Key Takeaways
Knowing how to improve customer experience in insurance starts with listening to every customer conversation, not a small sample, so you can see why people call and where they get stuck.
Automated quality assurance (QA) scores 100% of calls instead of the 1-3% most teams review by hand, which gives leaders a full picture of agent performance and customer sentiment.
Real-time agent assist keeps answers about coverage, claims, and billing consistent, and it lowers agent stress and turnover.
Voice of the customer analysis and first call resolution (FCR) tracking separate problems caused by policies and systems from problems caused by agents, so you fix the real cause.
Level AI gives insurers one platform for automated QA, agent assist, voice of the customer insights, and compliance monitoring, built on what customers actually say on calls.
Introduction
Insurance customers decide whether to stay or leave based on how a claim feels. In J.D. Power's 2025 U.S. Claims Digital Experience Study, 52% of auto and homeowners insurance customers who rated their digital claim experience as poor or just okay said they were likely to leave or not renew, compared with only 4% of those who rated it excellent. The same study found that insurers delivered adequate digital claim updates only 22% of the time. These figures come from a third-party study by J.D. Power, as reported by Repairer Driven News.
That gap is the opportunity. Customers rarely call an insurer when things are going well. They call when they have a claim to file, a bill they do not understand, or a policy question that matters to them. Each of those calls is a chance to keep a customer or lose one.
This guide covers how to improve customer experience in insurance with 15 practical tactics. Each one is based on what insurance contact center leaders tell us they struggle with: QA that reviews only a few calls, agents who give different answers to the same question, and no clear way to measure repeat calls. You will also see what one insurance provider achieved with Level AI's insurance solutions.
What Are the Best Ways to Improve Customer Experience in Insurance?
The 15 tactics below cover the full insurance customer experience, from the first claim call to long-term retention. The table gives a quick view, and the sections after it explain each one.
# | Tactic | Customer problem it solves | Metric to watch |
|---|---|---|---|
1 | Automated QA | Most calls are never reviewed | QA coverage, QA scores |
2 | AI agent assistance | Agents give different answers | Accuracy, handle time |
3 | Personalization | Service feels generic | CSAT, retention |
4 | Omnichannel service | Customers repeat themselves across channels | Channel switches, CSAT |
5 | Data-driven decisions | Changes are based on opinion | Time to act on issues |
6 | Voice of the customer analysis | Leaders do not know why customers call | Top contact reasons |
7 | First call resolution | Customers call back | FCR, repeat contacts |
8 | Proactive outreach | Customers chase updates | Inbound status calls |
9 | Agent training and onboarding | New agents take too long to learn | Ramp time |
10 | Compliance and risk monitoring | Missed disclosures and privacy slips | Compliance pass rate |
11 | Pain point identification | Hidden issues drive repeat calls | Issue volume by theme |
12 | Process improvement | Broken tools and policies frustrate customers | Effort, repeat calls |
13 | Agent productivity and retention | High agent turnover | Attrition, tenure |
14 | Satisfaction and retention | Customers leave after a bad experience | CSAT, renewal rate |
15 | Agency performance analysis | Uneven results across agencies | Quote and policy conversion |
1. Score Every Conversation With Automated QA
Many insurance companies still run QA by hand. A reviewer listens to a handful of calls, fills in a scorecard, and moves on. Manual QA typically covers only 1-3% of customer interactions, which leaves most of the customer experience unseen.
Automated QA uses AI to score 100% of calls, chats, and emails against your own scorecard. That means you can spot trends like policy cancellations, claim delays, and billing frustrations as they emerge, and you can coach agents using real examples instead of a random sample. The shift is from checking boxes to understanding how customers feel and whether agent responses helped.
2. Give Agents Real-Time Help With AI Agent Assistance
Insurance work is complex. Coverage rules, exclusions, deductibles, and claim steps differ by product and state, and no agent can memorize all of it.
AI agent assist listens to a live call and shows the agent the next best step, the right policy answer, and any required disclosure, right on screen. With Level AI's Agent Assist, advisors give consistent, accurate information, which matters because customers often report hearing different answers from different agents about the same coverage. Better answers on the first try also reduce follow-up calls.
3. Personalize Service Using What You Already Know
Customers expect an insurer to know who they are. Basic personalization, like using a name, is no longer enough. Customers want an agent who already knows their policy, their open claim, and what they called about last week.
Technology can bring that context to the agent before the conversation starts. Past interactions, policy details, and sentiment from earlier calls can all appear in one view, so the customer does not have to explain the situation again. Personalization also means solving the request quickly, whether that is through automation or a human agent, because customer expectations for speed have risen.
