Retail & Consumer Goods: Case Interview Walkthrough and Approach

Retail and consumer goods cases consistently rank among the top three industry sectors tested at MBB and Big Four firms. Based on our analysis of 800+ interview cases, what separates candidates who advance isn’t framework knowledge — it’s the ability to walk through a retail problem with operational fluency, demonstrating that you understand how stores, supply chains, and consumer behavior actually interact.

This guide takes you through a complete retail case from opening to recommendation, annotating each step with the reasoning interviewers expect to hear.

How Retail Cases Differ from Other Industries

Retail cases reward candidates who think in unit economics. Where a technology case might center on network effects or a healthcare case on regulatory barriers, retail problems almost always trace back to a simple chain: traffic × conversion × basket size × margin. Every framework you build should connect back to these levers.

Step 1: Clarify the Problem and Set Scope

The first 60 seconds determine whether you’re solving the right problem. In retail cases, the most common trap is assuming “profitability is declining” means a cost problem. In our experience working with candidates, roughly 60% of retail profitability cases are actually revenue-driven — specifically, traffic decline or basket size compression.

Questions to ask immediately:

• Which channel are we discussing? (A brick-and-mortar problem requires different levers than an e-commerce issue)
• What’s the time horizon of the decline? (Sudden vs. gradual points to different root causes)
• Is this company-specific or industry-wide? (Structural shifts vs. execution gaps)
• What’s the product mix? (Grocery behaves differently from apparel or electronics)

flowchart TD
    A[Client states problem] --> B{Clarify scope}
    B --> C[Which channel?]
    B --> D[Time horizon?]
    B --> E[Company vs. industry?]
    B --> F[Product category?]
    C --> G[Structure framework]
    D --> G
    E --> G
    F --> G
    G --> H[State hypothesis]
    H --> I[Request data]

Step 2: Build a Retail-Specific Structure

Generic frameworks fail in retail cases because they miss the operational layer. The structure below adapts the standard profitability tree to retail realities:

mindmap
  root((Retail Profit))
    Revenue
      Traffic
        Store location quality
        Marketing effectiveness
        Cannibalization from online
      Conversion
        In-store experience
        Staff availability
        Stock-out rate
      Basket Size
        Cross-selling
        Pricing architecture
        Promotional mix
    Costs
      Occupancy
        Rent per sqft
        Lease terms
        Store format efficiency
      Labor
        Hours per transaction
        Wage rate
        Scheduling optimization
      Supply Chain
        Inventory carrying cost
        Shrinkage rate
        Distribution efficiency
    Margin Mix
      Category contribution
      Private label share
      Markdown cadence

How to present this: Don’t draw the entire tree. State your top-level buckets (Revenue, Costs, Margin Mix), explain why each matters for this specific retailer, then ask which branch the interviewer wants to explore first. This demonstrates both structure and client-service awareness.

Step 3: Analyze with Retail Precision

Once the interviewer directs you to a branch, apply retail-specific analytical techniques. Here’s how analysis differs from generic approaches:

Revenue Analysis: The Traffic-to-Transaction Funnel

In our experience coaching candidates, the most impressive retail analyses decompose revenue into a physical funnel rather than abstract “price × volume”:

Cost Analysis: The Per-Square-Foot Lens

Retail costs are best analyzed on a per-unit basis. Revenue per square foot divided by cost per square foot gives you four-wall contribution — the single most important store-level metric.

Key ratios to reference:

• Revenue per square foot: $300–$600 (specialty retail), $500–$900 (grocery)
• Occupancy cost ratio: 8–15% of revenue (healthy), >20% (distressed)
• Labor as % of revenue: 10–15% (grocery), 15–25% (specialty)
• Shrinkage rate: 1–2% (well-managed), >3% (problem signal)

Step 4: Navigate Common Retail Traps

Based on our analysis of candidate performance data, these are the three mistakes that most frequently derail retail cases:

Trap 1: Treating online and offline as separate problems. Modern retail cases almost always involve channel interaction. If store traffic is declining, the interviewer expects you to ask whether online is cannibalizing or whether total brand demand is falling. The right move is to analyze total customer value across channels, not store-level P&L in isolation.

Trap 2: Ignoring seasonality in annual averages. A retailer showing 5% annual profit decline might actually be performing well in 10 months but hemorrhaging money during peak season (or vice versa). Always ask: “Is this trend consistent across quarters, or concentrated in specific periods?”

Trap 3: Recommending “cut costs” without quantifying impact at scale. Saving $0.50 per transaction sounds trivial — until you multiply by 2 million annual transactions. Retail rewards candidates who instinctively scale small numbers. Conversely, a “major initiative” costing $10M might represent 0.1% of revenue for a large retailer — barely material.

Step 5: Deliver a Structured Recommendation

Your final recommendation in a retail case should follow the “action, impact, risk” format:

1. State the core finding in one sentence (e.g., “The profitability decline is driven by a 12% traffic drop concentrated in suburban locations where a competitor opened within 2km”)
2. Quantify the impact of your recommended action (e.g., “Repositioning the promotional calendar to match the competitor’s entry timeline could recover approximately 40% of lost traffic, worth $8M in annual revenue”)
3. Flag implementation risks specific to retail (e.g., “This requires coordinating across merchandising, marketing, and store operations teams within one seasonal cycle”)

Sample Mini-Case: Specialty Retailer Margin Compression

Prompt: Your client is a 200-store specialty apparel retailer. Operating margins have dropped from 8% to 4% over two years despite flat revenue. The CEO wants to understand why and what to do.

Strong candidate approach:

1. Clarify: Revenue is flat — so this is a cost problem. Ask: which cost categories grew? Answer: labor (+3pp) and markdown costs (+1.5pp), partially offset by rent renegotiation (–0.5pp).
2. Hypothesize: Labor cost increase suggests either wage inflation, overstaffing, or declining productivity (same hours, fewer sales per hour).
3. Analyze: Request data on transactions per labor hour. Find it dropped 15% because the company maintained pre-pandemic staffing levels despite a shift of 20% of sales to online.
4. Recommend: Right-size store labor to current in-store traffic patterns, reallocating savings to digital fulfillment. Estimated margin recovery: 2pp within 12 months.

Key Takeaways

• Decompose retail revenue into the traffic → conversion → basket funnel, not abstract “price × volume”
• Always clarify channel scope and seasonality before structuring — these two questions prevent the most common wrong turns
• Think in per-square-foot and per-transaction metrics to demonstrate operational fluency
• Scale small numbers: retail operates on thin margins and massive volumes, so minor unit changes compound
• Connect online and offline in every answer — interviewers test whether you see the full picture
• End with quantified recommendations that acknowledge implementation complexity

Ready to practice retail cases with real-time feedback? Explore retail industry cases in our case library, or sharpen your approach with AI Mock Interview sessions focused on consumer goods scenarios. For deeper framework building, see our Profitability Framework Guide and Operations Case Framework.