please view the Excel data above, but there are unique and specific data files for these applications below under the analysis steps section highlighted below that will walk you through running cluster analysis on whichever tool you prefer.Task #2:Follow this STP analytics process outlined below, you may use Excel, R, or Python, there are how-to and data sets highlighted below this task.Open Chipotle.xlsx (found above) in Excel or Google Sheets. And open Chipotle Data Key.docx (found above) in Word or Google Docs.Classify each variable in the Chipotle dataset as the following (or “none”):A. Demographic segmentationB. Psychographic segmentationC. Behavioral segmentationD. OutcomeE. Marketing mix- Product- Place- Price- PromotionF. Not to be used3. Decide on a distinct number of clusters (3 or 4), discussing whether there is a marketing reason for this number of clusters.4. Open Chipotle.xlsx to run a cluster analysis (or R or Python, see highlight section below).5. Segment the data using the K-means method. Choose whatever variables you think are best for segmentation: demographic, psychographic or behavioral variables. State which you chose and why.6. Save cluster membership in the data. Do this once for each of the following:7. Check to see the number of people assigned to each cluster.8. Repeat Steps 5-7 until you have created clusters that you like (each of the clusters should have at least 20 people per cluster).9. Investigate the clusters quantitatively using means (e.g., Cluster 1 the age mean was 34; it was 74% female and income was high at 3.4 on a four point scale).10. Profile each cluster qualitatively based on the data from Step 8 (e.g., Cluster 1 is “middle-age, wealthy cluster,” etc.)11. Investigate outcome variable means for each cluster. For example, show the past frequency of Chipotle patronage for each of the clustered segments.12. Which cluster would you recommend as a primary target, and why?13. Run means analyses for variables you classified as marketing mix variables above. What would you recommend for the marketing mix (e.g., product, place, promotion and price strategy) for the primary target, in terms of your creative input? Also, present segmented bar charts (see example below).