4. Connect Service Across Every Channel
Customers move between phone, chat, email, text, and your app. The experience falls apart when each channel starts from scratch. A customer who explained a claim by chat should not have to repeat it on the phone.
Multimodal and omnichannel service means every channel shares the same customer record and the same quality standards. Score chat and email with the same rigor as voice calls, and make sure a handoff from one channel to another carries the full story. When your insurance digital experience feels like one conversation instead of five, customers notice.
5. Make Decisions With Data, Not Anecdotes
Insurance leaders often hear about problems through a few loud stories. A supervisor mentions an angry customer, and a process gets changed. But one story is not a trend.
When you analyze every conversation, you can validate known pain points with proof and bring that evidence to the business. Call center analytics also shows where systems and tools fail customers, so you stop blaming agent performance for problems that agents cannot fix. This is how an insurer's CX strategy moves from reacting to complaints to acting before they grow.
6. Listen to the Voice of the Customer
Voice of the customer (VoC) means the real words and feelings customers share about your company. Surveys capture only a small slice of it, because most customers never answer them. Calls capture the rest.
Voice of the customer insights analyze every conversation to show what customers want, what they struggle with, and which products or services help or hurt their experience. Instead of guessing why call volume spiked, you can see that customers are confused by a new billing notice or a claims status screen. This is the base for every other tactic on this list.
7. Improve First Call Resolution
First call resolution (FCR) is the share of customers whose issue is solved on the first contact. It is one of the clearest signs of a good experience, yet many insurers struggle to measure it. Without that number, it is hard to know why customers call back.
Start by tracking FCR across all calls, then look at the reasons behind repeat contacts. Common causes include agent knowledge gaps, unclear policy language, and product problems. These ways to improve first call resolution work best when the cause is known. Fixing it once removes hundreds of repeat calls.
8. Manage Customer Experience Proactively
Most insurance contact centers are reactive. A customer calls, and the team responds. Proactive service reverses that. You reach out first with a claim status update, a payment reminder, or a notice about a policy change, so the customer never has to chase you.
Conversation data shows you which events trigger the most calls. An AI virtual agent can then handle routine outreach and status questions at any hour, and hand off to a person when the situation needs judgment. Because digital claim updates are an area where many insurers fall short, as the J.D. Power findings above show, this is a strong place to start.
9. Speed Up Agent Training and Onboarding
New agents face a steep learning curve in insurance. They need to learn products, regulations, and systems, and they learn them while customers are waiting.
AI shortens that curve. Real-time guidance helps new agents handle live calls with support, and QA results show exactly which skills each person needs to practice. Our guide to reducing call center agent ramp time covers the approach in detail. Faster ramp means customers get a confident answer sooner, and new hires feel less lost.
10. Monitor Regulatory Compliance and Risk
Insurance is a regulated business. Agents must read required disclosures, handle sensitive personal data with care, and follow state rules. A missed step can create a compliance problem and a customer complaint at the same time.
AI can watch every conversation for compliance failures and privacy issues instead of a small sample. Regulatory compliance monitoring flags missed disclosures so supervisors can step in and correct them. Compliance and customer experience are linked, because customers trust an insurer that handles their data properly.
11. Identify Customer Pain Points Early
Pain points hide inside call volume. A confusing claim form, a broken login, or a billing notice written in dense language can each drive thousands of calls, and nobody sees it until complaints pile up.
When you analyze all calls, you can spot these themes in days. You can also tell whether customers are unhappy because of a policy itself or because of the service they received, which are very different problems with very different fixes. This clarity helps you decide where to spend time first.
12. Fix Broken Insurance Processes
Once you know where customers struggle, you can change the process behind it. That might mean simplifying a claims step, rewriting a letter, or fixing a self-service tool that sends people to the phone.
The strongest case for process change is evidence. Instead of saying a process feels broken, a leader can show how many calls it creates and what customers said about it. Undisputed data on customer pain points makes it far easier to win budget and attention from product, IT, and claims teams.
13. Improve Agent Productivity and Retention
Agent experience and customer experience are tied together. Agents who feel stressed and unsupported give worse service, and they leave. High turnover then means more new agents, more inconsistent answers, and a worse experience for customers.
AI helps on both ends. Agent assist reduces mental load during calls, and automation takes repetitive tasks off their plate. Pair this with agent coaching based on real conversations, so feedback is specific and fair. A leading credit union reduced agent burnout and improved member service with Level AI by moving from 2% QA coverage to 100% and giving agents live support. More tenured agents mean better service for customers.
