The Language of Sectors

Quick Service Restaurants (QSR) operate as high-throughput manufacturing units on retail real estate. Unlike traditional restaurants, QSR chains like Domino's, Burger King, and KFC are evaluated on operational efficiency metrics rather than culinary quality. Understanding these KPIs is essential for analyzing earnings calls from companies like Jubilant FoodWorks, Restaurant Brands Asia, and Devyani International.

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Key Takeaways

• Same Store Sales Growth (SSSG) is the most important metric—it reveals organic growth by excluding new store openings
• Average Daily Sales (ADS) provides the clearest picture of unit economics and store-level profitability
• Gross Margin stability above 70% indicates pricing power and efficient cost management
• Store Payback Period exceeding 4 years is a red flag signaling capital inefficiency
• Digital metrics (MAU, OLO Contribution) increasingly determine competitive advantage in the sector

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Understanding QSR Metrics

The QSR business model is fundamentally about asset velocity. A restaurant location has fixed costs—rent, equipment, and base staffing—regardless of how many orders it fulfills. Profitability depends on maximizing throughput: the number of orders processed through that fixed-cost base.

This operational reality explains why QSR metrics differ significantly from traditional restaurant analysis. Standard metrics like food quality ratings or customer satisfaction scores matter less than efficiency ratios that measure how effectively the "factory" converts raw ingredients into cash flow. Investors analyzing QSR earnings calls should focus on unit economics, same-store performance, and digital adoption rather than headline revenue growth.

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Same Store Sales Growth (SSSG / LFL)

What it is: Same Store Sales Growth, also called Like-for-Like (LFL) growth, measures revenue growth from stores that have been operational for at least 12 months. It is calculated by comparing current period sales to the same period in the prior year for only those stores that were open during both periods.

Why it matters: SSSG isolates organic growth from expansion-driven growth. A company can report strong revenue growth simply by opening new stores, but SSSG reveals whether existing locations are gaining or losing traction. It is considered the most honest indicator of brand health and customer demand.

What good looks like: Sustained SSSG above 5% indicates the brand is outpacing inflation and gaining market share. Jubilant FoodWorks reported 9.1% LFL growth for Domino's India in Q2 FY25, marking seven consecutive quarters of positive SSSG—a strong performance benchmark.

Red flag: Negative SSSG combined with aggressive new store openings suggests management is using expansion to mask declining performance at existing locations. Restaurant Brands Asia (Burger King India) reported -3.0% SSSG in Q2 FY25 despite 8.5% revenue growth, indicating this concerning pattern.

Example from earnings call:

"Domino's India achieved 9.1% like-for-like growth and continued to grow ahead of the market, marking seven consecutive quarters of positive LFL growth." — Jubilant FoodWorks Q2 FY25 Earnings Call

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Average Daily Sales (ADS)

What it is: Average Daily Sales represents the total revenue generated by a single store in one day. It is calculated by dividing total store revenue by the number of operating days in the period. ADS is typically reported as "System ADS" (all stores) or "Mature Store ADS" (stores open for 12+ months).

Why it matters: ADS is the foundational metric for unit economics. It determines whether a store can cover its fixed costs and generate profit. Unlike percentage-based metrics, ADS provides an absolute cash figure that cannot be manipulated through accounting treatments.

What good looks like: For pizza-focused QSRs, mature store ADS of ₹75,000-85,000 indicates healthy performance. Domino's India reported mature store ADS of ₹80,185 in Q2 FY25—the highest in six quarters. Burger-focused formats like Burger King require higher ADS (₹110,000-120,000) due to larger store formats and higher operating costs.

Red flag: Declining ADS despite new menu launches or marketing campaigns indicates weakening demand. A gap between System ADS and Mature Store ADS exceeding 15% suggests new stores are underperforming expectations.

Example from earnings call:

"Mature Store ADS came in at Rs. 80,185—highest in last six quarters." — Jubilant FoodWorks Q2 FY25 Earnings Call

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Gross Margin

What it is: Gross Margin is calculated by subtracting the cost of raw materials (food costs) from revenue, then dividing by revenue. It is expressed as a percentage and represents the profit retained after paying for ingredients before operating expenses.

Why it matters: Gross Margin measures pricing power—the ability to pass input cost increases to customers without losing demand. QSR companies face constant pressure from volatile commodity prices (cheese, chicken, vegetables) and must balance affordability with profitability.

What good looks like: Pizza-focused chains typically operate at 74-78% Gross Margins due to lower ingredient costs (dough, cheese). Burger chains operate at 65-70% due to higher meat costs. Jubilant FoodWorks maintains approximately 76% Gross Margin, while Burger King India operates around 67%.

