Insurers now aim for data-driven customer experience advantage
Here are five areas that should be insurance customer-care priorities.
Enhancing the insurance customer experience and using it as a differentiating factor is one of the key focus areas for today’s carriers.
Contact centers — the primary interface between the customer and insurance carrier — play a significant role in shaping the customer experience. Their performance directly impacts the organization’s reputation and perception in the consumer’s mind.
In addition to the focus on improved customer experience, contact centers also must be highly efficient to control operational costs and concurrently drive revenue growth.
Inside the contact center
Thanks to advances in technology, data management and analytics, contact centers have evolved significantly. They are now pivotal to the industry-wide transformation taking place, which is expected to continue in the coming years in order to keep pace with the customers’ increasing preference for digital channels.
The coronavirus pandemic amplified the use of contact centers across the insurance industry. In many cases, these facilities have become the only channel of communication between the insurer and the customer. This has resulted in increased call volume and average customer call time by nearly 20%, according to Talkdesk.
It follows that now more than ever, it is critical for insurance carriers to leverage data and advanced analytics to modernize their contact centers.
What follows are five areas that should be insurance customer-care priorities:
No. 1: Leverage technology and automation. Implementation of smart automation through self-service Interactive voice response (IVR), Virtual Cognitive Assistants (VCA) and chatbots no longer remains a discretionary decision for organizations. With increased competition from InsurTechs and rising labor costs, in order to stay competitive, companies need to deploy automated customer service across channels to provide a seamless omni-channel experience. The use of IVR and VCA can significantly improve the utilization of human resources by automating self-service tasks. VCA or chatbots are increasingly being deployed by insurers to handle customer interactions and obtain basic information or intent from the caller. This information can then be used to identify the customer, understand the reason for their call, and route the call to the right department. For example, a credit insurance carrier that implemented VCA to identify and authenticate claimants was able to reduce the Average Handle Time (AHT) of the call by 30 seconds.
The identification of the most frequent call types and classifying them on the basis of complexity is helping insurers to deploy AI technologies to handle simple calls and reduce the workload for the agents. One recent industry study indicated that 40% to 60% of all calls to the contact center are inquiries that can be easily handled using chatbots or conversational AI solutions. Seamless integration of the digital, IVR and chatbots can drive a large number of callers to alternate low-cost channels resulting in overall lower cost-to-serve.
No. 2: Maximize data analysis for more accurate forecasting. Incoming call volume in a contact center is not uniform across months, days or even hours. Hence, an optimum number of agents needs to be maintained to ensure prompt handling of calls.
We have observed that insurance carriers who simply rely on aggregated data with low granularity are not able to get a high level of accuracy in prediction. As the product portfolios expand with large number of call types, skill groups, agent tiers and various other factors at play, the most accurate forecasting can only be achieved through extremely granular data and implementing advanced time series modeling techniques like linear modeling, seasonal naïve, ARIMA and the Erlang C formula which calculates the probability of a call being sent to a specific skill group queue given the call volume and number of agents available at a point of time.
Using machine learning algorithms to accurately forecast the call volume and determine the accurate staff requirement helps in the optimum use of resources and ensures a positive customer experience. Using the service level thresholds along with the queueing probability can help in determining the optimal number of agents to staff throughout the day. This information can then be used to create monthly resource plans for all business units/functions.
Companies must realize that forecasting isn’t a one-time activity. It’s an ongoing process with frequent updates. Long-term forecasts may be used by workforce managers to determine hiring requirements, while short-term forecasts are extremely helpful in making scheduling decisions.
No. 3: Aim for intelligent routing and handling. A frequent reason for customer dissatisfaction is being re-routed too many times before reaching the right agent. A caller trying to get the status of his claim might be forced to go through the sales desk to policy administration before being routed to the claim adjustor. Identification of caller intent upfront can not only avoid unnecessary wastage of agent time but also improve customer experience significantly. The use of skill and competency-based routing can ensure that the call is handled by the most suitable agent in the first instance itself. This not only results in reduced handling time but also increases the likelihood of First Call Resolution (FCR).
Most insurance carriers appreciate the value of optimized lead allocation to the sales agents based on propensity to close a lead, but that same concept is still in its infancy in the telesales world. Usage of predictive algorithms to route the sales call to the agent with the highest probability to sell can significantly improve a call center’s sales performance.
