This is How India's Biggest Insurance Aggregator Used LLMs to Increase Sales by 15%
Results Achieved:
- Decreased lead closing time by 15%
- Boosted conversion rates by 15%
- Achieved 99% accuracy in providing precise answers from 2000+ policy documents
- Reduced information extraction time by 27%
- Decreased turnaround time by 30%
Problems:
- Higher drop rate because of higher turnaround time in addressing customer queries
- Answering policy-related questions requires reliance on the sales team lead.
- Sometimes agents provide the wrong information
BACKGROUND
India's biggest insurance aggregator was facing a problem that was affecting their sales agent's productivity.
In their sales setup, a team leader is overseeing a group of agents who sell insurance over the phone or in person.
The problem surfaced when a prospective customer inquired about a particular feature in an insurance policy. In such cases, the agent had to request clarification from the team leader to acquire the essential details before providing the customer with the information.
This procedure requires Tele-caller agents to relay queries to their team lead, who must then respond to ensure the seamless progress of the sales pipeline. This procedural bottleneck has a notable impact on their overall sales efficiency.
This process was a hassle and it also decreased the customer experience. Additionally, the agents were spending a lot of time going back and forth, which was causing the company to lose productivity. Considering the fact that the insurance collaborator is one of the largest companies in India, this loss of productivity of thousands of agents was also adversely affecting them financially.
Impact of LLM Solution:
- Reduced answer retrieval time to less than 5 seconds from the previous 5 minutes.
- Decreased dependency on team leads by 85%.
- The system accurately provides tailored plans for each prospect
How it worked behind the curtains?
1.
The insurer integrated the policy brochures into the RAG framework and linked it with GPT-3.5 (LLM).
2.
Agents were then provided with a chatbot interface containing comprehensive insurance details.
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3.
When customers inquire about specific policy information, agents simply input the query into the chatbot.
4.
The chatbot promptly provided the agents with the required information, allowing them to efficiently relay it to the customers.
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