A bakery is interested in increasing sales by optimally displaying and arranging its various baked goods and drinks. The bakery would like to know which items are typically purchased together so it can place the correlated items closer together in its display cases. The bakery has randomly selected 1,000 receipts and compiled a list of items that were purchased together for each receipt.
As an analyst, you have been asked to examine the data, summarize your findings, and recommend how the bakery can use these findings to strategically arrange its bakery products to increase sales. Use associative rules analysis to explore the various dependencies among purchased items. Use the Apriori method to do the analysis with a minimum antecedent support of 4%, minimum confidence of 70%, and maximum number of antecedents of 5. Analyze and interpret several of the resulting rules. Present your finding in the form of a 250-word executive summary that includes relevant data, charts, and tables, and addresses the following.
Question 1:How would you explain the concepts of support, confidence, and lift to an executive who is unfamiliar with association rules analysis? Include the Apriori method output chart when submitting the answer.
Question 2:What would you say about the support of the rules derived from the Apriori analysis?
Question 3:If both an apple tart and an apple Danish were purchased, how likely is it that an apple croissant is also purchased? Explain your answer.
Question 4:Does it make sense for the bakery to place all of its apple-flavored items together in the display or is it better to spread them out in the display? Explain why.
Question 5:If the bakery wanted to increase the sales of cherry soda, what cross-promotional offers could it employ? Explain why.