Executive Conversations: Putting generative AI to work in omnichannel customer service with Prashant Singh, Chief Operating Officer at LeadSquared

Prashant Singh, Chief Operating Officer at LeadSquared, joins Pravin Mittal, Director of Engineering of Amazon Aurora, for a discussion on using generative artificial intelligence (AI) to scale their omnichannel customer service application while controlling costs. LeadSquared helps customers build truly connected, empowered, and self-reliant sales and service organizations, with the power of automation.

This Executive Conversation is one of a series of discussions held with those progressing their industries where we seek to learn more about their discovery, ingenuity, and use of data and machine learning (ML).

Pravin Mittal (PM): While your business is very successful, what’s one unique characteristic about your company that sets you apart for your customers?

Prashant Singh (PS): LeadSquared empowers organizations to run high-velocity sales at scale around the world. We aim to build truly connected, empowered, and self-reliant sales organizations, with the power of automation. Our sales tech stack—sales execution, digital onboarding, and marketing, process, and field force automation—currently empowers over 250,000 users worldwide. What really sets us apart is the deep level of automation we have created for the specific industries we target.

PM: How have the service expectations of customers changed in the last 5 years, and how have you adapted LeadSquared to meet those expectations?

PS: Today, customers expect to be able to get in touch with their suppliers and business service providers anytime and in whatever channel they want. We had to adopt and build an omnichannel service across our suite of applications from sales to service in the LeadSquared CRM powered by Converse. Converse is our multi-channel messaging platform that helps businesses have real-time conversations with leads and customers.

Customers are also looking for shorter turnaround time to resolve their support queries and provide an end-to-end ticketing solution powered by AI. Our LeadSquared Service CRM provides a comprehensive platform that empowers businesses to transcend beyond basic ticketing by providing centralized support across multiple channels (like email, phone, chat, and chatbots), personalized interactions driven by AI, data-driven insights, and seamless integration with LeadSquared Sales CRM and other CRM tools.

PM: With the onset of generative AI, how has LeadSquared evolved its omnichannel services and ticketing solutions to improve customer experience?

PS: Chatbots and emails are crucial channels often leveraged by customers. Converse supported only menu-based and a natural language processing (NLP)-based conversational chatbots. There was an opportunity to upgrade the capabilities of Converse to provide chatbot functionality to answer frequently asked questions, understand user intent, and provide relevant answers to potential leads.

With the rollout of Service CRM, the role of Converse has become more and more important as it provides chatbot functionality for Service CRM users and helps in providing relevant answers to customer queries with quick turnaround time, thus providing a positive customer experience. We also realized that Service CRM can assist customer support agents by providing a summary of case notes, identify customer sentiment based on previous conversations, and generate relevant responses.

Incorporating these requirements was very expensive because before generative AI and Retrieval Augmented Generation (RAG), there was no way to automate the first-line service experience with chatbots in a way that incorporated customer data into the conversation easily and cost-effectively. We are now able to embed our customers’ unique business system data with RAG into each LeadSquared application we build for our customers. Our recently launched Service CRM is able to assist our agents by providing them a summary of case notes, and detect customer sentiment based on case history, and has improved agent’s ability to attend to more support cases, respond faster, understand customer sentiment better, thus reducing churn.

These new offerings are now part of the existing services module right out of the box and integrated to our CRM platform, bringing easy-to-use efficiencies to our customers.

PM: Did you run into any challenges leveraging generative AI in Converse and Service CRM products, and how did AWS services help?

PS: Users of the Converse platform expressed a need for expedited onboarding of chatbot functionality and more relevant responses based on their business data. Accelerating this onboarding process presented several challenges, including the time-consuming tasks of training the bot to respond to frequently asked questions and their variations, comprehending the customer domain, identifying high-volume yet low-value queries, and managing dialogue effectively. Lack of proper training data could lead to chatbots misinterpreting user intent and struggling to address unexpected questions. Additionally, dialogue management posed another challenge, requiring careful consideration of user context in responses.

The integration of RAG capabilities using Amazon Aurora PostgreSQL-Compatible Edition with the pgvector extension and large language models (LLMs) available in Amazon Bedrock has empowered our chatbots to deliver natural language responses to out-of-domain inquiries, enhanced dialogue management, and reduced our manual efforts. Consequently, we have observed a 20% improvement in customer onboarding times.

The native integration of Amazon Aurora with Amazon SageMaker and Amazon Bedrock via Amazon Aurora Machine Learning helped in summarizing case notes stored in Aurora databases without moving data outside the database and by integrating with LLMs in SageMaker and Amazon Bedrock. We were able to identify customer sentiment and emotions based on case conversation data by integrating with Amazon Comprehend and Amazon Bedrock via Aurora ML.

PM: Lastly, how do you envision LeadSquared’s competitive advantage evolving as generative AI becomes more prevalent in the market, and how do you plan to maintain your position as a leader in the industry?

PS: At LeadSquared, we are driven by using technology to help our clients be more efficient in their business. As a vertically integrated CRM and Service platform, we see generative AI offering us capabilities around services such as context summarization from support interactions, sales insights from CRM data, identifying the next best action for sales teams, goal management frameworks, and providing superior customer service via the voice channel to influence sales. All of this will help our clients enhance their top-line revenue and improve customer satisfaction.

Learn more about how LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora PostgreSQL

Learn more about how to build a generative AI-powered agent assistance application using Aurora and Amazon SageMaker JumpStart.

Learn how to lower cost per query in RAG by 75-80% with Aurora Optimized Reads.

About the authors

Pravin Mittal is Director of Engineering in Amazon Aurora; he leads the Amazon Aurora PostgreSQL and MySQL engineering team for AWS and is responsible for the daily operations, strategy, planning, positioning, and development of the business. Previous to his role with Aurora, Pravin was General Manager for Amazon Timestream and Head of Engineering for Amazon DocumentDB. He has been at AWS for 6 years, and during this time, he has built and launched both these services. Pravin has over 20 years of experience in operating systems, computer architecture, and databases. Pravin has an MBA and Master’s in Computer Science and Engineering from University of Washington, Seattle, and a Bachelor’s in Computer Science from University of Wisconsin, Madison.

Prashant is the co-founder and Chief Operating Officer of LeadSquared. He plays a vital role in defining and executing LeadSquared’s goals on product, engineering, distribution, and customer success. He is passionate about building industry leading, dominant tech companies from India that can solve problems that have significant impact on the world. Prashant is an alumnus of IIT Delhi. He was co-founder of Proteans Software prior to LeadSquared.