Excel Sheet
Budget: $10 – $30 USD
Turn in the following items:
1)Proof of Cluster Analysis
2) Answer to "Which cluster would you recommend as a primary target, and why?"
3) Submit Bar Graph
4) Present your ANOVA output table
5) Interpret your results
Open Chipotle.xlsx in Excel or Google Sheets. And open Chipotle Data Key.docx in Word or Google Docs.
Classify each variable in the Chipotle dataset as the following (or “none”):
Demographic segmentation
Psychographic segmentation
Behavioral segmentation
Outcome
Marketing mix
Product
Place
Price
Promotion
Not to be used
Decide on a distinct number of clusters (3 or 4), discussing whether there is a marketing reason for this number of clusters.
Open Chipotle.xlsx to run a cluster analysis.
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.
Save cluster membership in the data. Do this once for each of the following:
Check to see the number of people assigned to each cluster.
Repeat Steps 5-7 until you have you have created clusters that you like (each of the clusters should have at least 20 people per cluster).
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).
Profile each cluster qualitatively based on the data from Step 8 (e.g., Cluster 1 is “middle-age, wealthy cluster,” etc.)
Investigate outcome variable means for each cluster. For example, show the past frequency of Chipotle patronage for each of the clustered segments.
Which cluster would you recommend as a primary target, and why?
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).
Week 4-2 Segmented Bar Chart Example.pngDownload Week 4-2 Segmented Bar Chart Example.png
Running an ANOVA with excel:
First identify which variable you would like to work with. Put the data of the specified variable for each cluster into a separate column.
Click on the Data tab at the top of the screen and then click Data Analysis on the right-hand side. ANOVA-step 2.pngDownload ANOVA-step 2.png
Then select “Anova: Single Factor” ANOVA-Single Factor.pngDownload ANOVA-Single Factor.png
It will ask for Input Range. Identify the top leftmost box and bottom rightmost of the table you created in Step 1. Type these box labels as such - top leftmost: bottom rightmost. Click OK. ANOVA-Single factor-2.pngDownload ANOVA-Single factor-2.png
A new screen will open with the results of the ANOVA test. If the p-value is less than 0.05, we can conclude with 95% confidence that the difference between the means is statistically significant. ANOVA Output table.png
1)Proof of Cluster Analysis
2) Answer to "Which cluster would you recommend as a primary target, and why?"
3) Submit Bar Graph
4) Present your ANOVA output table
5) Interpret your results
Open Chipotle.xlsx in Excel or Google Sheets. And open Chipotle Data Key.docx in Word or Google Docs.
Classify each variable in the Chipotle dataset as the following (or “none”):
Demographic segmentation
Psychographic segmentation
Behavioral segmentation
Outcome
Marketing mix
Product
Place
Price
Promotion
Not to be used
Decide on a distinct number of clusters (3 or 4), discussing whether there is a marketing reason for this number of clusters.
Open Chipotle.xlsx to run a cluster analysis.
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.
Save cluster membership in the data. Do this once for each of the following:
Check to see the number of people assigned to each cluster.
Repeat Steps 5-7 until you have you have created clusters that you like (each of the clusters should have at least 20 people per cluster).
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).
Profile each cluster qualitatively based on the data from Step 8 (e.g., Cluster 1 is “middle-age, wealthy cluster,” etc.)
Investigate outcome variable means for each cluster. For example, show the past frequency of Chipotle patronage for each of the clustered segments.
Which cluster would you recommend as a primary target, and why?
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).
Week 4-2 Segmented Bar Chart Example.pngDownload Week 4-2 Segmented Bar Chart Example.png
Running an ANOVA with excel:
First identify which variable you would like to work with. Put the data of the specified variable for each cluster into a separate column.
Click on the Data tab at the top of the screen and then click Data Analysis on the right-hand side. ANOVA-step 2.pngDownload ANOVA-step 2.png
Then select “Anova: Single Factor” ANOVA-Single Factor.pngDownload ANOVA-Single Factor.png
It will ask for Input Range. Identify the top leftmost box and bottom rightmost of the table you created in Step 1. Type these box labels as such - top leftmost: bottom rightmost. Click OK. ANOVA-Single factor-2.pngDownload ANOVA-Single factor-2.png
A new screen will open with the results of the ANOVA test. If the p-value is less than 0.05, we can conclude with 95% confidence that the difference between the means is statistically significant. ANOVA Output table.png