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.

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.



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.


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

curl -X GET
  -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%.

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.

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

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