Scaling Positive Experiences via AI

Trucking insurance InsurTech MGA Cover Whale’s Chief Experience Officer discusses how the company integrated AI to drive superior customer experiences.

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In a fast-paced tech world, constant innovation is key. To be a leader in the InsurTech space, actively incorporating artificial intelligence (AI) into operations fuels scalability. In insurance, the bulk of interactions happen after one signs on the dotted line. Having a well-equipped customer service organization is critical. This article highlights the benefits of integrating AI into customer service.

If you want to feel the pulse of an organization, listen to customer calls. That’s the starting point. Then, lay the groundwork to improve and establish (or reset) onboarding and training programs for your representatives. Develop meticulous call scripts that are several decision trees deep as well as knowledge centers—internal for you and external for your customers. At Cover Whale (New York), we established a knowledge foundation first, and then developed service level agreements (SLAs) across the organization so we could get back to customers faster. We audited interactions, trained, retrained, and continually updated our knowledge centers. You can’t get to the sexy stuff—the AI—without establishing a strong foundation of basics first.

Cover Whale homepage. (Click to enlarge.)

The volume of inquiries to our company far surpasses the number of people available to answer them; an Erlang C analysis found we needed to significantly increase the size of the team to achieve our desired service levels. So, we turned to innovating with technology for the solution. We found that applying ChatGPT in its native form to customer inquiries was a risky move (see: Bing’s ChatGPT meltdown). We decided instead to leverage ChatGPT but built parameters for the technology to search only in our agent knowledge center. To date, this technology powers our in-app chatbot. It works because no matter how varied the type of question a user inputs, the chatbot serves up the right information in response. This is a stark contrast to previous chatbot technology that found it difficult to correctly understand questions.

The next trial of AI to try to improve speed-to-response was to equip our Service Team with responses for inbound email inquiries. The AI would develop friendly language at the beginning and end of the email, but the team still had to do research to get a correct policy-specific response. They found this support feature appealing, but it didn’t solve for inbound inquiries. We took the feedback and moved on, knowing what needed to be built next: AI that can use policy-specific data for substantive responses.

‘Bundle of Bots’

To address this, the AI Team built a ‘bundle of bots’ (BOB). Bob  consists of several internally trained models that create smart responses, drawing from both policy data from our platform, as well as thousands of previous customer inquiries in our CRM. We put a timer on these responses in order to be reviewed by a human as a failsafe, but with speed-to-response as the goal, the responses will still launch without human review if the clock runs out. Our Service Team is continuing to train the model by scoring every outbound response, thereby eliciting improved responses every day. While we are in the early days with the technology, initial results look promising.

The core technology is important, but so is how it all comes off to your customers. It’s important that organizations purposely build the persona of their AI. It’s like hiring a new employee—except this employee will operate at a 10,000x level. It will invariably impact your customer experience; therefore, you’ll want it to reflect your brand voice and perhaps carry a name that resonates with your customer base.

One Customer at a Time

Striking the right balance between human touch and technological efficiency in the customer’s experience is an art. It involves laying a solid foundation, iterative development, continuous learning, transparency and feedback. The journey will not be linear or flawless, but when teams start to free up to focus more on high-value tasks and increasingly difficult customer problems, you’ll know you’re on the right path. Success is not the technology itself, but using it to enhance the human connection, one customer at a time.

Cover Whale Appoints Chief AI Officer 

Saira Taneja //

Saira Taneja is Chief Experience Officer at Cover Whale, a commercial trucking insurance provider and fast-growing InsurTech. Taneja brings over a decade of experience in the health insurance sector across various functional areas where she held multiple leadership roles. Her passion for innovative market offerings led her to Cover Whale. Leveraging her expertise in scaling businesses while also achieving customer-centricity has been instrumental in the company’s success. She currently oversees the Growth, Marketing and Customer Success organizations. She holds a BA in International Business from Bentley University, and an MBA from Bentley’s McCallum Graduate School of Business.

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