This case study is about one of Percolata customers -- a large Japanese apparel company with business operation worldwide.

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The customer witnessed their existing forecaster’s error rate (traffic forecast) to be 4 to 9 times higher than Percolata’s. In other words, Percolata forecast is 4 to 9 times more accurate than the existing forecaster.

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Percolata’s forecaster helps the apparel company gain a 10% revenue increase while maintaining the same labor budget.