Case Study: Legion Technologies achieves 98% demand forecast accuracy with PredictHQ

Legion relies on PredictHQ to help retailers eliminate labor inefficiencies

Legion Technologies, a workforce management company, helps retailers optimize their teams of hourly workers. Their challenge was the poor quality of available event data, which was inconsistent, incomplete, and full of duplicates, making it unsuitable for their machine learning models. This issue forced their data scientists to spend significant time on manual data cleaning instead of core data science, threatening the scalability of their accurate demand forecasting. They needed a superior source of event data to improve their forecasts.

By implementing the PredictHQ API, Legion gained access to cleansed, enriched, and verified real-world event data. PredictHQ provided the high-quality, attribute-rich data necessary for their algorithms to learn patterns and make accurate predictions. This partnership saved Legion's data science team 20% of their manual data processing time and enabled them to achieve a 98% accuracy rate in their demand forecasts, allowing them to deliver superior labor optimization to their clients.

Legion Technologies

Thomas Joseph

Head of Data Science