Seven Peaks Insights

Data Analytics Strategies to Improve the Insurance Customer Experience


For businesses in the digital age, data might be more valuable than gold or oil, as raw materials that can be refined and used to develop successful products and services. This is especially true for the insurance business, where data analytics are becoming increasingly more important with the vast amounts of data needed to develop future insurance products and assess claims.

This article will discuss the importance of the data analysis process in how to improve insurance customer experiences (CX), including how to implement the right data strategy and corresponding business solutions.

How important is data analysis in insurance?

Insurance companies are trying to develop InsurTech, or Insurance Technology, to win the hearts of customers and drive business success.

We’ve previously covered how important InsurTech is to the insurance sector. In InsurTech, insurance data analysis is considered one of the important functions used to create a better and more personalized experience.

According to market research firm Mordor Intelligence, the global insurance data analytics market will grow to US$27 billion by 2029, with a compound annual growth rate (CAGR) of 15.90%, with Asia Pacific as the region that is anticipated to grow the fastest. Understandably, companies in this industry are willing to invest heavily in order to implement the latest findings and technologies in InsurTech. Read on to learn more about how they will do this, and why.

How insurance companies benefit from data analysis


Less insurance fraud

Insurance fraud is a prevalent issue in the industry. The National Insurance Crime Bureau (NICB) of the United States reveals that 10% of all insurance claims are fraudulent. This might originate from the insured party themselves, or in collusion with a third party, or from field staff conspiring with the insured to make fraudulent claims.

Because of this, insurance companies end up compensating fraudulently exaggerated claims. It causes the loss ratio and the loss adjustment expense ratio to increase unnecessarily. Having a data analytics system helps insurance companies search for information from various sources in the process of detecting fraud more quickly and accurately. This can be more efficient in reducing the rate of fraud than random inspections, or wasting time and resources manually searching for documents, as was done in the past.

More precise calculation of insurance premiums

Insurance companies can use customer data and statistics to analyze and evaluate individual risks. When combined with simulation models, this helps calculate insurance premiums that are most appropriate to the level of risk. Insurance premiums are more accurate and fair, and your company prevents unnecessary loss of reserves and resources.

A good data analysis system also helps automate more workflows. Gone are the days of guesswork and manual data entry that may lead to incorrect calculations. Insurance data analytics can help improve existing insurance policies to accurately reflect the actual risks, and make designing new insurance policies more efficient.

Additionally, implementing usage-based insurance (UBI) or charging insurance premiums based on actual usage can help customers feel they’re receiving more value for the insurance premiums they pay. Examples of UBI include using IoT devices with motion detection sensors, devices that detect engine ignition, and pairing devices with GPS tracking to calculate insurance premiums based on the driver’s mileage and behaviors. 

An example of data-empowered insurance in Thailand is Thaivivat, a leading auto insurance provider in Thailand, offers pay-per-use car insurance. Customers pay insurance premiums based on the actual time spent driving, by connecting the TVI Connect device to the car’s USB port. Another example is an innovative InsurTech product that lets customers pay insurance premiums according to the actual period of use of the vehicle through an application on your Smartphone by using the TVI Connect device which is powered by the car's USB port. Leading Thai companies like SCB and TIP Up2Mile also offer pay-per-mile insurance, which doesn’t require additional equipment. In pay-per-mile insurance, premiums are charged according to actual distance driven, such as every 5,000 km. or 10,000 km.

Faster claims processing

When information from insurance claims documentation and systems are recorded digitally, connected online, and are updated real-time via the cloud, it becomes much faster and easier to analyze data for claims processing. By eradicating the need for manual management, the entire claims process can be completed in a matter of minutes.

Lead generation

Analysis of customer and market data helps insurance companies with lead generation. This form of insurance data analysis identifies how to draw potential customers to read the details of your insurance policies, and make the decision to purchase your insurance products instead of your competitors'. Data analytics offers visibility of key metrics such as your customer acquisition cost (CAC), which prove invaluable to your marketing team when planning more impactful content and personalized marketing campaigns.

Better insurance customer experiences and greater satisfaction

When your company has insurance products that respond to the needs of your customers, they can be executed quickly, with fairer insurance premiums. This creates a better customer experience, increases satisfaction with the services provided, and has the potential to improve renewal rates, or encourage customers to buy additional insurance products in the future. It also increases the chances of referrals. All these factors drive your business’s success in the long run. 

These factors emphasize that collecting customer data – whether in person or on the cloud – and analyzing that data without a well-defined plan is no longer sufficient to keep up in the insurance sector. Here’s what effective data analysis should look like.


How to improve customer experience in insurance with data analysis processes



1. Make sure your team is prepared

  • Share knowledge, organize training for upskilling or reskilling, and strengthen relevant skills for employees to prepare your team for data analysis. Understand how to find insight from raw data and use various data analytics tools. McKinsey predicts that from 2016 to 2030, the insurance industry will see a 55% increased demand for people with technology skills. Underwriting staff, call center teams, people in your finance department, and even the sales department will inevitably have to improve their automation skills, as these may account for up to 70% of all required skills.

  • Find the right tools and solutions, such as data analysis platforms like Mixpanel, cloud solutions. Improve the functionality of websites, applications, and social media to support more efficient workflows.

2. Collect customer data

  • Collect customer data from every touchpoint, whether from insurance policies, claim history, contact with the call center, engagement from websites and social media.

  • Filter and integrate all data into a single source of truth in a data warehouse or data lake.

3. Analyze user behavior and customer preferences

  • Organize your customers through customer segmentation based on common characteristics and risks, then set a target persona for each group.

  • Analyze the needs and pain points of customers in each persona.

4. Use insights to create a customer journey

  • Invent innovative insurance products that are suitable for your target personas.

  • Create messaging and a tone of voice that are appropriate for each target persona.

  • Adapt your messaging into formats for all platforms, including emails, websites, social media posts, chatbots, or applications.

5. Keep track of your performance and continually improve

  • Follow up on how well your new customer journey is doing. Check KPIs from various indicators such as sales, policy renewal rates, customer satisfaction and feedback.

  • Continuously adjust your data strategies based on the results you get. Never stop improving, so you can maintain your existing customer base while attracting new customers that meet your goals.

We’re here to help you analyze your data.

Seven Peaks is not only a consultant in digital transformation. We also have deep experience working with insurance data analytics and leading InsurTech businesses both in Thailand and abroad. We are a trusted technology partner for global InsurTech companies, providing advanced data analytics solutions and implementations such as Mixpanel. We offer our clients complete data and end-to-end cloud solutions that elevate the quality of your data collection.

Reach out to us today!


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