Article | July 20, 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.
Article | July 19, 2022
Insurers of the future will play more of a risk avoidance role and less of a risk mitigation one.
The seemingly effective yet simple ideas of Netflix, Uber, Ola, Amazon, and many other ideas have forever transformed their industry segments. Digital transformation in the insurance industry is embraced in various ways to address the complex challenges posed by consumers, regulatory, and digital landscapes.
To keep up with insureds' demands, insurers have had to digitize various aspects of their operations. Any company that wants to stay competitive in today's market must meet customers where and when they need it. Insurance's digital transformation, powered by artificial intelligence, machine learning, predictive analytics, mobile services, live chat, and other technologies, enables insurers to do just that and will continue to change the industry for years.
Insurance Companies to Look at Value Chain through a Digital Lens:
Gain First-Mover Advantage:
Product introduction to gain a potentially sustainable competitive advantage. To achieve the first-mover advantage, the insurer should have two crucial capabilities: the ability to pinpoint unmet customer needs to guide product development and quickly adapt existing products to market forces.
Reduce IT costs to fund innovation:
When insurance companies refactor monolithic applications into modular micro services, application maintenance costs are reduced.
Grow revenue by differentiating the customer journey:
Electronic document capture and processing, robotic process automation (RPA), and robo-advisors improve serviceability and help businesses gain a competitive advantage.
Despite market participants' claims that the insurance industry was not an early adopter of digital transformation, new players, business models, and demanding customers are forcing the industry to embrace digital technologies. As a result, the global insurance market is expected to grow by 45% between 2022 and 2025.
Modern digital engineering does not occur in a vacuum; new products must be compatible with existing technologies and processes. Ascertain that the development team understands legacy insurance applications and the data required to integrate them with new, digitally engineered products.
Automobile Insurance, Insurance Technology
Article | December 19, 2022
When building a practical framework, AI holds tremendous potential for insurers. Insurance companies can use AI to make better business decisions and provide differentiated customer experiences. To take advantage of AI, insurers need to know and clear the air about what is possible to do with AI.
Insurance with AI: Understand, Learn & Respond
Here are the ways insurers must use AI in their workforce and build a workable model.
Language: Insurers can use natural language processing using AI to extract legacy unstructured data and convert it into structured data. As a result, organizations can extract information and automatically classify it into different sections. In addition, AI can even learn and guide users to make decisions using machine learning and curtail errors.
Management: AI has emerged as a game-changer in managing the workforce, risks, and insurance functionalities and augmenting flawless products and services. While we talk about workforce management, AI puts tasks in one place, organizes them, and stores them under a data-proof model. So, no more scattered documents and pilling of files! AI is here, and it will transform and respond to businesses more efficiently with solution-driven aspects.
Efficiency: Businesses need to be proactive by having a smart workforce that adds efficiency. Before, the insurance sector had a sloppy work platform. But now, with the passing of time, they need to overcome and be more efficient at work. Using AI in your business will save a lot of time, energy and money. It will lead to faster processes that are error-free, accurate, and predictive, encourage crystal clear communication, and have fewer chances of fraud.
Insights on AI’s Role in Insurance
Existing and start-up insurance businesses will be fortified with the help of AI use cases. Let’s get some insights into AI's potential for businesses.
The global AI market is estimated to grow at a CAGR of 42.2% to $733.7 billion by 2027. The inclusion of AI in insurance records a growth of 56% until 2021.
AI has the potential to save insurance companies up to $390 billion by 2023.
In 2021, more than 40% of insurance businesses increased their expenditure on AI use cases and projects.
These statistics show that AI in insurance is only going to get bigger. Investments in AI are high on the priority lists of decision-makers.
The Futuristic Hold
The insurance industry is under enormous pressure in terms of digital transformation. The rate of transformation is consistently accelerating. This paints the future of the insurance industry with AI to be more progressive with improved products and services, which will eventually host numerous opportunities for exponential expansion and reach globally.
Article | April 17, 2020
Kennedy's Elizabeth Bardsley discusses the risks brokers need to be aware of as more and more professionals work from home as a result of the coronavirus pandemic. As the insurance industry continues to grapple with the Covid-19 pandemic, many have begun to give thought to what lasting changes will stay with us once the crisis has passed. For example, attitudes towards flexible working are expected to permanently change as more and more professionals work from home. And in a similar vein, we are likely to see a significant impact on the popularity of cyber and digital liability policies.