The insurance industry’s sales and customer success teams are under pressure to deliver positive customer experiences faster than their competition. Customers expect an honest and positive experience in all end-to-end transactions like quoting, policymaking, and policy activation. Today, rising costs and long wait times have led carriers and brokers to deploy insurance chatbots to meet increased demand.
So, what makes a positive customer experience?
A recent report by PwC says nearly 80% of all American consumers point to speed, convenience, knowledgeable help, and friendly service as the most critical elements of a positive customer experience.
Traditionally, an insurance company’s customer service team would answer every customer’s phone call and email and talk about how to do business with the insurer.
In a lot of cases, traditional methods work great. The issue is scale.
Long wait times, language barriers, and a high volume of client calls and emails have increased personnel costs and led to poor prioritization of cases and a weakened customer experience for many insurers.
In response to these trends, rule-based and AI chatbots are changing the insurance industry’s customer service strategy:
- Close to 30% of life and property insurers have used chatbots in their operations in the last five years.
- Chatbots have become the leading application of AI in insurance within routine operations like customer service and lead management.
- By 2026, chatbots will occupy 40% of all overall deployment within the insurance industry’s customer service roles.
Whether rule-based or AI-enabled, chatbots lift resource constraints and drive customer service strategies across the insurance sector. As a result, it is clear that chatbot deployment will remain a priority for insurers in the foreseeable future.
Let’s examine the two main types of chatbots that insurers widely deploy: rule-based and AI-based.
Rule-Based Insurance Chatbot Advantages
Rule-based chatbots follow a predesigned sequence of questions and commands that a given user would find helpful. To configure a rule-based chatbot, insurers must analyze data to anticipate what tasks users are most often trying to accomplish. Users will choose between various options (e.g., “Help me file a claim,” “Help me complete enrollment,” “How do I adjust my plan?”), and depending on their selection, the chatbot will direct them to the right resource.
A recent survey by Drift discovered the most common frustrations for customers are websites being hard to navigate, simple questions not being answered, and primary contact information for a business being too hard to find. Rule-based bots can improve the customer experience by quickly directing a user to the correct information immediately after being asked.
When a customer asks an unprogrammed question to a rule-based bot, it can immediately transfer the conversation to a human. This ensures the chatbot can resolve simple cases while freeing capacity to deliver better customer service for more complex issues.
Based on the responses given by the user and how the rules-based chatbot is programmed, the bot can either give a written reply back or trigger a task such as sending out an email, relocating the user to a different page, scheduling a meeting, or issuing an invoice.