Case Study

Delivering Just-in-Time Insights for Little Caesars

Little Caesar’s promises its “Pizza! Pizza!” will be hot-and-ready when customers walk in each store. Learn how Vervint helped the pizza chain use data in a new way to create accurate pizza production predictions.

Orange image of a pizza that is half pepperoni pizza half breadsticks. Also included is a cup of dipping sauce. In the top left corner is the Little Caesars logo.

What We Did

When Little Caesar’s wanted to use data differently to estimate pizza production by store, they invited Vervint to the kitchen to create the recipe for accurate and actionable predictions.

App Development

Machine Learning

Data Analytics

About Little Caesars

Headquartered in Detroit, Michigan, Little Caesars was founded by Mike and Marian Ilitch in 1959 as a single, family-owned restaurant. Today, Little Caesars is the third largest pizza chain in the world, with stores in each of the 50 U.S. states.

Creating the Recipe for Accurate Pizza Predictions 

Little Caesars is well-known for its “Pizza! Pizza!” slogan and promise to offer walk-in customers a Hot-N-Ready pizza that’s ready when they are. 

But how do they make that happen without having too few pizzas or too many that go unsold? 

By partnering with Vervint to deliver Hot-N-Ready data insights in a whole new way.

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Using Data in a New Way

Little Caesars was working with Microsoft to explore the idea that machine learning could deliver accurate predictions for pizza demand on a store level. Vervint came on board to bring the model to life, determining how to deliver the right data in the right way to accurately drive pizza production store-by-store.  

The Vervint team mined existing data and the primary drivers of walk-in pizza purchases. Working with Little Caesars, Vervint designed a system that leverages machine learning algorithms to provide hourly predictions for Hot-N-Ready sales by store based on historical sales data plus insights related to weather and major league baseball, football, and hockey games.  

Taking Tech to the Next Level

Vervint leveraged machine learning algorithms to create hourly predictions for Hot-N-Ready sales but took the tech to the next level to deliver tailored predictions for each store based on several data insights. 

Machine learning models typically operate on a model that feeds in a data point and returns a prediction based on that insight. Vervint added an inference engine – cutting-edge technology that allows Little Caesars to consider multiple data insights by the store to predict sales with greater accuracy.  

Over time, this machine learning algorithm gets smarter and better able to more precisely forecast pizza production based on earlier projections compared to actual sales. 

Vervint designed the processes and system to send sales data to the cloud, integrate and manage data, and send the data downstream – marking the first time it had used this technology to this scale.  

Next time you pick up pizza from Little Caesars, know that Vervint innovation helped make sure your pie was Hot-N-Ready, as promised.

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