Improve Demand Forecasts with External Intelligence

Uncover customer demand anomalies, improve forecasting and make pivotal business decisions around sales forecasts, inventory planning, pricing, labor and other supply functions.

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Customers using PredictHQ

Dynamic pricing: Setting prices and packaging based on smarter forecasts.
Customer stories
Labor optimization: Ensuring the right number of drivers and store staff to meet demand.
Customer stories
Yield optimization: Tracking incoming demand ahead of the booking curve.
Customer stories
Merchant Services: Adding relevant demand causal factor insights to customer communications.
Customer stories
Amazon Alexa's "Events Near Me" feature uses PredictHQ data to inform users about local events.
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Demand forecasting: Getting drivers in the right place ahead of time to improve pick-up times.
Customer stories

The Challenge

Inaccuracies in demand forecasting cost businesses millions each year

Demand forecasting is the heart of your business, but the process is complex and errors are frequent and costly. Companies are always working to improve their demand forecasting methods and forecasting models, and need more than commonly used datasets such as historical transactions and seasonality patterns to manage volatility. Experimenting with both quantitative and qualitative modeling is key as companies seek to drive down their forecasting error rate.

Our Solution

Incorporate external intelligence into your forecasting models to reduce errors to improve accuracy

Forecasting practitioners need to incorporate external data sources to create resilient forecasting models. Using forecast-grade data allows businesses to build accurate and dynamic models. PredictHQ factors in 18+ categories of demand causal factors – external events that are impacting your businesses – so you can train your models with the most relevant data.

Discover

Gain visibility into the external factors impacting demand fluctuations.

Train

Use our demand intelligence API to train your models with relevant, accurate data.

Improve

Reduce MAPE and improve forecasting accuracy.

Unlock the external factors driving demand

Millions of events, one global source of truth.

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.

Train your forecasting model with our API

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:

Time series models
Regression analysis models
Machine learning models
Deep learning models
Causal models

Explore the API

curl -X GET https://api.predicthq.com/v1/events/count/
  -H "Accept: application/json"
  -H "Authorization: Bearer $ACCESS_TOKEN"

Drive down error rates to improve forecast accuracy

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%.

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Customer Stories

Integrate PredictHQ into your demand forecasting and get results

Learn how customers are integrating demand intelligence into their forecasting models and seeing value.

Customer Stories

Thomas Joseph

Head of Data Science,

Legion

Thomas Joseph

Head of Data Science,

Legion

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

Demand forecasting based on industry

Data teams rely on high quality data to understand market conditions across all industries. Demand intelligence is designed to seamlessly plug into current forecasting models and improve the output