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I am extremely new in this quest of analytics and seek help from you lovely folk. Excluding task 21, these are the tasks I need help with i.e 22 and 23:
21 classify the orders into Lunch, dinner and others category (Completed, only for context) 22 Identify the customers who exhibit any deviation from their existing behaviour of ordering in lunch 23 Identify the change in the AOP of all the customers who changed their ordering time from lunch to dinner
on your 22 question. First define how you determine deviation. First filter the dataset to lunches, then using the summarize tool you can calculated the standard deviation and mean of ordering time or amount (depending on what you need) with grouping by customer. Then append this data back to you dataset to create a rule or formula that will flag each order if it deviates from the mean for more than one or two standard deviations (again depends on how you define the deviation). Then you filter by this flag your dataset and can see all customers with deviations.
Don't know what is AOP, but supposed that having data from previous step you can calculate it.