We are witnessing a growing trend to map the end-to-end customer journey across channels and reimagine the entire customer experience to keep pace with the changing customer expectations. To make contact centers a real growth driver, carriers must think beyond customer care and strive to engage the customer better by leveraging micro-segmentation and analytics techniques. This will help them understand the customer better and implement behavior-based routing and handling for a delightful customer experience as well as revenue maximization.
No. 4: Capitalize on performance metrics. In order to effectively manage the contact center, it is essential to define objective-based key performance indicators and monitor them regularly. A separate set of metrics need to be tracked for objectives related to customer experience and agent productivity. A simple metric like Call Handle Time might give us information about the agent’s efficiency in handling the call quickly but doesn’t provide visibility into issue resolution success. At the same time, the call duration from the customer perspective is a completely different metric which includes the time to connect, navigate the IVR menu, waiting time in queue, routing time, time spent in talking to multiple agents, hold time as well as a post-call survey.
Organizations need to understand the complete call flow and ensure that they capture the key metrics at each node in order to identify bottlenecks and redundancies. Metrics must be clearly defined and understood across the organization for their effective adoption and usage. We have seen customer care leaders incorrectly assuming that the individual agents are responsible for Speed of Answer, while in reality, it is primarily the time spent waiting in the queue, which is only dependent on the staffing numbers.
Equally critical are the post-call IVR survey and quality control metrics. Traditionally, contact centers have been using sampling techniques to monitor the quality of a few select calls by verifying the survey feedback and validating it by listening to the call recordings. However, with improved speech-to-text algorithms as well as cloud processing platforms available to quickly generate actionable insights from the call records in near real-time, insurance carriers no longer need to be limited to screening a fraction of calls but, in fact, must score each and every call. Call scoring automation will ensure that contact center leaders leave nothing to chance and are 100% confident in their quality standards.
No. 5: Supercharge agent training. Routine transactional calls do not require advanced agent skills. This has significantly increased the emphasis on training agents who need to be skilled to handle complex customer queries or drive up-sell/cross-sell.
Post-call survey data integrated with insights generated from speech and desktop analytics tools can prove to be a treasure trove for the contact center leader looking to improve agent performance. Automated analytics systems provide contact center managers a complete picture of agent behavior by looking at patterns in speech, desktop and text interactions. This data aggregated from a large number of interactions can be leveraged to identify and highlight the specific areas where an agent is performing well, along with any opportunities for improvement.
Automated performance monitoring system can further be enhanced to identify training needs, detect issues, categorize and score incident types, provide training and self-coaching recommendations and automate performance feedback to minimize supervisor overhead. Metrics-based gamification modules add another dimension of competitiveness to help push agents to give their best performance and drive up the overall productivity of the contact center.
The takeaway
Insurance carriers always want to attract new customers while retaining existing ones through excellent customer service. The industry is in the beginning phases of a major opportunity to gain customer insights through contact centers.
Progressive insurance carriers are utilizing data and advanced analytics to transform this traditional cost center into a driver of business growth and brand development. The carriers that have been simply measuring and tracking a few basic metrics over the years are thinking that it is high time for them now to start leveraging advanced AI and ML techniques to exploit the tremendous amount of valuable data being generated by the contact centers. Such data generated every minute can help uncover customer expectation insights that will help insurers face down future challenges.
Varun Sood (Varun.Sood@exlservice.com) is an engagement manager with EXL Service and has more than 16 years of analytics consulting experience primarily in the insurance domain. He has managed and led many major analytics engagements with various large companies around the world in areas such as risk, fraud, collections, pricing, operations, and customer analytics.
Vivek Bhakuni (Vivek.Bhakuni@exlservice.com) is a project manager at EXL Service with nearly 14 years of Analytics and Technology experience. He’s worked with top insurance carriers to incorporate advanced analytics tools to increase the accuracy and efficiency of business processes.
Dr. Upendra Belhe (upendra@belheanalytics.com) is president of Belhe Analytics Advisory, which helps businesses achieve business outcomes through data-driven insights. He serves as a strategic advisor to EXL Service.
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