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How chatbots are changing the Insurance sector – Five examples

Insurance chatbots are the new buzzword ruling the insurance companies currently. The primary objective of a chatbot is to provide a faster and an efficient system for communication with the customers and streamline the tedious insurance tasks. The insurance sector is playing hard to automate their on-boarding, sales and training processes and make it available for the hand-held devices. But, the significant issues still lies with the sales force management where customers are a lot more aware, and the insurance products are more sophisticated and specific. A chatbot is the real game changer when it comes to salesforce management and revolutionizing the Insurance processes.

Here is a list of a few examples of how IT is transforming the insurance:

1. Virtual customer representative:

The typical scenario of the manual customer care system goes like putting the customer on hold with a constant background reminder that you need to wait for a few more minutes as our customer representative is on another call. It has always been a turn off for a customer because it is annoying, time-consuming and lacks efficiency. Insurance chatbots are here to put an end to these tiresome phone calls. Chatbot act as a virtual customer representative who is available at all the times. With the help of natural processing and artificial intelligence, they process the customer’s queries in just a few seconds with a personalized response. The total number of queries that can be handled by insurance chatbots is incomparable to the real customer care support.

2. Saving costs:

Business insider has predicted that implementation of insurance chatbots can save up to $12bn of labor costs.  Insurance firms often invest a massive amount of money in recruiting, training and mentoring a workforce to make it eligible for the insurance processes. Leveraging the benefits of AI, and natural language processing and developing the agent, and customer chatbots can help to save substantially on these costs.

3. Better understanding with the customers:

  When it comes to insurance then it is the most intimidating sector for the customers. 72% of the people are of the belief that they are not able to decipher the Insurance jargons used by insurance companies. It doesn’t give them a clear picture of what they are getting into when buying an insurance plan which makes them quite skeptical about investing in insurance. Chatbot is a great way to provide the straightforward answers to the customers and make them understand better.

4. Cut-down redundant processes:

The excessive paperwork involved with insurance lifecycle needs a dedicated workforce to manage it. Not just insurance agents but even the customers dread it. Chatbots together with AI make these processes much faster and easy that saves a lot of time. Though this is still in the nascent stages of development, it will be one of the key advantages of insurance chatbots in the future.

5. Providing customized solutions:

  Customers can get solutions tailored to their needs instantly through chatbot. They will need to provide information like their salary, savings, what are they looking for in the insurance plan, duration and an automated insurance solution based on those inputs is presented to them. Apart from that they can also set renewable insurance dates, access their documents online, set reminder with the help of Insurtech Chatbot implementation.

Though there has been a surge in the use of Chatbots for insurance, still it has a long way to go. InsureTech responsible for implementation of IT in insurance companies needs to come up with more effective solutions to make the customer engagement a lot more pleasant and user-friendly.

Start your chatbot journey with Mantra Labs today. Know more https://www.mantralabsglobal.com/

References:

https://www.streebo.com/blog/how-ai-powered-chatbots-changing-insurance-sector/

https://venturebeat.com/2018/06/19/why-insurance-companies-are-betting-big-on-ai-powered-chatbots/

https://www.streebo.com/blog/chatbot-insurance-industry-chatting-betting-high-on-smart-bots/

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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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