How Insurance Chatbots Reduce Average Handle Time (AHT)

September 08, 2020 (Updated)

Chatbots

Average Handle Time (AHT) is an important metric for insurers. Even a small reduction in AHT impacts the bottom line. But reducing AHT simply for the sake of cost-savings is a short-sighted approach. Instead, insurance chatbots help insurers reduce AHT in ways that increase customer satisfaction and lifetime value. 

how insurance chatbots decrease aht

What is Average Handle Time? 

Average Handle Time (AHT) is the average time it takes to handle a call or transaction from start to finish. This includes the call initiation, hold time, conversation, and any followup tasks needed to resolve the call after the fact. 

Average Handle Time is calculated as follows:

Definition of AHT (Average Handle Time)

Average Handle Time is the most common metric that contact centers use to measure efficiency. And yet, for many insurers, AHT has been increasing. 

“Average handle time increased 10.99% from 2013 to 2016 and has only continued to increase since then”

Forrester, Predictions 2020: Customer Service, Oct 31, 2019

Insurance buyers are overwhelmed with information and coverage choices. They also have trouble understanding their current policies and claims processes. More than 75% of insurance customers reveal they struggle to understand the information provided by their insurer.

This increase in confusion has led to more friction in the customer journey and longer time to resolution. To be successful, insurers must address the friction that is at the root of AHT issues. 

Reducing AHT the right way with insurance chatbots

When you reduce Average Handle Time, you reduce labor costs and pressure on support teams. But, problems occur when cost optimization is the primary focus. 

Instead, the core focus should be on the customer. In insurance, meaningful relationships begin with knowing the customer and their expectations, as well as implementing an ongoing client-centric approach. 

Insurance chatbots help achieve this at scale, holding great promise both in terms of customer experience and cost savings. But, it is important to note that this wasn’t always the case.

A quick look back to 2016 reminds us why early chatbots failed to meet customer expectations. It was almost impossible to manage expectations when customers could only use text to interact with a bot. 

With text-only chatbots, it was unclear what the bot could (and couldn’t) do. The experiences were frustrating and often contributed to poor net promoter scores. 

The same was also true with AI chatbots, which were an attempt to overcorrect the issue. With AI chatbots, customers could request anything they wanted from a bot. There wasn’t a structured path toward resolution. 

Where chatbot technology is now

Finally, chatbots are now at the point where they add real value to the equation. They’ve grown so much that we often call them conversational apps or conversational interfaces. 

Conversational apps are a combination of graphic elements, text-based messaging, and rich experiences. Rather than rely solely on text exchanges, conversational apps use buttons, images, embedded calendars, and much more to make things easier. 

In short, this means that modern insurance chatbots improve customer experiences, instead of weighing them down. They’re not just a means to decrease AHT, but rather a way to increase customer satisfaction, net promoter scores, and lifetime value. 

Conversational Strategies in Banking and Insurance

Use cases for insurance chatbots

Insurance chatbots cut down on the redundant paperwork and unnecessary steps in the claims process that frustrates customers. Good insurance chatbots simplify experiences across the entire customer journey. 

Common use cases for insurance chatbots include: 

  • Managing claims and renewals
  • Generating leads by engaging visitors on your website
  • Customer feedback and reviews
  • Customer awareness and education 

Good insurance chatbots seamlessly manage the agent-human handover. For example, the bot starts the conversation then passes an agent if necessary. When the conversation is complete, the agent closes the case and passes back to the bot. After an agent marks a case as closed, the chatbot picks the conversation back up to follow up on how satisfied the customer was with their interaction.

Here you can see how a well planned conversational flow can significantly decrease AHT while making the entire process more efficient. 

Lessons learned from Lemonade

By now, you’ve heard of Lemonade, an insurtech selling home, renters, and now pet insurance. The company found a way to connect with young customers and make buying insurance quicker and simpler — mostly through intelligent automation. 

In 2017, Lemonade showed us how many steps in the insurance process were ripe for automation with their insurance chatbot, Jim. One claim that Jim processed took only a few minutes, and the claim was actually paid within three seconds of submitting it.

Again, what makes Lemonade and other insurtechs disruptive is the commitment to adding value and increasing efficiency.

“You see, A.I. Jim works at the speed of light, 24/7, but costs only a few pennies in electricity bills. It’s one of those rare cases where the best service comes with the best price tag.”

Daniel Schreiber, CEO & Co-founder of Lemonade

And, that is one of the most compelling reasons to adopt an insurance chatbot. It is a clear win-win for the customer and the business.

To succeed, insurers must make processes: 

  • easy for the customer through self-service and reducing friction
  • efficient for the customer (the right service experience, to the right user, at the right time) and 
  • emotional: forging a positive emotional bond with the customer

Are you ready to decrease your Average Handle Time with an insurance chatbot? Get in touch with our experts, today.

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