14. Raise Customer Satisfaction and Retention
Retention is the result of everything above. Customers stay when claims are handled well, answers are consistent, and they do not have to call twice.
Survey scores alone miss most customers, because few respond. Inferred CSAT estimates satisfaction for every conversation, so you see the whole picture, not just the people who filled out a form. One global ticketing platform that moved from 2% review coverage to 100% conversation coverage reported its highest customer satisfaction in six years. The business is not insurance, but the lesson carries over: you cannot improve what you cannot see.
15. Analyze Agency Performance
Many insurers sell and serve through agencies, brokers, and partner call centers. Quality can vary a lot between them, and a customer judges your brand by the weakest one.
Using the same QA scorecard and the same conversation data across every agency lets you compare results fairly. You can see which agencies convert quotes into policies, which struggle with coverage explanations, and which need coaching. Those trends also point to ways to bring in more quotes and policies.
What Does This Look Like in Practice? An Insurance Provider Case Study
A provider of device insurance, warranty, and support services had large volumes of contact center data but little insight into what customers were really experiencing. Its QA scores relied on fixed rules and keywords, and results were bunched together, so it was hard to tell strong performance from weak.
After the company adopted Level AI, it used AI-powered QA scoring for more accurate scores, Voice of the Customer to surface trending pain points, and Agent Assist for live guidance. Average handle time dropped by 20%, and first call resolution rose by 15%. You can read the full insurance provider case study for details.
How Level AI Helps You Improve Insurance Customer Experience
Level AI improves customer experience in insurance by giving you a clear, data-based view of 100% of customer interactions. Many insurers rely on small manual QA samples, so they never get the full picture of why customers call. Level AI analyzes every conversation to find the true voice of the customer, whether the cause of dissatisfaction is a confusing policy, a broken digital tool, or a billing issue. It also tracks FCR and customer sentiment, and it separates agent-related issues from problems in the business itself, so leaders have facts instead of guesses.
Level AI also helps agents serve customers better in the moment. Agent Assist provides real-time, on-screen guidance during live calls, so agents can answer complex questions, stay compliant, and give consistent information about policies and procedures. That lowers stress and mental load, which helps reduce turnover and build a more experienced team. For the wider business, it turns anecdotes into numbers, so leaders can show exactly where customers struggle and change products, systems, and training with a measurable effect on satisfaction and retention.
1. How can we better understand why our customers are calling?
Many customers are looking for ways to understand the primary reasons for customer calls and identify the biggest pain points in the customer journey. They want to move beyond assumptions and gain data-driven insights into the "voice of the customer." This includes identifying the root cause of issues, whether they stem from agent knowledge gaps, product bugs, or broken systems and tools. By analyzing call data, companies can distinguish between customer dissatisfaction due to a policy versus the service they received. Customer sentiment analysis and a clear view of what voice of the customer means are good places to start.
2. How can we improve our Quality Assurance (QA) process to be more effective?
A common frustration is that traditional QA processes are manual, time-consuming, and only cover a small fraction of customer interactions (typically 1-3%). This provides a very limited and often incomplete picture of agent performance and customer experience. There is a strong desire to move towards 100% automated QA to get a comprehensive view of all interactions, identify trends, and provide more targeted coaching to agents. This would allow for a shift from simply checking boxes to understanding the nuances of customer sentiment and the effectiveness of agent responses. This guide on how to improve quality assurance in a call center walks through the steps.
3. How can we ensure our agents provide consistent and accurate information to customers?
Inconsistency in the information provided by agents is a significant concern that negatively impacts customer experience. Customers report hearing different things from different agents regarding processes, products, and coverages. This often stems from inadequate agent understanding or training. There is a clear need for tools that can monitor these conversations and provide real-time guidance and support to agents, ensuring that all customers receive the same, accurate information. See how real-time agent assist works on live calls.
4. How can we effectively measure First Call Resolution (FCR)?
Many organizations struggle to measure FCR and understand why customers have to call back. Without this data, it's difficult to identify the reasons for repeat calls, such as agent knowledge gaps or product issues. The ability to track FCR and analyze the reasons for follow-up calls is seen as a critical step in improving customer experience and operational efficiency. Teams that improve CSAT without increasing headcount often begin by measuring FCR.
5. How can AI help reduce agent stress and turnover?
High agent turnover is a significant challenge, and there's a recognized link between agent experience and customer experience. Agent assist technologies are seen as a way to reduce agent stress by providing real-time support and automating repetitive tasks. By making the agent's job easier and helping them navigate complex situations, companies can improve agent retention, which in turn leads to more tenured and experienced agents providing better service. Our roundup of the best insurance call center software compares tools built for these needs.


