Retail & Consumer Products Specialist: Industry Specific Analysis
Conduct an Institutional-Grade Analysis of any Consumer Facing Stock
Last updated: 18 December 2025
Objective:
Generate a rigorous, metrics-driven equity analysis of any Retailer or Consumer Packaged Goods company by systematically extracting, calculating, and benchmarking institutional-grade industry-specific operating, financial, and capital efficiency metrics across recent periods. The analysis is designed to translate changes in demand, margins, inventory discipline, and cash generation into clear implications for future growth durability, risk, and valuation.
Explanation:
This analysis is designed to deconstruct a Retail or Consumer Packaged Goods business into its core economic drivers, moving beyond headline revenue growth to assess the quality, sustainability, and profitability of that growth. By examining metrics such as comparable sales, traffic, average order value, price versus mix, and sales productivity, the framework distinguishes between demand-led growth and price- or promotion-driven growth, which has materially different implications for durability and valuation. Gross margin, markdown intensity, inventory turnover, and weeks of supply are used to evaluate merchandising discipline and brand pricing power, while store-level economics and customer metrics such as repeat purchase rates, lifetime value, and acquisition costs provide insight into whether growth is value-accretive at the unit level.
The analysis then links operating performance to financial outcomes through cost structure, cash flow, and capital efficiency metrics, including SG&A leverage, operating margin, free cash flow conversion, return on invested capital, and lease-adjusted balance sheet risk. These metrics determine whether scale translates into operating leverage, whether inventory and working capital are sources of cash or risk, and whether the company can fund growth, withstand cyclical pressure, and return capital to shareholders. By benchmarking these measures against peers and historical performance, the framework explicitly ties operational execution to valuation outcomes, clarifying when a company merits a premium multiple due to durable growth and strong returns versus when deteriorating demand, margin pressure, or balance sheet risk justify multiple compression.
As always, be aware that models can make mistakes. At each step, examine the response and challenge information or conclusions that appear erroneous before proceeding to any subsequent steps. If in doubt use a second model with the same prompt to verify the information and generate challenge questions and answers (CoVe process) to correct interpretations of data.
Link to blog post explanation:
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Preferred Model(s):
ChatGPT-5.2+ Deep Research Mode for strongest analysis. Gemini 3 for most accurate data pulls outside provided sources (eg valuation multiples).
Expect these highly detailed industry specific reports to take approximately 10 minutes to complete.
Important Execution Notes:
Inset the stock ticker, name and exchange where indicated
Choose sub-industry type
State periods to analyze
Provide 5-10 peers to benchmark against
Sample Output:
Copy/Paste Prompt Set:
Important note: Subscribers can use this prompt set for their own analysis. However, the prompt is copyrighted by The Inferential Investor, paywalled, and must not be shared without permission.