Article | August 9, 2022
A quick Google Trends search on data reveals that data analytics, data and analytics, data analysis, and predictive analytics have steadily grown in popularity among businesses across industries.
These terms peaked when business leaders searched for ways to increase ROI and reduce business costs and tech-based investments. The insurance industry is amongst the industries actively leveraging data analytics.
The rising importance of analytics in insurance has made CMOS take note too. As agility became more important in the insurance industry, more than 85% of global businesses shifted to a data-driven model.
The purpose of taking you back is to emphasize that, as a CMO, now you need to churn accurate data and turn it into relevant information. This is a necessary model to practice to make the right decisions or will improve the decision-making process.
Without data analytics, you are deciding in a void, and that’s not considered good practice. Forrester reports that 41% of insurance companies faced challenges in extracting data and making decisions based on it in 2020.
Take a look at how and what you can do with insurance analytics to cater to better insights into your decision-making process and, finally, ROI generation.
Bring Data to These Key Levels of Departments
Analytics in insurance raises the bar in terms of marketing. As you know, marketing results frequently fluctuate, making data insights challenging to capture. CMOS who base their decisions solely on outcomes usually loses sight of making sound decisions due to unstructured data.
Therefore, it is essential to have an aligned platform for data analysis in insurance. To begin with, marketers must understand the various types of data analytics available. Most insurance marketers employ descriptive, predictive, and prescriptive analytics, among others. This will assist them in strategizing based on continuous data insights from various sources for any given initiative.
Sales leaders can also improve how they spend their time by using data analytics to create more accurate sales forecasts. However, the question is, how will they do it efficiently?
CRM software is the answer and solution to them. The software performs best because of its analytical capabilities in combination with data visualization, particularly predictive functions. It generates enormous amounts of data on customer interactions, which can then be used to inform decisions. You can assemble relevant data and use it to make some decisions, such as:
Acquisition and management of leads
Sales funnel optimization
There is enormous value in optimizing productive data by focusing on prospects likely to become loyal customers.
Utilizing data analytics in insurance boosts insurance operations. Small changes help to align a wide range of core processes. You can access data obtained from operations, observe key aspects of the overall processes, and make appropriate decisions. A targeted, timely, and data-driven approach will help you make decisions about these key functions, which can lead to business growth in the long run.
Bain's research in 2019 reports that seventy insurers were polled. They say data analytics will reach 58% in the marketing funnel and 45% in business operations.
Begin with Overcoming Barriers to your Decision-Making Process
Use Data to Identify Customer Patterns
Information from data can identify patterns. As mentioned above in the sales section, CRM's predictive modelling and the popular Google Analytics' descriptive overview are the two best platforms for identifying customer patterns.
What is the best way to get pertinent data? Data mining is the answer to it. Do you want to know about it? Then read data mining for pattern evaluation now!
As a CMO, you're probably aware that behavioral patterns are highly predictable and can sometimes result in unsatisfactory outcomes. This occurs when you are unable to obtain relevant data. And you end up performing ineffective marketing activities. To assist you in overcoming it, an AI-enabled platform can reduce the level of effort and provide the necessary data to study your customers' patterns in real-time. This is how you will notice a significant increase in sales.
According to research by McKinsey and Company, automation saves 43% of insurance employees’ time.
Segmenting Sales Plans
Following the establishment of your customers' patterns, segmenting the insurance sales plan is a necessary step. In this process, analytics provide detailed information about customers, allowing you to make decisions about sales functionalities. This will undoubtedly reduce the time, energy, and effort you previously spent.
Accurate customer segmentation and sales forecasting can also help tailor marketing efforts, improve the sales funnel, and keep sales strategies in check.
When Media 7 contacted Vishal Srivastava, Vice President (Model Validation) at Citi, here’s what he said about data segmentation through data analytics.
CMOs must ensure that adequate data quality checks have been performed, The goal is to ensure a scientific approach to data segmentation, sampling methodology, and data outliers, which can significantly impact revenue forecasts.”
Pricing & Savings
Analytics in insurance marketing can help CMOs make cost-cutting decisions and become more cost-effective in marketing efforts. It can set price ranges based on historical, current, and predictive performance. Also, analytics will help you figure out how to price things in the future, which will be good for ROI.
Keep Improving with Data to Stay Abreast with The Decision-Making Process
Better data organization in your business boosts productivity."
Warren Buffett, an American business magnate, investor, and philanthropist.
This phase is best suited to the current business environment. Implementing data analytics in insurance now will open up tremendous opportunities in the future. To make the most of them, you, as a CMO, must stick to a data-driven model for marketing actions.
