Factoring events into your demand forecasting reduces errors and improves accuracy. Add real-world awareness into your models so you can be prepared for every event-driven demand surge or decline.
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.
Merchant Services: Adding relevant demand causal factor insights to customer communications.
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.
Demand forecasting has been stuck looking backwards for too long. Building strategies on last year or 2019’s transactions is meaningless, but knowing the evolving context and what is impacting each key location is hard. Yet profitability depends on being able to accurately build out accurate forecasting models that make use of forecast-grade external data.
Events drive demand. $1.1 trillion per year worth of demand each year in fact. Discover which event categories impact your demand and prepare, so you can turn anomalies into competitive advantage. Combine your historical data with PredictHQ’s seven years of forecast-grade event data and then use our API in your forecasting to reduce costly forecast errors.
Gain visibility into the external factors impacting demand fluctuations.
Use our demand intelligence API to train your models with relevant, accurate data.
Reduce MAPE and improve forecasting accuracy.
Demand forecasting requires extensive data, machine learning, and ruthless feature prioritization to build precise models. We capture and enrich millions of global demand causal factors that impact businesses globally. And we help you determine which features provide significant value so you can prioritize the data that matters for your business.
Outside of attended and unattended events, we’re always adding new categories to reduce demand volatility concerns. Live TV events is a new dataset that allows businesses to tap into the stay at home economy and understand how predicted TV viewership impacts demand.
Demand intelligence is forecast-grade data that can be seamlessly integrated into your models - no matter what methods you’re using. Below are a few types of quantitative forecasting methods you might employ with our external intelligence:
Revealing the drivers of demand volatility allows businesses to forecast with greater accuracy. When forecasts are more reliable, business teams can make more strategic decisions around product strategy, staffing optimization, inventory management, and more. And that can result in millions saved each year
A leading fast food chain invested in demand intelligence quickly realized that improvements in their forecasts could result in gains of $8.5M for the year. Gain access to the four steps a QSR leader took to decrease forecasting errors by 20%.
Learn how customers are integrating demand intelligence into their forecasting models and seeing value.
Don't underestimate how much effort it takes to work with event data... Being able to rely on a company whose sole purpose is to remove the ambiguity of event data has been game-changing for us.
Read Legion’s Story
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.
Predictive Analytics
Data Centralization
Inventory Management
Workforce Optimization
Dynamic Pricing