Red flag: Gross Margin decline of more than 100 basis points YoY often indicates aggressive discounting (e.g., "Buy 1 Get 1" offers) to maintain traffic, which erodes profitability. Sustained margin compression suggests loss of pricing power.

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Store Payback Period

What it is: Store Payback Period measures the time required for a new store's cumulative profits to equal its initial capital investment. It is calculated by dividing total store setup cost by annual store-level EBITDA.

Why it matters: This metric determines capital efficiency and return on investment. Shorter payback periods mean faster capital recycling and higher returns. It is a critical factor in evaluating expansion strategies and franchise economics.

What good looks like: Healthy QSR operations achieve payback periods of 2-3 years for company-owned stores. Domino's India typically reports payback periods in the 2.5-3 year range. Franchise models may show faster paybacks due to lower capital requirements.

Red flag: Payback periods extending beyond 4 years, or management shifting language from specific timeframes to vague terms like "long-term potential," indicates deteriorating unit economics. This often precedes writedowns or store closures.

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Monthly Active Users (MAU)

What it is: Monthly Active Users counts unique customers who interact with the brand's mobile application or digital platform within a 30-day period. It is a standard digital engagement metric borrowed from technology sector analysis.

Why it matters: MAU indicates digital platform stickiness and customer engagement depth. Higher MAU correlates with lower customer acquisition costs, better order predictability, and stronger competitive moats. Digital-first customers typically show higher order frequency and lifetime value.

What good looks like: Leading QSR apps in India target MAU exceeding 10 million with consistent growth. Domino's India reported record MAU of 12.8 million in Q2 FY25, representing 18.5% YoY growth. High MAU combined with improving conversion rates indicates strong digital execution.

Red flag: High marketing spend coupled with stagnant or declining MAU suggests ineffective customer acquisition. Low app-to-order conversion rates (below 15%) indicate engagement without monetization.

Example from earnings call:

"Record high MAU (Domino's India App) at 12.8 million (+18.5% YoY); Highest ever app conversion." — Jubilant FoodWorks Q2 FY25 Earnings Call

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OLO Contribution (Online Ordering Mix)

What it is: OLO Contribution measures the percentage of total orders placed through digital channels (mobile app, website) versus traditional channels (phone calls, walk-in counter orders). It is calculated by dividing digital orders by total orders.

Why it matters: Digital orders have lower fulfillment costs, higher average ticket sizes, and better data capture for personalization. High OLO contribution indicates successful digital transformation and operational efficiency. It also reduces dependence on aggregator platforms (Swiggy, Zomato) and their associated commissions.

What good looks like: Leading QSR operators target OLO contribution above 70% for delivery orders. Domino's India consistently reports OLO contribution exceeding 95% for delivery, reflecting strong app adoption and brand loyalty.

Red flag: Declining OLO contribution or heavy reliance on third-party aggregators (exceeding 30% of orders) indicates weak direct customer relationships and margin pressure from commission fees.

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Ticket Size vs. Traffic Split

What it is: This analysis separates SSSG into its two components: Average Ticket Size (average order value per transaction) and Traffic (number of customer transactions). The relationship reveals whether growth comes from customers spending more per visit or from more customers visiting.

Why it matters: The split provides insight into growth quality and sustainability. Traffic-led growth indicates expanding customer base and brand strength. Ticket-led growth may indicate menu price increases or successful upselling, but can mask declining customer counts.

What good looks like: Balanced growth with both metrics positive is ideal. Traffic growth of 3-5% combined with ticket growth of 2-4% indicates healthy demand expansion with effective pricing strategy.

Red flag: Positive SSSG driven entirely by ticket size increases while traffic declines suggests the brand is losing customers but extracting more from remaining ones—an unsustainable pattern that typically precedes sharper declines.

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Mature Store ADS vs. System ADS

What it is: This distinction separates Average Daily Sales for stores operational for 12+ months (Mature Store ADS) from the average across all stores including recent openings (System ADS). New stores often experience a "honeymoon period" of elevated sales that normalizes over time.

Why it matters: Mature Store ADS provides a realistic baseline for long-term unit economics, filtering out the temporary boost from new store openings. It is the more conservative and reliable measure for valuation purposes.

What good looks like: Mature Store ADS within 5-10% of System ADS indicates consistent performance across the store base. Mature Store ADS showing an upward trend over consecutive quarters signals improving brand strength.

Red flag: System ADS significantly exceeding Mature Store ADS (by more than 15%) suggests new stores are cannibalizing existing locations or that the honeymoon effect is masking underlying weakness.

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Quick Reference

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