Aside from that, it appears that the data analytics you select for your business must be capable of informing and driving performance. Performances ranging from risk assessment to sales forecasting and a plethora of actionable insights assist businesses in thriving.
Frequently Asked Question
How are data analytics used in insurance companies?
Data analytics empowers insurers to optimize each function and also assess risks. It also identifies trustworthy customers, which further boosts engagement.
What does data analytics mean in insurance?
Data analytics empowers insurance professionals by providing them with the business intelligence to understand their customers better, build better products and services, and thus, boost business growth.
How are insurance companies using data?
Insurers can use data to gain insights from customers’ profiles. They can review their history, behavioral pattern, and marketing needs to develop strategies and provide marketing services.
Automobile Insurance, Insurance Technology
Article | December 19, 2022
The blockchain has penetrated the mainstream. We predicted this in our 2019 article “Blockchain-as-a-Service: the Accelerator for Blockchain Adoption” where we talked about the technology's ease of integration. Companies can seamlessly adopt blockchain technologies by referring to existing use cases like smart contracts, data authentication, and asset management. They can also take advantage of open-source materials.
With the blockchain's accessibility on top of its formidable qualities, it’s no surprise that the digital ledger system is being integrated into every industry–from banking and healthcare to gaming and cybersecurity. As a cornerstone of the rise of financial technology or fintech, another industry it’s now serving is auto insurance. Here’s how the blockchain is revolutionizing the auto insurance industry:
Benefits of the blockchain in auto insurance
Multiple back-and-forths can slow down the manual processing of both insurance contracts and filed claims. Blockchain-based tools can speed this up by accessing necessary information through the data network. Insurers can easily access and verify the personally-identifiable information (PII) required for insurance contracts via the blockchain, as well. This means no lengthy coordination with other parties, shorter queuing time, and less paperwork.
Moreover, the blockchain helps those who buy auto insurance worry less about their PII being used by malicious individuals and organizations. Monash University asserts blockchain security effectiveness by pointing out how its design can alert any network of even the most minor changes to the data it contains. This is because blocks containing data are marked with hashes–input strings of computation characters–that become invalid when information is modified. When hashes become invalid, the network is notified. With such a prompt and responsive alert system, insurance agencies can easily detect hacking activities to protect sensitive data.
Blockchain applications in auto insurance
The most significant benefit of the blockchain’s application in auto insurance arguably lies in optimizing property and casualty (P&C) insurance verification processes. Sound Dollar defines property and casualty insurance as coverage for any damage the possessions stipulated in your contract incurs. Blockchain-based tools, like smart contracts, can immediately gather relevant information from an insurer's network to verify damaged possessions. It can also identify which ones are covered by your insurance contract. This streamlined verification process saves insurers billions of dollars in operational costs and makes filing a claim much easier for the client.
The blockchain can also be used to minimize and prevent fraud. Some of the best blockchain-based tools can identify whether an individual claims payouts from multiple insurers. These tools cross-check PII and non-PII with salient information from claims filed elsewhere to check for similarities. Moreover, the Insurance Innovation Reporter found that advancements in anti-fraud blockchain technology can detect third-party helpers, such as garages and brokers. This enables insurers to expand their data on fraudulent networks and prevent future cases of fraud.
Challenges to full implementation of the blockchain in auto insurance
Before full-on integration, developers and businesses have to address data integrity. While blockchain data cannot be edited, it does not ascertain that encoded information is true. This means data has to be verified before it's encoded on the blockchain. Blockchain-based technology is also expected to become more expensive in the coming years. As it becomes mainstream, demand for the technology and relevant development research will further drive operation and maintenance costs upwards.
There is still much work to be done if the auto insurance industry wishes to fully integrate the blockchain into its workflows. But with the long-term benefits it brings, insurers and clients alike will undoubtedly look to blockchain-based technology for improved services and a better overall experience.
Article | July 20, 2022
Artificial intelligence (AI) has changed the insurance industry – and customer service is no exception. One of the most common forms of AI are the use of chatbots, which Forbes defines as “software functionality that is designed to receive conversational input through text of voice and then generate a response that is also in natural language.” In other words, instead of interacting with a human, you’re “chatting” with a bot that’s programmed to understand your questions and direct you to the right place.
Article | April 13, 2020
Amid COVID-19, banks began offering mortgage deferrals and slashing credit card interest rates in half for cardholders who need relief. Home and auto insurance companies COVID-19 plans are now being released. How will this impact your insurance right now? How can you save on insurance during COVID-19, while making sure to stay protected?