Uncover customer demand anomalies, improve forecasting and make pivotal business decisions around sales forecasts, inventory planning, pricing, labor and other supply functions.
Dynamic pricing: Setting prices and packaging based on smarter forecasts.
Labor optimization: Ensuring the right number of drivers and store staff to meet demand.
Yield optimization: Tracking incoming demand ahead of the booking curve.
Merchant Services: Adding relevant demand causal factor insights to customer communications.
PredictHQ is an Accenture Data Services Partner.
Demand forecasting: Getting drivers in the right place ahead of time to improve pick-up times.
Businesses know they need to capitalize on demand forecasting, but the intricacies of the process can be daunting. Creating demand forecasting methods, building out forecasting models and deploying both quantitative and qualitative modeling techniques are common business practices, but how can you ensure and optimize forecasting accuracy?
Event data — both historical and future — are crucial demand causal factors that come from a variety of event categories . Historical event data aids in training forecasting models and is used for correlation with historical demand while forward looking data aids in forecasting future demand. Access demand intelligence by using our API or get real-time event Alerts with PredictHQ Notifications.
Gain visibility of real-world events by centralizing and aggregating event data.
Discover correlation between historical event data and demand.
Integrate demand intelligence into forecasting models.
Factors such as event type, attendance, location and audience will determine the actual impact on a business. PredictHQ has created proprietary event ranking technology that takes all factors into consideration.
Once you connect historical event data with historical incremental demand to establish the data correlation, you can begin to refine forecasting models.
PredictHQ provides feature engineering within our API like aggregate event impact, which helps businesses correlate events with demand faster. Get in touch with our experts to get access to our getting started guide.
Demand intelligence can be seamlessly integrated into your models once correlation is found – no matter what methods you’re currently using. Below are a few types of quantitative forecasting methods you might employ with event data:
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
Use demand intelligence in your yield management strategy to make the most of your occupancy and ensure higher revenue.
Identify demand drivers to package, price and update load factoring long before seats start selling.
Know about the shifts in foot traffic before they occur and make decisions around staffing, marketing promotions, and more.
Know where demand surges are happening in advance so you can price effectively and place strategically.
Contact our data science experts to find out the best solutions for your business. We'll get back to you within 1 business day.
Dynamic pricing: Setting prices and packaging based on smarter forecasts.
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.
PredictHQ is an Accenture Data Services Partner.
Predictive Analytics
Data Centralization
Inventory Management
Workforce Optimization
Dynamic Pricing