Retail Sales Data Case Study
Budget: $10 – $30 USD
I have a sales dataset from the retail industry and I want it turned into a clear, decision-oriented case study. The end goal is to help management understand what is happening in the numbers and what actions to consider next.
You will start by introducing the study and stating its business-decision focus. From there, please document the dataset in plain language—source, time span, all variables, coding schemes—so that any non-technical reader can follow along.
A full descriptive analysis comes next. I need separate treatments for every qualitative and quantitative variable, followed by an exploration of how key pairs of variables interact. Well-labeled tables, graphs, or heat-maps should make those findings easy to scan.
Once the statistics are in place, translate the results into managerial insights: what the data imply for pricing, promotions, inventory, or any other retail lever that appears relevant. Finish by putting forward a set of testable hypotheses that management could validate in future studies or controlled experiments.
Deliverables
• Written report (Word or PDF) with narrative, visuals, and appendices
• Editable analysis scripts or notebooks (R, Python, or SPSS—your choice)
• Slide-ready summary of the managerial takeaways
Clarity, reproducibility, and a tone that speaks to retail decision-makers are essential. If you have questions about the dataset structure or want to suggest additional analyses, let me know early so we can keep the project moving smoothly.
You will start by introducing the study and stating its business-decision focus. From there, please document the dataset in plain language—source, time span, all variables, coding schemes—so that any non-technical reader can follow along.
A full descriptive analysis comes next. I need separate treatments for every qualitative and quantitative variable, followed by an exploration of how key pairs of variables interact. Well-labeled tables, graphs, or heat-maps should make those findings easy to scan.
Once the statistics are in place, translate the results into managerial insights: what the data imply for pricing, promotions, inventory, or any other retail lever that appears relevant. Finish by putting forward a set of testable hypotheses that management could validate in future studies or controlled experiments.
Deliverables
• Written report (Word or PDF) with narrative, visuals, and appendices
• Editable analysis scripts or notebooks (R, Python, or SPSS—your choice)
• Slide-ready summary of the managerial takeaways
Clarity, reproducibility, and a tone that speaks to retail decision-makers are essential. If you have questions about the dataset structure or want to suggest additional analyses, let me know early so we can keep the project moving smoothly.