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The ‘Digital’ Insurance Broker

3 minutes, 24 seconds read

The technological advancements brought forth by insurtech will soon become routine for brokerage offices within the next few years. Digital-first approaches have finally trickled down, turning ripe for adoption for this major distribution channel. However, broker adoption has still not caught pace with their agency counterparts.

According to a 2019 report surveying independent insurance brokers across the US, Canada & the UK, the average for digital technology adoption at an independent brokerage is only around 43%, even though nearly 96% of them (almost universally) use a broker management system for indispensable day-to-day operations. Interestingly, over 80% don’t offer any form of ‘mobile apps’ or ‘self-service portals’ for customers or staff. 

Today’s insurance customers are younger and prefer digital over traditional channels — leaving a lot of unmet gaps in the value chain. The report also identified key areas where adoption is growing — such as capabilities in workflow process management, document management, sales opportunities & prospect tracking, one system-one view visibility into all departments among others. For example, the downside to not outfitting your broker operation with employee mobility tools alone translates to over 30% reduction in staff productivity. 

Today’s insurance customers are younger and prefer digital over traditional channels

Meanwhile, brokers are facing a whole new set of challenges — Insurance is being built for digital and the audience is changing. Gen Z and Millennials will form the core of their target demographic. A fully online brokerage can benefit these potential customers through simple end-to-end policy administration and by fine-tuning the customer journey.

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Join our Webinar — AI for Data-driven Insurers: Challenges, Opportunities & the Way Forward hosted by our CEO, Parag Sharma as he addresses Insurance business leaders and decision-makers on April 14, 2020.

While brokers are not involved in the manufacture of insurance products or the evaluation of risk, several other value chain functions are being performed through brokers now — of which managing the customer relationship is pivotal. 

There is a lot of data across the lifecycle to look at, which necessitates the need for advanced analytics in order maximize the opportunities to up/cross-sell. At present, data analytics is widely under-utilized among most insurance brokers leaving them blindsided to customer needs.

The Case for a ‘Digital’ Brokerage

A digital broker business is built on these foundational blocks — robust broker management system, seamless mobility tools for employees, insurer connectedness, self-service portals, smart customer apps, advanced data analytics and the cloud. 

The case for digital brokerage

Taking the entire business model online requires the right business advisory and technical roadmap, without which the transformation can leave you with unwarranted gaps in the operating structure. This is where Artificial Intelligence can play a critical role in securing brokerages to be future-ready. The digital broker has to be outfitted with a staunch selection of AI-enabled tools that provide better business visibility, more unified workflows and eliminates time spent managing and updating divergent systems.  

Analysing big data (predictive analytics) and social media using AI can offer real-time insights for measuring risk, immediate demands and possible life changes for customers. For brokers, this translates to an enhanced ability to justify value to clients and ultimately retain those customers.

EY ‘The broker of the future report’

According to a recent EY report on the state of digital brokerages, ‘digital onboarding tools’ and ‘sales leads & application tools’ were identified as attributes with the lowest satisfaction among brokerages. There is a growing sense that these tools need to be a cut above the industry benchmarks — in order to improve the digital relationship with a customer or prospect.

The Digital Broker can also leverage automation to improve efficiency in agent productivity and document handling processes. For instance, enabling employees with remote digital tools empowers them to quickly take action – from quoting prospects to providing policy details and managing claims for existing customers — especially when they need it most. 

Brokers, just like insurers and agencies, need next-gen customer engagement solutions in order to maximize real customer lifetime value. Technologies like Artificial Intelligence have the potential to enhance several facets of the business from reducing back-office processing times and intelligent lead allocation to designing better customer facing products. Improvements achieved through the deployment of AI can create significant gains in operational efficiency and RPE (revenue per employee).

To learn how MantaLabs can help your brokerage begin its digital transformation journey, reach out to us on hello@mantralabsglobal.com

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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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