Retail Competitor Market Data Analysis
Budget: €12 – €18 EUR
I have a sizeable retail-sector market dataset that I need transformed into clear, actionable competitor insights. The core objective is to pinpoint how key players are positioning products, pricing, promotions, and geographic reach so I can refine our own strategy with evidence-backed recommendations.
Here’s what I have ready for you: raw market data pulled from industry reports, syndicated POS feeds, and several months of web-scraped pricing information. What I’m missing—and where your expertise comes in—is a rigorous competitor analysis that reveals:
• Which retailers are gaining or losing share over the last four quarters
• Pricing and discount patterns across comparable SKUs
• Category-level strengths, weaknesses, and emerging niches each competitor is exploiting
• Geographic or channel advantages that aren’t yet saturated
Please walk me through the analytical framework you would use (Python, R, Power BI, Tableau, or other relevant toolsets) and the specific visualisations or statistical tests you find most effective for retail market intelligence. A concise memo and an interactive dashboard are the preferred deliverables, but I’m open to formats that best communicate the story the data tells.
I’ll provide the cleaned data files immediately after kickoff and stay available for quick clarification so you can iterate fast. Looking forward to seeing how you turn numbers into tactical retail advantage.
Here’s what I have ready for you: raw market data pulled from industry reports, syndicated POS feeds, and several months of web-scraped pricing information. What I’m missing—and where your expertise comes in—is a rigorous competitor analysis that reveals:
• Which retailers are gaining or losing share over the last four quarters
• Pricing and discount patterns across comparable SKUs
• Category-level strengths, weaknesses, and emerging niches each competitor is exploiting
• Geographic or channel advantages that aren’t yet saturated
Please walk me through the analytical framework you would use (Python, R, Power BI, Tableau, or other relevant toolsets) and the specific visualisations or statistical tests you find most effective for retail market intelligence. A concise memo and an interactive dashboard are the preferred deliverables, but I’m open to formats that best communicate the story the data tells.
I’ll provide the cleaned data files immediately after kickoff and stay available for quick clarification so you can iterate fast. Looking forward to seeing how you turn numbers into tactical retail advantage.