Automation And Customer Insights For E-commerce Using AI Powered Rezo


The e-commerce landscape across the globe has seen a dramatic shift due to the adoption of smartphones and the advancement in payment technology. Exponential growth led to increased customer expectations and strong competition. Brands constantly need to hire more staff to be able to handle the online and offline customer support. In addition, customers interact with brands across multiple channels and it is difficult to map customer interaction across these disconnected channels.

Solution by Rezo

Rezo is built with Artificial Intelligence in his core and incorporates machine-learning, natural language processing, predictive analytics, feedback mechanism and other propriety algorithms — to automate customer service for enterprise. For e-commerce, Rezo has been piloted to achieve the following:

-Track customer interactions across multiple channels – Emails, Chats, API’s, Social Media, etc.

-Mapping customer interaction journey across multiple platforms.

-Auto-categorization of the tickets basis the content and hence ability to understand the top issues for the brand.

-Auto-routing basis the content of the issue type, location, client, etc. This enables brand to best leverage the strengths and knowledge base of agents.

-Automated responses for customer queries that are standard in nature and would need to tap into static information for responding. Examples – what is your refund policy, what is the shipping cost, reset password, etc.

-Triggering workflows that require look-up into multiple databases before responding to customer queries like order status, shipping status, etc.

-Agent Performance Metric that helps track agent performance on a number of metrics.

-Customer Satisfaction Metric that can help identify how satisfied the customers are, identifying the bottle necks and possibilities of root cause analysis.

With Rezo, brands can cope up with the pressure of online and office customer support not just the seasonal spikes but also support the variability that comes with the unexpected traffic without affecting the quality.

Rashi Gupta (Ph.D) on Linkedin
Rashi Gupta (Ph.D)
Rashi is a co-founder at She is a data science professional with over 16 years of experience in both academic and corporate. Over these years, she has worked as Assistant Professor, Lead Data Scientist and as an analyst. She works with enterprises to develop IP lead products and newer solutions/prototypes. With expertise in Text Analytics, Machine Learning and Bayesian Methodology, Rashi has designed and developed models which have been published in world renowned journals. Rashi holds her doctoral from University of Helsinki and double masters from IIT Delhi.