I am studying the effects of a sales program on the weekly unit sales at ~1,000 retail locations. I am having trouble figuring out which statistical test is appropriate to run for this scenario. Here is the background of my problem.
I have ~1,000 stores which are divided into 3 groups:
- Program Group (~600 locations) - had a sales program applied
- Control Group (~400 locations) - did not have any program applied
- Online Group (1 location) - online sales without physical location
Each store has 17 weeks of data. Each week had one of these three possible conditions applied. These conditions did not run consecutive and they not overlapping.
- Program A: 5 out of 10 weeks
- Program B: 2 weeks out of 10 weeks
- Null Program (no program): Remaining 10 weeks
Only stores in the program group were subjected to one of the conditions and all ~600 stores were subjected for the same program for that given week. There is no reason to believe that a program would impact sales at Control stores and should be considered isolated.
The dependent variable being measured here is sales units for that week. The specific question is whether Program A or Program B or both had a measurable impact on sales against the control group. Additionally, it is possible that the program had an indirect effect on online sales which is why it is included separately.
I think an ANOVA test is required for this. However I got confused because I have repeated measures with multiple conditions. Should I be considering all 17 measures for each location (17 x 1,000)? Or do I aggregate numbers? I'm not sure how to get started. If someone can point me in the right direction it would be helpful. I have R and Excel I can use to run this analysis.