Meet ContextCheck: Our Open-Source Framework for LLM & RAG Testing! Check it out on Github!

in Blog

August 16, 2022

Why insurers should focus on hyper-personalized claims

Author:




Artur Haponik

CEO & Co-Founder


Reading time:




11 minutes


The current economic turbulence [1] coupled with increasing consumer demand for personalized services has revolutionized the insurance industry. Now more than ever, customers want data-driven conversations to help them learn about the most convenient insurance coverage options. They also want affordable coverage centered on their needs rather than being placed in a general category, which, in most cases, works against low-risk customers who end up paying higher premiums [2].

To keep up with changing market dynamics, insurance companies are embracing digital transformation to help them drive personalization innovations like data analytics and automation that increase conversion and customer satisfaction [3].

The doubling down on personalization efforts by insurance companies has given birth to the next chapter of insurance personalization – hyper-personalization. Below, we’ll look into how hyper-personalization can help insurance companies remain competitive in this cutthroat market and how you can implement it successfully.

What is hyper-personalization in insurance?

Personalization is not a new concept in the insurance industry. Insurance companies have been offering tailored insurance policies based on a measurement of risk for decades. Personalization also transcends into marketing, where insurers use customer data to recommend certain products to specific customers.

Hyper-personalization takes it even further by incorporating a broader set of data and using it to create an in-depth, dynamic understanding of the consumer. Therefore, hyper-personalization in insurance is the timely, relevant engagement of customers across multiple channels throughout the customers’ lifecycle. Insurance companies achieve this by leveraging different technologies like AI, analytics, and automation to provide targeted, dynamic, and personalized customer experience [4].

Role of data in hyper-personalization of insurance

Businesses need to focus on data to provide a hyper-personalized experience to their customers. Data can help insurers develop a deeper understanding of their customers, simplify customer interactions, and ultimately provide better services.

When it comes to providing personalized insurance experiences, the data used goes beyond general customer preferences and demographics. It is about analyzing customer profiles through their purchasing histories.

To achieve this, insurers need to unify data from multiple sources and devices like browsing history, social media, consumer trends, purchase history, and data from IoT devices to create a unified, personalized repository [5].

personalization, meeting, analysis

A good example of a company doing this to great effect is Intuit [6]. Thanks to its accounting software, QuickBooks, the company’s insurance arm has access to a vast array of customer data that it can use to provide personalized business insurance.

By leveraging a host of consumer data, insurance companies don’t have to ask too many questions during the onboarding process as they already have this information. Intuit, for example, can access factual information like a business’s payment information, address, and transactional data like business revenue right from its accounting software, QuickBooks.

Insurance companies can also use analytics software to draw comparisons from similar businesses. This way, they gain insights into where a company may lack sufficient coverage and areas where they might be paying much more than they have to. The result is data-driven pricing models based on factual behavioral and transactional information aggregated from various internal and public data sources.

Read more about Big data analytics in the insurance sector

The biggest challenges to hyper-personalization

Insurance companies often have to deal with challenging market conditions, evolving customer needs, and extreme competitiveness from their peers in the industry [7]. That said, data disparity is perhaps the biggest challenge facing hyper-personalization in insurance.
Insurance companies work with lots of data, ranging from historical quotes and claims, active policy data, marketing preferences, web analytics, as well as insights derived from external third-party sources and digital engagement.

Unfortunately, most of this data isn’t aggregated and may require quite a bit of manual processing before it can provide any helpful insights. The result is an increased likelihood of time-consuming analytics, data silos, and low-quality insights.

insights, laptop, phone,hyper-personalization

Additionally, this data disconnect means that departments like claim handlers, contact center agents, and underwriters often have different analytical views of the same customer. Since hyper-personalization requires speedy processing and high-quality data, insurance companies must focus on eliminating data disparity during the implementation process to avoid the challenges it presents down the line.

How to implement hyper-personalization in insurance

When it comes to implementing hyper-personalization in insurance, execution is everything. Here are a few strategies to help you create a more data-driven, personalized customer experience.

