Case Study: InPost achieves smarter demand forecasting and lower operational costs with Addepto

InPost improves demand forecasting with Addepto using 4.6 billion zł revenue data

The Polish parcel delivery company InPost faced significant challenges in demand forecasting and pricing strategy, leading to high customer churn. They struggled to keep up with rapidly shifting demand, a problem exacerbated by the COVID-19 pandemic, and their manual, intuition-based processes were causing costly delays. InPost turned to the vendor Addepto to implement an AI and machine learning-based solution to improve prediction accuracy.

Addepto built and implemented a custom Machine Learning prediction model that integrated historical data, macroeconomic factors, and third-party data, including the impact of rare events like the pandemic. This solution automated the forecasting of sales and optimized prices for individual sellers. The results for InPost included automated data processing, data-grounded predictive analytics, a reduction in customer churn, and an improved customer experience, all achieved through the ML platform developed by Addepto.

InPost