Increasing Add-to-Carts with an AI- Shopping Assistant

Industry

eCommerce

Platform

Website & Android

Live Since

August 2020

Product Used

Conversational Commerce

Tata CLiQ is the flagship digital commerce initiative of the Tata Group, the India-headquartered global conglomerate with over USD 100 billion in annual revenue. It is owned by Tata UniStore Limited. TataCLiQ operates in categories such as Electronics, Appliances, Fashion, and other Accessories. It is one of the fastest growing eCommerce startup in India.

With the onset of the pandemic and the restrictions to stay indoors, we were looking to simulate the offline shopping experience online. Our goal was to help our users experience the same comfort and get the same assistance while purchasing products online that they have in an offline store. We partnered with Haptik to build an AI-powered virtual assistant to deliver personalized recommendations and drive engagement across every stage in the buyer’s journey. We are already seeing massive success as more and more users are interacting with the AI assistant, and have observed a 2.4X increase in cart additions for users who interacted with the AI Assistant vs those who didn’t. We’re looking forward to unleashing newer opportunities with Haptik’s AI-powered assistance."

— Ankita Singh - Product Manager - Tata CliQ

Challenge

Tata CliQ drives thousands of visitors to their website and mobile app on a daily basis. However, the ratio of visitor sessions converting into transactions was lesser than expected.

The Tata CliQ team realized the need for:

A scalable way to provide buying assistance to customers, especially for high-value categories such as electronics & appliances.
The need for automation and AI-powered recommendations to improve conversions without scaling the support team.

Solution

Tata CliQ partnered with Haptik to build an AI Shopping Assistant called CliQ genie for their website and android app. CliQ Genie helps with:

Delivering personalized recommendations to users by understanding their specific preferences.
Enabling users with decision-making by choosing products most relevant to their requirements.
Answering deeper product queries both technical and non-technical, to accelerate the purchase-making process.
Extracting feature-wise sentiments from user reviews and show the qualitative judgment of each product feature.
Seamlessly connecting users with a live agent, in complex, high-value scenarios that require a human touch.