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Even when the customer has successfully added items to cart, it all means zilch until the purchase is complete. The average cart abandonment rate for all sectors worldwide was 75.6% last year. Simply put three out of every four digital customers leave websites without completing the purchase. 

At the customer acquisition phase, you’ve to compete with zero-profit offers, despite the fact that your product is the best in its niche.

Although 80% of businesses claim they offer a great customer experience, only about 8% of customers express satisfaction with their experience. 

So, what went wrong? Why are customers leaving your site without purchasing? And more importantly, what can you do about it?

Mastering the art of understanding user persona, discovering bottlenecks in the delivery process, and designing a user-friendly interface will help you build the product that supersedes customers’ expectations. 

Mapping the Customer Journey 

It involves understanding your customers’ behavior and feelings throughout their interaction with your products/services and visually mapping them to tell a complete story of their overall experience. 

More precisely, the journey begins from the moment they first come to know about your product and the phases they pass through while making a final purchase decision.

“For brands, customer journey mapping is like walking a mile in their customers’ shoes and understanding their circumstances with empathy.”

Apart from managing complex user experience problems, you can tweak customer journeys to understand past, present or a future state surrounding a day in the life of your customer.

According to Gartner, Eighty-two percent of organizations have created a customer journey map, but only 47% are using those maps effectively. The mapping of the customer journey begins by creating a cross-functional team led by the CIO, CMO or even the CEO. 

A journey map is different from process maps. They detail multiple channels and touchpoints before and during the buying process. Interestingly, the more value-added layers you can include, the better is your view of your customer.

Top Customer Journey Map Layers

Source: Uxpressia

Adding convenience to the customer experience value chain can create powerful moments of truth. For instance, while shopping on your portal, a customer might want to know more information about your product, it’s features, reviews, etc. 

A proactive service that goes to the customer first using real-time messaging and custom product recommendations, is how innovative solutions can address such pain points, impacting the overall experience.

Choosing the Right Attributes

Before we look at how to select the most relevant inputs for outlining behavior, it’s important to grasp the fact that customer journey mapping is an iterative process. For instance, the questions answered by customer journey maps a decade ago is totally different from today.

Source: Harvard Business Review | Linear customer journey map in 2010

Source: Medium | The present-day non-linear customer journey map (eg: Ikea)

The goal is to build a comprehensive map that will conclusively identify gaps from multiple touchpoints — areas of customer experience that are disjointed or painful.

To achieve this, it is vital to map out each phase of the pre-buying and actual buying journey and map them alongside data-driven personas. Data is critical for customer journey stages — it is almost impossible to create customer journey maps without it.

The Modern Customer Journey
Source: G3 Com

The modern customer journey map needs to cover the complete omnichannel experience. Customers are now communicating with companies through 10 channels on average. Their expectations are fast-moving and rapidly evolving. They expect communications about the latest products from their favorite brands to happen in real-time.

For instance, Magalu, one of Brazil’s largest retail companies, recognized that its app was growing in popularity. They decided to enable deep linking, so that loyal customers who tapped on a Magalu ad were taken directly to the mobile app they already have installed, resulting in more than 40 percent growth in overall mobile purchases.

Customer journey maps are drawn from the customer’s point of view and are based on people’s mental models (how things should behave, the flow of interactions and possible touchpoints). They combine user personas, user scenarios & user flows to understand and predict how the customer will behave next.

5 Key Attributes of an efficient Customer Journey Map

  1. Most relevant brand goals: The goals should be reflective of the inner aspirations of the organization that outwardly manifest into creating the best experiences consistently for the customer.
  2. Key customer touch-points: Identify touch-points across all channels, and define the action and available paths for each. This layer is critical to understanding how the service structure forces customers into unnecessary interactions and take measures to avoid them.
  3. Empathy Map: This map depicts exactly what the customer thinks, says, does and feels about your product/ service or the complete attitude towards the brand itself. One can also find utility in creating one-user vs multiple-user empathy maps.
  4. Affinity Diagram: This is a great planning tool, and it enables you to organize the data and insights gathered up to this point into bundles.
  5. Sketch the Journey: Now is the time to visualize the structured data into powerful story-driven narratives pointing out gaps in the process. This step will inform what solution or fix will remedy your customer’s pain-point for the long term.

