How an insurance brand improved CX with call center analytics, reducing emails by 50%

In this case study, we show how a leading insurance provider leverage advanced analytics to improve its overall call center operations. Specifically, our client adopted the use of an AI-based text mining software to locate specific reasons behind an increasingly high volume of customer complaints.

The insurance company is based in Italy and operates on a domestic level. Its mission is to be the number one insurance provider in the country. However, at one point, our client’s call center experienced an abnormally high surge in customer support tickets and calls. 

Not too long ago, or in early 2016, our Italian insurance client had experienced significant troubles with their local call centers. The operators there reported receiving a higher-than-average volume of customer complaints. Emma, one of their Customer Service Managers, was tasked to determine why so many of her firm’s policyholders were dissatisfied. She and the other managers became puzzled by this situation because they could not precisely explain the issue.

At the same time, the company lacked the proper technological infrastructure to help them deeply understand customer sentiment. They didn’t own any software or tools that could specifically analyze all the incoming call center data to uncover hidden truths behind the complaints. Therefore, our client was heavily delayed in their decision-making and action plans, which prolonged the situation. Live chat requests, emails, calls, and negative service ratings continued to build up even more.

Then, after researching into the abundance of competitive market options, Emma’s professional network referred her to Wonderflow. The tool features that appealed to Emma were our quick reporting of accurate insights and ease of use.

By leveraging artificial intelligence (AI) technology, the Wonderflow system is a highly advanced text mining analytics solution for businesses. The web scraping tool automates the entire customer feedback analysis process, thus requiring no manual support. It also performs at a highly cost-efficient speed.

Using speech-to-text analysis, the system primarily focused on collecting and analyzing data related to any form of communications between the client’s agents and customers. Some of the channels where related complaints mostly appeared were from:

• Contact center call logs or transcripts
• Chatbot conversations between agents and customers
• Emails exchanged between the client’s employees and customers (including any private communications)
• Comments and posts on the insurance company’s Facebook page
• Online community forums, expert reviews, news articles, and blog posts relating to insurance
• And much more

In turn, our client was presented with a clear report of valuable customer insights within a matter of weeks. They specifically discovered that:

• Customers were overall unsatisfied about their insurance agents’ general impoliteness and slow response time
• 37% of customer emails were free-text descriptions involving vehicle incidents; many of the firm’s policyholders called in to report something about a car accident. Yet, it took an average of six email exchanges between agent and customer to align on the issue entirely.
• Compared to three of its main competitors, and as a result of Wonderflow’s ability to provide comprehensive competitor insights, our client had the weakest brand positioning in the Italian insurance market.

Emma also explained:

Based on Wonderflow’s granular and unique insights, our Italian insurance client understood that the heart of their problem mainly lies in their poor customer service. So, Emma and her team took the following key actions:

• Designed and implemented an online contact form for their policyholders to easily use for reporting car-related accidents, resulting in fewer email complaints by nearly 50% within the first six months
• Initiated a more robust employee training program to better equip agents with the right tools and knowledge about the brand itself and its customers (e.g., internal workshops); resulting in a 4.5% improvement in first call response rate (FCR) within the initial three months
• Devised new marketing campaigns that targeted the customers of other local insurance providers and used ads that highlighted their ‘more affordable’ policy plans and speedy services; resulting in a 6% increase in insurance plan renewals and 8% in subscription purchases

 

Wonderflow respects the client’s wish to share limited information in this case study. To learn more about how our technology improves businesses, check out our solution pages tailored to the needs of insurance industry providers or for Customer Care professionals.