Implemented Salesforce for a Leading International Organization Case Study
Case Study

A UK-based online marketplace improves sales by 32% by leveraging machine learning for price elasticity


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.


Online Marketplace



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The client was keen to acquire proactive visibility of price fluctuation across various product categories to drive key business objectives like -

  • Price promotion strategy
  • Visibility on optimum price levels to drive incremental Gross Merchandize Value (GMV)
  • Ability to retain its inventory margins and
  • Minimize the influence of price elasticity on Sales Velocity


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



Clear visibility

of sales velocity of different items inclusive of the seasonalities

32% Increase

In sales volume

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