Why You Need Customer Journey Mapping?

You’re doing great if you understand your customers and are able to exceed their expectations. Retaining a loyal customer base might make you think about the essence of understanding the customer journey. 

But, how are you planning to face the competitive landscape? Because customers constantly lookout for change. What if your competitors satisfy your customer’s needs with a better emotional connection? Mapping the customer journey will allow you to transform the experience delivery process creating ‘wow’ moments that strengthen loyalty.

“The term ‘customer experience’ won’t exist in the organization of the future. It will be deeply entrenched in a company’s product, process, and culture that it will be synonymous with the brand and represent the only way to do business.”

Ann Lewnes, EVP and CMO, Adobe

We specialize in helping organizations build attractive and easy-to-understand user journey maps for faster omnichannel integration. Reach out to us on hello@mantralabsglobal.com, to learn more.

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Across the Insurance ecosystem, a special fraction within the industry is noteworthy for its adoption of new technologies ahead of others. However slow but sure, uberization of insurance has conventionally demonstrated a greater inclination towards digitization. Insurers now more than ever, need big data-driven insights to assess risk, reduce claims, and create value for their customers. 

92% of the C-Level Executives are increasing their pace of investment in big data and AI.

NewVantage Partners Executive Survey 2019 

Artificial Intelligence has brought about revolutionary benefits in the Insurance industry.

AI enriched solutions can remove the ceiling caps on collaboration, removes manual dependencies and report errors.

However, organizations today are facing a lot of challenges in reaping the actual benefits of AI.

5 Challenges for AI implementation for Insurers

5 AI Implementation Challenges in Insurance

Lack of Quality training data

AI can improve productivity and help in decision making through training datasets. According to the survey of the Dataconomy, nearly 81% of 225 data scientists found the process of AI training more difficult than expected even with the data they had. Around 76% were struggling to label and interpret the training data.

Clean vision, Process, and Support from Executive Leadership

AI is not a one time process. Maximum benefits can be reaped out of AI through clear vision, dedicated time, patience and guided leadership from industry experts and AI thought leaders.

Data in-silos

Organizational silos are ill-advised and are proven constrictive barriers to operational productivity & efficiency. Most businesses that have data kept in silos face challenges in collaboration, execution, and measurement of their bigger picture goals. 

Technology & Vendor selection

AI has grown sharp enough to penetrate through the organizations. As AI success stories are becoming numerous investment in AI is also getting higher. However big the hype is, does AI implementation suits your business process or not – is the biggest question. The insurtech industries have continued its growth trajectory in 2019; reaching a funding of $6B. With the help of these insurtech service firms, Insurance organizations have made progress, tackling the age-old insurance ills with AI-powered innovations.

People, Expertise and Technical competency

‘Skills and talent’ in the field of AI is the main barrier for AI transformation in their business.

Still playing catch-up to the US, China, and Japan — India has doubled its AI  workforce over the past few years to nearly 72,000 skilled professionals in 2019. 

Are you facing challenges with your Insurance process but have no idea where the disconnect is? Is your Insurance business process ripe for AI in the year 2020?

What is the right approach?

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 on the 13th of February, 2020.

Register for the live webinar by Parag Sharma (AI Thought Leader & CEO Mantra Labs). 

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Ratemaking, or insurance pricing, is the process of fixing the rates or premiums that insurers charge for their policies. In insurance parlance, a unit of insurance represents a certain monetary value of coverage. Insurance companies usually base these on risk factors such as gender, age, etc. The Rate is simply the price per ‘unit of insurance’ for each unit exposed to liability. 