Invest in data assets

To deliver hyper-personalized insurance services, you need to have a deep understanding of your customers. Basically, the more informed a company is, the better able it is to anticipate its customers’ needs and cater to them.

Therefore, you need to create a data pipeline [8] to deliver consumer insights. You also need to break down core data activities into discrete building blocks that can be utilized across all departments in the organization. This includes everything from capturing proprietary information from various sources, such as customer account data, data from the CRM, claims and fraud data, web and marketing data, and household data.

house, currency

Since this data is mainly fragmented and in different formats, you also need a data infrastructure to consolidate, augment, and store collected data to derive useful insights into customer profiles. Graph databases are some of the most effective ways to achieve this [9]. These databases provide a quick and effective way to build a 360-degree view of individual customer profiles. And since customer data is fluid, your data pipeline should be able to proactively collect, manage, update, and secure customer data. Therefore, it is vital to create data assets that facilitate clear data collection, storage, and analysis.

Deploy technology specialized for personalized insurance offers

Data is the lifeblood of hyper-personalization in insurance. Technologies like AI and machine learning utilize customer data to guide real-time decision-making. When a customer applies for a claim or when calculating insurance premiums for new customers, these technologies ingest data, identify signals that indicate the customer’s profiles, then use the customer’s data to create a 360-degree view.

However, for these actions to be effectively proactive, insurers must also consider their business policy as well as permissions granted by the customer. Since all these actions occur in near real-time, they must manage their data efficiently and evaluate their library of actions for maximum effectiveness.

All this is achieved through tailored technologies that come in many forms, including real-time interaction and orchestration engines. But, despite the seemingly complex nature of these technologies, proper deployment can help orchestrate recommendations across different areas, including sales, marketing, and service delivery in terms of underwriting and claims.

Prioritize customer needs over product sales

Insurers, like any other business, are primarily centered around selling individual products in lieu of focusing on customer needs. Or at least that’s what it was before personalization became a major focus. The insurance industry has changed in this regard as hyper-personalization requires insurers to think from the customer’s perspective in all elements of the business, from sales and marketing and product development to underwriting processes.

Traditionally, marketing responsibilities in most insurance companies were highly decentralized. The result was that customers got a different approach when they used different channels such as websites and in-person conversations with customer support representatives. Since each marketing channel was focused on the next-best action (NBA) based on a narrow view, this resulted in customers getting offers that, in most cases, were not based on their best interests.

Insurance companies seeking to implement hyper-personalization must take a different approach by considering the customers’ best interests, aligning NBAs with customer needs, and reconciling competing departments so they can focus on one goal – putting the customer first.

Personalize your marketing efforts

Besides helping you provide personalized insurance offers, the data you collect can also help shape your marketing efforts. You can achieve this by segmenting your target audience based on their unique characteristics. This way, you are better able to send them offers that suit them through preferable channels.

Say, for example, you notice that customers in your young adult segment spend most of their time interacting on the web or social media. In this case, you can prioritize your marketing efforts on these channels.

marketing, team, meeting

In the same measure, if another group prefers calling your contact center and discussing your offers directly with your agents, you can invest in intelligent call analytics, so your customer service teams can provide a hyper-personalized experience.

Develop a personalized cross-channel experience

Hyper-personalized insurance relies heavily on data collected from multiple sources like IoT devices and social media. Therefore, it is imperative to ensure a seamless customer experience across all channels. Whether customers interact with your business through a business app, social media, or over the phone, they should experience the same level of personalization, regardless of the communication channel.

Provide real-time hyper-personalized interactions and responses

Customer expectations in the insurance industry transcend service delivery. Communication also plays a major role in providing a hyper-personalized experience. According to statistics, 75% of customers expect companies to respond to their social media posts within 24 hours [10]. Additionally, 79% of customers prefer using the live chat feature on the website over social media due to the quick response time [11].

This means that you not only have to respond to comments and queries promptly, but you also need to do it with a tailored approach.

Benefits of hyper-personalization in insurance

Improved customer experience

Hyper-personalization isn’t just in the insurance industry. Several streaming platforms and giant retailers like Netflix and amazon gather and aggregate real-time user data to gain incredible awareness of their customers’ preferences. This way, they can better provide their customers with tailored services and products at a scale that meets their needs.

