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Latest Trends in Insurance Technology

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Today, the insurance industry is at a digital transformative phase to enhance the business models. There are few key areas we can expect insurers to embrace as they seek to create more automated, user-friendly processes in Insurance sector.

Use of automations and artificial intelligence  

Insurance industry is shifting towards exploring automation of more complex and risky processes rather using of traditional method, which is less effective in case of time and accuracy. Using of emerging technologies like Artificial Intelligence and Machine learning provide the scope of intelligent automation for analysis of huge amount of data generated by IoT and smart wearables devices. These Analysis and cross checking of data help understanding the better customer insights, fraud detections, claims verification and processing.

With the more refined automated technologies and capability of analysing more data, insurance companies like AIG started employing smart drone for automated property assessment and claims processing, which not only helps in accurate assessment but reduces the operational cost also.

Redefining of Insurance distributions

For better user experience, insurers have already generalized the new channel of distribution such as online research, comparison platforms and chatbot for better interaction and understanding, which already impacted in the market of personal insurances. The new direct distribution channels and online comparison platform for direct small insurances are likely to be more effective in coming days.

Companies like Allstate is already allowing small business owner to buy policies in just five minutes, or P2P platform like Gather giving the opportunity to small business owner to self insure and coverage is offered through a captive which is owned by the businesses it insures.Thus offering greater transparency and reducing cost in policies for these type of enterprise.

Insurance through value chain disaggregation

As the market is growing, the specialization in sectors is becoming more popular. As insurers move into advanced and extreme digital stages there is more use of data, automation, connectivity, ecosystem integration, new development methodologies, and a smarter use of IT resources. Some of these companies are providing customer interface with a unique value propositions, some companies provides tools for specialized software solutions for the insurers.

Companies like PolicyBazar provides insurance comparison and gives customized suggestions and recommendations based on the customer needs and choices, using their artificial intelligence.

Data analytics to improve profitability and better customer experience

The exponentially greater data availability and better analytical capability of softwares provide the base of making decision. Cross checking and analysing on the large amount of data coming from various unstructured resources such as social media real time data through various connected devices, helps in better risk management to drive greater profitability as well as better customer experience. Applying a combination of techniques such as predictive modeling, text mining, databases searches and exception reporting, insures are able to understand better customer insight, fraud analytics which help them in making insight driven strategies and risk mitigation strategies.

Sensors, Detectors, and Telematics  for building data

IoT or internet of things refers to the physical objects that are embedded with sensors, which gather information about specific objects and transmit it. These transmitted data are then analyzed as discussed earlier.

In insurances, using of IoT technologies is becoming more popular. In case of home insurances, smart homes is one of the fastest growing segment. Insurances companies are giving more discount on policies for an internet connected Home/Smart home.

Various wearable devices are also in demand as it enables life and health insurers to better engage with customers while obtaining real time insight into risk. Aditya Birla Health  Insurance is offering their policyholders health benefits and rewards for connecting their approved apps and wearable devices to their health app so they can track one’s activity.

Property and casualty insurance companies like AIG , are going to use smart drone for better property assessment.

Blockchain Technology for fraud detection

In coming days Distributed Ledger Technology(DLT) or Blockchain Technology is going to be leveraged across all sector including Insurance for its revolutionary way of sending, receiving and storing information in a secure and decentralized way. Using of Blockchain technology in insurance will improve the quality of service, increase in the volume of data from new data sources, automate claims, also will reduce the operational costs. It has the potential to ease out fraud detection and risk prevention as per a report from EY.

Once insurance and blockchain technology are interconnected, key business process like policy management and claims management are likely to transformed and new business model are expected to emerge using Blockchain.

Augmented Reality/Virtual Reality in Insurance

Though Augmented Reality is leveraged by many other sectors, like in social media or in gaming and other sectors, insurance sector still is limited to areas like marketing or training by simplifying complex explanations, meant for customers and employees. How about a 3D modeling and simulations help customers in making insurance claims easier and faster? Or how about before you go for the home insurance a simulation helps you pinpoint all the areas under insurance rather than reading the lengthy document?

There are big challenges ahead for insurers. With more changing technologies, executives will need to carefully consider the opportunities.

 

 

 

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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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