Webinar: How to build more meaningful machine learning models with third-party data

You will learn how:
- Third-party data can enrich your first-party data
- AWS services such as Amazon SageMaker and Amazon QuickSight can make building ML models easier and more accurate
- PredictHQ's demand intelligence can help improve forecasting accuracy
- Delivery company, Favor, improved its mean absolute percentage error (MAPE) with PredictHQ data and Amazon SageMaker
- You can find, discover, and use third-party data and APIs from AWS Data Exchange.
Watch this webinar now
Featured Speakers

Stephanie Bouic
Lead Customer Success Manager

Kevin Johnson
Head of Data Science, Favor
Customers Using PredictHQ
- Customer Stories
Labor optimization: Ensuring the right number of drivers and store staff to meet demand.
Customer storiesMeeting the demands of customers and optimizing route delivery with anticipated disruptions.
Customer StoriesDemand forecasting: Incorporating events into their Antuit-built models to better understand demand across 9600 stores.
Customer StoriesAmazon Alexa's "Events Near Me" feature uses PredictHQ data to inform users about local events.
BlogDemand forecasting: Getting drivers in the right place ahead of time to improve pick-up times.
Customer storiesEvent visibility: Available in Zartico’s platform enabling deeper insight and smarter decisions.
Customer StoriesPricing: A key source of intelligence for the Lighthouse platform, enabling smarter pricing.
Customer StoriesLabor optimization: Enriching the Legion Technologies platform, used by retailers to reduce labor inefficiencies.
Customer Stories