Algorithms at Customer Service: How Machine Learning is Shaping the Future of E-Commerce

Algorithms at Customer Service: How Machine Learning is Shaping the Future of E-Commerce

Where e. three We seek to use this technology and put it at the service of the customer (Customer-centric strategy). The main idea is Use all the data that you store on the Internet not only in the purchase process, but also in the visits to various digital channels made by the customer By analyzing and processing it Finding results that allow us to improve customer experience, build loyalty and increase conversion‘, it states Mark Tegrina Commercial Director of e.tres.

This technology has great potential. Which has had a positive impact on the consumer digital journey ever since Allows the personalization of interactions based on the strategic use of the data provided by this. every day more, Customers demand a more personalized experience. In fact, a study revealed that 73% of consumers said they were tired of being exposed to irrelevant content.

From e.tres they list some of the advantages of applying machine learning in e-commerce. This technique allows to improve:

  • Search engine results: By creating a specific search ranking based on the relevance of that specific user.

  • Attention and customer service: Providing interest and accompaniment in purchasing and resolving inquiries.

  • Supply and demand forecast: With broader and more accurate information, data-driven decisions can be made that ultimately lead to the development of better products and services.

  • Dynamic Pricing: They can be used to estimate optimal prices, such as competitor prices, time of day, inventory, season or event prices, among other examples.

  • Email fraud prevention: The more data you have, the more you can detect anomalies in the transaction. In this way, it can be used to identify patterns and find out what is normal and what is not in purchases that a particular user receives.

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