Serving data in new ways for the QSR industry
Restaurant forecasts are broken
The global pandemic obliterated historical demand trends in industries across the economy. Demand patterns and consumer behavior has changed, and will continue to change in our dynamic, complex, and interconnected world.
More recently, rapidly rising inflation is hitting the economy where it hurts, and the restaurant industry is no exception. Many of these companies were struggling before the pandemic even began, and after two plus years of restrictions and regulations that shut many restaurants down for good – it’s become business-critical to better manage supply and labor costs in order to not just survive, but thrive.
For example, foot traffic to quick serve restaurants dropped nearly 60% when lockdown efforts began, with new and improved options for food delivery and online ordering beginning in March of 2020. (Source) Those businesses that used real-world data to understand shifts in demand were able to pivot to focus on optimizing contactless delivery and user-friendly customer experiences – which was the key to success for QSRs during the height of strict lockdown efforts.
Intelligent event data unlocks the ability to dynamically track events impacting your business locations including health warnings, event cancellations, postponements, and more– all updated by the minute. As live events and public gatherings continue to pick back up in 2022, event data powers the ability to anticipate demand patterns and plan around them to maximize sales while avoiding food waste and unnecessary labor costs.
Let’s take a closer look at how to use event data to improve forecasting accuracy, make data-driven business decisions, and increase profitability.
Proactively discover the catalysts that will impact your demand
Integrating dynamic event data into existing systems and processes powers explainability, and ways to better contextualize data. Detailed event data reveals correlations between different categories of events and your sales, inventory, and employee data.
For example, Domino’s Pizza integrates event data to understand how live TV events such as televised football games impact their demand. They rely on PredictHQ event data to track how this type of event impacts their inventory and staffing needs, which gives them the opportunity to fine tune their supply and number of delivery drivers on staff ahead of upcoming live TV events.
Once you identify the relationship between real-world events and your eventual business outcomes, you can use this insight to make operational decisions that cut costs and maximize revenue:
Reroute suppliers and delivery drivers to avoid traffic and weather-related challenges
Avoid being overstaffed and costly overtime pay
Prevent lost sales due to being understaffed
Get the right message to the right customers at the right time
Ensure enjoyable in-store customer experiences and timely food deliveries
Turn demand forecasting into a competitive advantage
Event data drives accurate forecasting, which directly impacts the customer experience. When hungry customers come to your stores and you’re fresh out of the best-selling menu items, they’ll seek out other options. Visibility into event-based demand insights makes it easy to stock up on fast-moving items, and schedule enough staff to handle periods of high demand – all while the competition hasn’t yet caught onto the many ways events are driving local demand.
Learn more about how to use event data to deepen insights, optimize your supply chain, and create new business opportunities in the exclusive webinar hosted by Mike Leon, Senior Analyst at ESG; Miriam McLemore, Director of Enterprise Strategy and Evangelism at AWS; and PredictHQ’s very own Chief Strategy Officer, Richard Bray.