Case Study: Nanit improves sales forecasting accuracy with Pecan AI

Nanit improves sales forecasting accuracy to 80% with Pecan

Nanit, a leader in smart baby-monitoring technology, faced a challenge in improving its sales forecasting accuracy. The company relied on internal models built in Python or Excel that provided limited predictive power and made it difficult to understand demand drivers. Nanit turned to Pecan AI for a predictive analytics solution to gain clearer visibility and build forecasts leadership could trust.

Using Pecan AI, Nanit generated its first predictive model in just three days and had production-ready forecasts within three weeks. The platform provided full transparency into predictions, narrowing over 20 internal assumptions down to just four true sales drivers. This resulted in forecasts with up to 80% accuracy across SKUs and channels. The solution from Pecan AI gave Nanit's leadership greater confidence in their decision-making.

Nanit