You likely have an existing forecast model or platform, but are you incorporating the right external data sources? Leading QSRs use PredictHQ's API for more accurate staffing, inventory and demand planning.
Demand Forecasting: Incorporating events into models for smarter forecasting.
Labor optimization: Ensuring the right number of drivers and store staff to meet demand.
Demand Forecasting: Incorporating events into models for smarter forecasting.
Demand forecasting: Incorporating events into their Antuit-built models to better understand demand across 9600 stores.
Amazon Alexa's "Events Near Me" feature uses PredictHQ data to inform users about local events.
Demand forecasting: Getting drivers in the right place ahead of time to improve pick-up times.
Many demand forecasting models rely primarily on internal data to predict demand for their stores, so volatility can disrupt even the best laid plans significantly. Whether caused by events you weren't prepared or major shifts in consumer behavior, restaurants miss opportunities to drive profitability and create efficient operations when forecast models don’t factor in external data.
Leading quick serve companies ingest external intelligence into their models to improve restaurant forecasting efforts. Whether it’s county-by-county TV viewership for NFL games, a nearby expo or cluster of community events, or severe weather data that impacts your store’s foot traffic, know event impact matters. PredictHQ's enriched data is the forecast-grade source of truth for anticipating event-driven demand volatility.
Gain insights into the external demand factors impacting your business
Set up staffing schedules based on anticipated demand
Align food inventory and purchasing with your improved demand forecasts
Know more than "we had a spike here last month". Historical transaction data and seasonality guides forecasting direction, but accurate predictions need external data to make the most of each location's context.
PredictHQ's data covers 18+ event categories so your models are factoring in real world changes in footfall and demand. Whether that's conferences near by or TV viewership data, this context enables QSRs to understand what will impact food orders to better anticipate demand spikes or lulls.
Anticipated demand directly impacts how store managers set their staffing schedules. If you improve accuracy and reduce forecasting errors, you can better calibrate your workforce to demand.
Train forecasting models with demand intelligence to identify peak days. Now you can guarantee the best customer service for your customers without having too many employees on the clock.
Food waste is expensive and frustrating, but you can't risk out-of-stocks. Without insight into how external circumstances impact those inventory levels, your stores are running a serious risk of ingredient shortages or millions lost in wastage.
Improve your restaurant inventory management and keep food and waste costs under control by reducing forecasting errors and ensuring accuracy with demand intelligence.
Lineup uses PredictHQ's demand intelligence to reduce forecasting errors and improve model accuracy. During initial trials, Lineup’s forecasting was 35% more accurate when leveraging demand intelligence.
There are always going to be things you’re not going to know ahead of time, especially with restaurant demand. The goal is to ensure they can help restaurants get the most accurate predictions possible, exactly when they need them to drive profitability.
Read Lineup’s Story 
Improve your forecasting models for more accurate demand predictions
Visualize event data through BI tools like Tableau or Observable to better understand impact
Get value from demand intelligence by being able to search and identify relevant events efficiently.
Know impactful events in advance and adjust prices sooner
Predict future demand fluctuations and optimize staffing schedules
Identify demand catalysts to improve supply chain efforts and inventory levels
Contact our data science experts to find out the best solutions for your business. We'll get back to you within 1 business day.
Demand Forecasting: Incorporating events into models for smarter forecasting.
Demand forecasting: Getting drivers in the right place ahead of time to improve pick-up times.
Labor optimization: Ensuring the right number of drivers and store staff to meet demand.
Amazon Alexa's "Events Near Me" feature uses PredictHQ data to inform users about local events.
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