There are numerous technology solutions and processes that enable businesses to collect and leverage data to boost customer experience and ultimately drive sales. Insurers can, for example, leverage cloud-based solutions to provide the same tailored, personalized experience across the insurance claims process.

smile, customer experience, hyper-personalization

By implementing hyper-personalization, they can make their customers feel known and understood. Additionally, by automating many of the relevant processes, insurers can show their customers that they are willing and able to put them at the center of everything they do.

Improving the sales process

Hyper-personalized insurance can benefit sales initiatives in numerous ways. Many insurance customers are willing to give you more access to their personal data in exchange for lower premiums. This provides greater insights into customer behavior and preferences, which in turn, significantly improves targeted marketing campaigns and initiatives. It also helps insurance companies provide customers with the services they need and develop products they want.

Creating happier employees through optimized sales processes

When employees have the knowledge and resources needed to do their jobs, they are likely to have higher morale. This, in turn, helps them provide a better customer experience. The past few decades have seen a significant rise in health insurance claims. These claims can be incredibly challenging to both customers and employees.

Hyper-personalization can make this process more efficient by giving employees the resources they need to process these claims. It also means less effort on the customer’s end. Additionally, the insurance adjusters can gather relevant data more efficiently through a technological approach rather than relying on one-way communication and paper forms. The result is less time spent gathering information, so employees can focus on delivering better customer service.

What’s the next step in insurance hyper-personalization?

We’re likely to see insurance companies leveraging existing technologies to engage customers with tailored offers at the right time through the proper channels. The abundance of collected customer data will also help insurers respond to changes in consumer behavior more efficiently.

Insurance industry leaders will also be able to build up a 360-degree view of their customers’ needs, preferences, and pain points to improve customer satisfaction throughout the insured’s’ lifecycle. It is also likely that insurers will continue to explore how new technologies and data sources can help them engage customers more effectively as well as improve their understanding of risk.

Final thoughts

Insurance companies have been delivering personalized services for decades. But, as consumer demands for personalized services increase, they’ve had to change their business approach to deliver hyper-personalized services. With the inception of this ‘new’ strategy, the industry is expected to change drastically to a more customer-focused approach in marketing, underwriting, and claims processing.

References

[1] Tandonline. com. The Implications of the Financial Crisis to the Insurance Industry. URL:  https://www.tandfonline.com/doi/pdf/10.1080/1331677X.2010.11517417. Accessed July 23, 2022
[2] Schemeserve. com. 5 Things Customers Want From Insurers. URL: https://www.schemeserve.com/5-customers-insurers/. Accessed July 23, 2022
[3] Hitachi-solutions.com. Insurance-Digital Transformation. URL: https://global.hitachi-solutions.com/blog/insurance-digital-transformation/. Accessed July 23, 2022
[4] Earnix.com. The Age of Insurance Personalization. URL: https://earnix.com/wp-content/uploads/2019/11/The-Age-of-Insurance-Personalization-1.pdf. Accessed July 23, 2022
[5] Recosenselabs.medium. What is Unified Data Repository and Why Do You Need It. URL:https://bit.ly/3Bjr6LO. Accessed July 23, 2022
[6] Intuit.com. URL: https://www.intuit.com/. Accessed July 23, 2022
[7] Insurance-analyzer-info.com. 6 Biggest Challenges for Insurance Companies. URL: http://insurance-analyzer-info.com/6-biggest-challenges-for-insurance-companies/. Accessed July 23, 2022
[8] Stitchdata.com. Data Pipeline Architecture. URL: https://www.stitchdata.com/resources/data-pipeline-architecture. Accessed July 23, 2022
[9] Aws. Amazon. Nosql. URL: https://aws.amazon.com/nosql/graph/. Accessed July 23, 2022
[10] Hubspot.com. Social Media Response Time. URL: https://blog.hubspot.com/service/social-media-response-time. Accessed July 23, 2022
[11] Hubspot.com. Social Media Response Time. URL: https://bit.ly/3b5sJ5f. Accessed July 23, 2022



Category:


Data Analytics