Data Analytics for an Online Retailer from continental Europe

Customer Background

Our client is an established online retail company based out of continental Europe.
Client’s primary need was to strengthen its demand forecasting catpabilities and plan inventory and other supply chain specific goals more accurately.

Client wanted to get an overview of the entire operations that could help them in forecasting the demand and plan inventory and other logistics.
Client wanted to have an on-line platform through which they could understand the hidden patterns in purchased and returned goods.

Aress assigned a team of data analytics experts who performed the necessary exploratory data analysis for finalizing the features to be used in the final dataset for modeling.
Based on the dataset that was modeled, the Aress team deployed RFM (Recency, Frequency and Monetary) model-based customer segmentation technique to understand ‘The Vital Few’ customers.
Recency (R) as the days since last purchase- How many days ago was a particular SKU last purchased.
Frequency (F) as the total number of transactions- How many times has the customer purchased from the online portal.
Monetary (M) as the total money spent - How many Euro has a particular customer spent.
Applying RFM based segmentation techniques made identifying product groups and customer groups easy.

The solution which Aress implemented helped in improving the client’s demand forecasting and planning.
It also enhanced the ability to manage inventory costs and avoid out-of-stock situations for key products.
Implementation of the solution helped in automation due to which human intervention was reduced in supply chain planning process, thereby minimizing the errors and improvement in the business performance.