Bajaj Finserv scales in revenue
and CX with yellow.ai

Learn how yellow.ai helped Bajaj Finserv offer superior CX with Blu - a multilingual bot, and helped increase revenue by many folds.

Use case:

Customer Support, Engagement & Commerce

Channels:

Website, PWA, WhatsaApp, Alexa & Google

Integration:

Salesforce

Bajaj finserv is one of the fastest growing financial institutions with over 20k employees, spread over 1400 locations. The Company has a revenue of $7.6 billion with a base of 43 million customers.

Founded
2007
Website
www.bajajfinserv.in
Industry
Finance
Company size
29,000+

Challenge

Differentiating in
the highly
competitive market

India’s financial market is a highly competitive and cluttered market. To differentiate itself from the herd, Bajaj Finserv needed a solution that would help them offer superior Customer experience whilst keeping the cost under control.

Solution

01.

Multilingual Virtual
Assistant

yellow.ai built a multilingual Virtual Assistant, BLU, which was deployed on 5 channels to help users across the customer lifecycle. The bot solves user queries, sells financial solutions and has become an integral part of web sales and services for Bajaj. In 2020 alone, it accounted for over $100M in sales.

02.

Smart Integrations

Blu had smooth integrations with Bajaj Finserv's existing CRM & billing systems which enabled seamless operations without the team having to learn to work with something new. Blu was designed to blend into Bajaj Finserv's existing tool and app ecosystems and function as an unified team.

03.

Voice Bot Services

Voice Bot services were deployed to further better customer servicing and renewal services. yellow.ai's best in tech Voice assistants helped Bajaj services streamline conversations and foster relationships with customers, at scale.

Impact

20Mn

Conversations handled so far

$16 Mn

Saved over the last one year

95%

Bot Accuracy

Looking ahead

“With yellow.ai's voice bot success in the picture, Bajaj Finserv wants to further diversify voice capabilities that'll help reduce operational costs further by 20%. Further, they also plan to achieve revenue targets of $200Mn in the coming year with an increased bot accuracy of 97%.”

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