Jubilant FoodWorks, which operates Domino’s Pizza in India, has adopted machine learning tools to precisely adjust prices and discounts across different times and sales channels, enabling a more nuanced response to inflation and cost pressures.
- Price hikes calibrated using machine learning by day parts and channels
- Personalized discounts deployed to optimize revenue and customer value
- Focus on protecting dine-in and takeaway growth alongside delivery
What happened
On its Q2 FY27 earnings call, Jubilant FoodWorks’ CEO Sameer Khetarpal disclosed that the company uses machine learning models to finely tune price increases across different times of day, known as day parts, and ordering channels such as delivery and dine-in. The price rises have ranged from approximately 140 to 200 basis points, reflecting a calibrated approach rather than blunt uniform hikes. Alongside pricing, Jubilant also applies data-driven personalization to target discounts, allowing for customer-specific final prices.
The company faces cost pressures including recent inflationary spikes and input cost increases, notably in cheese and other supplies. Through multiple strategies including pricing adjustments, discount management, and optimized product mix, Jubilant has been able to absorb the majority of these costs but remains prepared to adjust prices further if necessary.
Why it matters
Jubilant FoodWorks’ use of machine learning to manage pricing represents an important shift in India’s food service sector, reflecting growing capabilities to leverage data to optimize revenue and customer segmentation. This approach can help the company maintain margins without alienating price-sensitive consumers through indiscriminate price hikes.
However, this also raises questions about fairness and transparency in pricing, especially as discounts become personalized and prices may vary significantly between customers and channels. As noted by media commentators, such personalized pricing practices challenge traditional notions of consumer surplus and may pressure regulatory and market scrutiny around data use and customer rights in pricing.
What to watch next
Future updates from Jubilant FoodWorks will be closely monitored to see how their machine learning models evolve and adapt to ongoing inflation and supply disruptions. Investors and analysts will also look for disclosures on which product categories and customer segments are most affected by these targeted pricing strategies.
Additionally, it will be important to observe how consumers respond to differential pricing between dine-in, takeaway, and delivery channels, as well as how competitors in the Indian quick service restaurant industry adopt or push back against similar data-led pricing models.