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Improve Reorder Sales with Machine Learning-based Intelligence

Read how GSPANN helped a US-based retailer, with 800+ stores and 25B annual sales, to increase reorder sales through personalized emails and deliver relevant information at the right time utilizing machine learning (ML) algorithms.

Key highlights:

  • The ML model learned from 2 years’ data of over 47+ million transactions.
  • Increase in average order value, open rate, and CTR for the reorder email campaigns.
  • 23% decrease in email unsubscription rate.

This case study can help you understand how machine learning algorithms can do wonders by learning from historical transactional data and then deliver a deep personalization to the customers, which leads to enhanced customer experience and loyalty.

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