Enabled an e-commerce company to increase sales by predicting the right cashback/discount to increase GMV%

Converting Clicks to Sales with AI Analytics for Footwear

Case Study: Converting Clicks to Sales with AI Analytics for Footwear

About the Client

The client is an e-commerce and financial technology company based in India. They offer B2C services for consumers and has around 17 fulfillment centers across India partnering with more than 40 courier companies.

The Business Challenge

The client wanted to increase the sales figure for a particular category (footwear) by improving the conversion rate. Additionally, they also wanted to increase the GMV (Gross Merchandise Value) by figuring out the right amount of cashback or discount to be given.

What Aptus Data Labs Did

We built an AI-based analytics model to process existing data and predict optimal GMV and cashback to solve the business challenge.

The Impact Aptus Data Labs Made

We had to work on two main objectives that were:

  1. Increase category user visibility by getting more users from the home page to the category page to place orders.
  2. Improve conversion by offering the right cashback or discount.

Moreover, we used the following process to prepare data and build the ML model to meet the above two objectives. Aptus Data Labs:

Tools used

The Outcome

The deep learning analytics model was able to predict the optimal GMV and cashback with an accuracy of 90%. Moreover, the model enabled the client to execute this solution for every footwear brand and subcategory with sufficient data points. Therefore, the client could also plan and improve the conversion rate increasing sales. Hence, the client was able to predict banner position and idea racking to get the maximum conversion.

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