Typically, a unit of insurance (both in life and non-life) is equal to $1,000 worth of liability coverage. By that token, for 200 units of insurance purchased the liability coverage is $200,000. This value is the insurance ‘premium’. (This example is only to demonstrate the logic behind units of exposure, and is not an exact method for calculating premium value)

The cost of providing insurance coverage is actually unknown, which is why insurance rates are based on the predictions of future risk.  

Actuaries work wherever risk is present

Actuarial skills help measure the probability and risk of future events by understanding the past. They accomplish this by using probability theory, statistical analysis, and financial mathematics to predict future financial scenarios. 

Insurers rely on them, among other reasons, to determine the ‘gross premium’ value to collect from the customer that includes the premium amount (described earlier), a charge for covering losses and expenses (a fixture of any business) and a small margin of profit (to stay competitive). But insurers are also subject to regulations that limit how much they can actually charge customers. Being highly skilled in maths and statistics the actuary’s role is to determine the lowest possible premium that satisfies both the business and regulatory objectives.

Risk-Uncertainty Continuum

Source: Sam Gutterman, IAA Risk Book

Actuaries are essentially experts at managing risk, and owing to the fact that there are fewer actuaries in the World than most other professions — they are highly in demand. They lend their expertise to insurance, reinsurance, actuarial consultancies, investment, banking, regulatory bodies, rating agencies and government agencies. They are often attributed to the middle office, although it is not uncommon to find active roles in both the ‘front and middle’ office. 

Recently, they have also found greater roles in fast growing Internet startups and Big-Tech companies that are entering the insurance space. Take Gus Fuldner for instance, head of insurance at Uber and a highly sought after risk expert, who has a four-member actuarial team that is helping the company address new risks that are shaping their digital agenda. In fact, Uber believes in using actuaries with data science and predictive modelling skills to identify solutions for location tracking, driver monitoring, safety features, price determination, selfie-test for drivers to discourage account sharing, etc., among others.

Also read – Are Predictive Journeys moving beyond the hype?

Within the General Actuarial practice of Insurance there are 3 main disciplines — Pricing, Reserving and Capital. Pricing is prospective in nature, and it requires using statistical modelling to predict certain outcomes such as how much claims the insurer will have to pay. Reserving is perhaps more retrospective in nature, and involves applying statistical techniques for identifying how much money should be set aside for certain liabilities like claims. Capital actuaries, on the other hand, assess the valuation, solvency and future capital requirements of the insurance business.

New Product Development in Insurance

Insurance companies often respond to a growing market need or a potential technological disruptor when deciding new products/ tweaking old ones. They may be trying to address a certain business problem or planning new revenue streams for the organization. Typically, new products are built with the customer in mind. The more ‘benefit-rich’ it is, the easier it is to push on to the customer.

Normally, a group of business owners will first identify a broader business objective, let’s say — providing fire insurance protection for sub-urban, residential homeowners in North California. This may be a class of products that the insurer wants to open. In order to create this new product, they may want to study the market more carefully to understand what the risks involved are; if the product is beneficial to the target demographic, is profitable to the insurer, what is the expected value of claims, what insurance premium to collect, etc.

There are many forces external to the insurance company — economic trends, the agendas of independent agents, the activities of competitors, and the expectations and price sensitivity of the insurance market — which directly affect the premium volume and profitability of the product.

Dynamic Factors Influencing New Product Development in Insurance

Source: Deloitte Insights

To determine insurance rate levels and equitable rating plans, ratemaking becomes essential. Statistical & forecasting models are created to analyze historical premiums, claims, demographic changes, property valuations, zonal structuring, and regulatory forces. Generalized linear models, clustering, classification, and regression trees are some examples of modeling techniques used to study high volumes of past data. 

Based on these models, an actuary can predict loss ratios on a sample population that represents the insurer’s target audience. With this information, cash flows can be projected on the product. The insurance rate can also be calculated that will cover all future loss costs, contingency loads, and profits required to sustain an insurance product. Ultimately, the actuary will try to build a high level of confidence in the likelihood of a loss occurring. 

This blog is a two-part series on new product development in insurance. In the next part, we will take a more focused view of the product development actuary’s role in creating new insurance products.

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