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The client is a multi-national online marketplace that supplies to retailers internationally while selling directly to the consumer via its own e-commerce site, with a consolidated portfolio covering kitchen and homeware, garden, beauty, fitness, and pet products.
The client was keen to acquire proactive visibility of price fluctuation across various product categories to drive key business objectives like -
An ensemble solution of multiple descriptive statistics like ANOVA, Dispersion Analysis, and Hypothesis Testing to identify key patterns across product categories
Supervised Machine Learning to estimate price elasticities across SKUs
Leveraged advanced Econometric Time series Modelings like ARIMA, Holt Winter, and Exponential Smoothing to predict futuristic prices
of sales velocity of different items inclusive of the seasonalities
In sales volume
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