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5 InsurTech Trends for 2023

3 minutes read

For 2023, we believe that InsurTech will be used to supplement the rising concerns of inflation, arrested economic development, and heavily burdened pension schemes by catering to customers with greater attention to detail. 

# Digitally Enabled CX 

Insurance models in the present context have become bloated and complicated to the point where customers feel alienated. Customer needs are also converging across a wide range of areas: health, retirement, and investment management, to name a few. Simplifying the existing delivery model is key, and one such model that is likely to emerge is that of being a ‘distribution specialist’.

These firms are predominantly client-centric and extremely capital-light as they do not take on balance sheet risks. These firms will invest heavily in client-facing technology, and those that curate a delectable insurance discovery and delivery experience will have a huge leg-up over their peers. These developments are in line with Gartner’s predictions for the InsurTech industry, where digitally enabled CX is listed as a key success factor for InsurTech in the coming years.

# InsurTech native Telematics

Analysts and experts alike have been citing usage-based insurance programs as the next big thing in the world of insurance for nearly two years now. But how effective can usage-based programs be if they rely entirely on the customer to predict their decisions and make purchases accordingly? 

This is where telematics systems come in. As cars become increasingly ‘smart’, it will become easier and cheaper to integrate telematics into the insurance plan to implement a real-time ‘pay as you go’ plan. Telematics will be crucial for developing markets in Asia as societies become increasingly digitized and people start to get comfortable with the idea of insuring themselves and their vehicles separately. 

# Algorithmic Risk Assessments

Research has shown that with the application of machine learning models to the risk assessment strategies employed by risk analysts, Insurance companies can decrease the time taken to evaluate customer profiles by allowing faster servicing and thereby leading to greater customer loyalty and satisfaction. This will allow companies to process claims swiftly and accurately, thereby allowing risk assessment professionals to focus on refining their models.

Some firms have already demonstrated success by incorporating AI into their workflows. Lemonade, an insurance company that is ‘digital first’ has seen massive success by using AI to facilitate claims, quotes, and personalizing prices and interactions with individual customers.

# Broadening capabilities in the Metaverse

With over $25Bn dollars having been invested into it by Facebook alone, Metaverse is here to stay for the long run. And for Insurers, the possibilities offered by metaverse are hard to ignore. This means they finally have a tool to combine the efficiencies of AI-powered chatbots, with the warmth of face-to-face interactions. Internal training, conducting sales pitches, and using NFTs to verify personal documents are some of the most highly anticipated use cases.

Max Life insurance, a leading Indian insurance player has already started to think about how best to use the metaverse to boost employee engagement and morale.

# Disruptors will strive to stay afloat

Much of what made new-age insurers attractive to customers was the way they structured themselves (tech-first, expedited claims, etc.) that were antithetical to running an insurance business at scale. Kimberly Harris-Ferrante of Gartner predicts that the coming year will see a lot of new Insurtechs pivot to more traditional operating models, with the successful ones being acquired and the others being forced to shut shop.

Some have already closed down, such as GoBear (Asia Pacific) citing increasing regulatory and compliance pressures as the primary reason. Other examples include Kinsu (from Latin America) and Coverly for small businesses.

Conclusion: 

2023 is likely to see the beginning of the final stretch of digital transformation in the insurance industry as many have already caught on to the basics that are required to run a robust digitally-enabled sales and servicing operation. Conservatism will go hand-in-hand with novel, disruptive technologies as incumbents will lap up all existing software capabilities to bolster direct distribution, simpler delivery mechanisms, and a narrower focus on servicing the customer. Expect greater use of APIs, hybrid cloud architectures, and ‘headless tech’ in the coming year.

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10 Analytics Tools to Guide Data-Driven Design

Analytics are essential for informing website redesigns since they offer insightful data on user behavior, website performance, and areas that may be improved. Here is a list of frequently used analytics tools to guide data-driven design that can be applied at different stages of the website redesign process. 

Analytics Tools to Guide Data-Driven Design

1. Google Analytics:

Use case scenario: Website Audit, Research, Analysis, and Technical Assessment
Usage: Find popular sites, entry/exit points, and metrics related to user engagement by analyzing traffic sources, user demographics, and behavior flow. Recognize regions of friction or pain points by understanding user journeys. Evaluate the performance of your website, taking note of conversion rates, bounce rates, and page load times.

2. Hotjar:

Use case scenario: Research, Analysis, Heat Maps, User Experience Evaluation
Usage: Use session recordings, user surveys, and heatmaps to learn more about how people interact with the website. Determine the high and low engagement regions and any usability problems, including unclear navigation or form abandonment. Utilizing behavior analysis and feedback, ascertain the intentions and preferences of users.

3. Crazy Egg:
Use case scenario: Website Audit, Research, Analysis
Usage: Like Hotjar, with Crazy Egg, you can create heatmaps, scrollmaps, and clickmaps to show how users interact with the various website elements. Determine trends, patterns, and areas of interest in user behaviour. To evaluate various design aspects and gauge their effect on user engagement and conversions, utilize A/B testing functionalities.

4. SEMrush:

Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct keyword research to identify relevant search terms and phrases related to the website’s content and industry. Analyze competitor websites to understand their SEO strategies and identify opportunities for improvement. Monitor website rankings, backlinks, and organic traffic to track the effectiveness of SEO efforts.

5. Similarweb:
Use case
scenario: Research, Website Traffic, and Demography, Competitor Analysis
Usage: By offering insights into the traffic sources, audience demographics, and engagement metrics of competitors, Similarweb facilitates website redesigns. It influences marketing tactics, SEO optimization, content development, and decision-making processes by pointing out areas for growth and providing guidance. During the research and analysis stage, use Similarweb data to benchmark against competitors and guide design decisions.

6. Moz:
Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct website audits in order to find technical SEO problems like missing meta tags, duplicate content, and broken links. Keep an eye on a website’s indexability and crawlability to make sure search engines can access and comprehend its material. To find and reject backlinks that are spammy or of poor quality, use link analysis tools.

7. Ahrefs:
Use case scenario:
Research, Analysis, SEO Optimization

Usage: Examine the backlink profiles of your rivals to find any gaps in your own backlink portfolio and possible prospects for link-building. Examine the performance of your content to find the most popular pages and subjects that appeal to your target market. Track social media activity and brand mentions to gain insight into your online reputation and presence.

8. Google Search Console:

Use case scenario: Technical Assessment, SEO Optimization
Usage: Monitor website indexing status, crawl errors, and security issues reported by Google. Submit XML sitemaps and individual URLs for indexing. Identify and fix mobile usability issues, structured data errors, and manual actions that may affect search engine visibility.

9. Adobe Analytics:
Use case scenario:
Website Audit, Research, Analysis,
Usage: Track user interactions across multiple channels and touchpoints, including websites, mobile apps, and offline interactions. Segment users based on demographics, behavior, and lifecycle stage to personalize marketing efforts and improve user experience. Utilize advanced analytics features such as path analysis, cohort analysis, and predictive analytics to uncover actionable insights.

10. Google Trends:

Use case scenario: Content Strategy, Keyword Research, User Intent Analysis
Usage: For competitor analysis, user intent analysis, and keyword research, Google Trends is used in website redesigns. It helps in content strategy, seasonal planning, SEO optimization, and strategic decision-making. It directs the production of user-centric content, increasing traffic and engagement, by spotting trends and insights.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UXR and Product Design.

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