Recommendation/Example Analysis For The Appropriate Statistical Tests
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Description
Experience Level: Intermediate
Hi Jeremy,
I have two groups of stores -- Test (70 stores) and Control (600 stores). I would like to assess the average performance in each group both before and after we execute marketing tactics in the Test group and conduct business as usual in the Control group. Our hypothesis is that the Test group will perform better than the Control group. We will be using the following metrics to assess performance. There are seasonal effects to sales volumes.
SSS% - Same store sales percent. This is the current year net sales divided by the prior year net sales minus 1. Example: (15,000 / 14,000) - 1 = +7.1%. Approximately 840 data points in the Test group and 7,200 in the Control group.
AWS - Average Weekly Sales. This is total net sales over a date range divided by the number of operating weeks in the range. Example: 180,000 / 12 = 15,000. Approximately 840 data points in the Test group and 7,200 in the Control group.
OSAT - Overall Satisfaction Score. This is based upon customer survey responses to a Likert scale of 5 to 1 where 5 is totally satisfied and 1 is totally dissatisfied. OSAT score equals the number of 5 responses divided by total responses. Example: A store collects 100 survey responses and 70 customers select a 5 rating. 70 / 100 = 70% OSAT score. Approximately 7,000 data points in the Test group and 60,000 in the Control group.
The deliverable would be a recommendation on the appropriate statistical test to assess our hypothesis across each of the above metrics. Also, would like to see an example run on sample data we could provide to you. Our small BI shop has access to Minitab, R, and Python but would prefer Minitab as the tool of choice.
Could you provide an estimate on a total cost for this project and a timeline. We would need to have you enter into an NDA prior to sending you any data.
Thanks,
Dave Hall
Sr. Business Analyst
I have two groups of stores -- Test (70 stores) and Control (600 stores). I would like to assess the average performance in each group both before and after we execute marketing tactics in the Test group and conduct business as usual in the Control group. Our hypothesis is that the Test group will perform better than the Control group. We will be using the following metrics to assess performance. There are seasonal effects to sales volumes.
SSS% - Same store sales percent. This is the current year net sales divided by the prior year net sales minus 1. Example: (15,000 / 14,000) - 1 = +7.1%. Approximately 840 data points in the Test group and 7,200 in the Control group.
AWS - Average Weekly Sales. This is total net sales over a date range divided by the number of operating weeks in the range. Example: 180,000 / 12 = 15,000. Approximately 840 data points in the Test group and 7,200 in the Control group.
OSAT - Overall Satisfaction Score. This is based upon customer survey responses to a Likert scale of 5 to 1 where 5 is totally satisfied and 1 is totally dissatisfied. OSAT score equals the number of 5 responses divided by total responses. Example: A store collects 100 survey responses and 70 customers select a 5 rating. 70 / 100 = 70% OSAT score. Approximately 7,000 data points in the Test group and 60,000 in the Control group.
The deliverable would be a recommendation on the appropriate statistical test to assess our hypothesis across each of the above metrics. Also, would like to see an example run on sample data we could provide to you. Our small BI shop has access to Minitab, R, and Python but would prefer Minitab as the tool of choice.
Could you provide an estimate on a total cost for this project and a timeline. We would need to have you enter into an NDA prior to sending you any data.
Thanks,
Dave Hall
Sr. Business Analyst
David H.
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16 Mar 2018
United States
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