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10 Most Important Interaction Design Principles

Mikhail Mitra
7 minutes, 7 seconds read

The process of interaction design involves studying the behavior and structure of interactive systems and implementing them for developing useful digital products. In other words, interaction design is the relationship between user and product and the services they use.

The purpose of interaction design is to create a great user experience. That’s why most of the UI disciplines require understanding and hands-on experience of interaction design principles. After all, it’s about designing for the entire interconnected system: the device, interface, context, environment, and people. Interaction designers strive to create meaningful relationships between people and the products and services they use. It may include computers, mobile devices, gadgets, appliances, and more.

It is important to understand ux design best practices while developing complex web and mobile applications. These are the key elements that product designers should not neglect while creating an interface for the user. 

The 10 most important interaction design principles are-

  1. UX: Match user experience and expectations
  2. Consistent design: Maintain consistency throughout the application
  3. Functionality: Follow functional minimalism
  4. Cognition: Reduce cognitive loads/mental pressure to understand the application
  5. Engagement: Design interactively such that it keeps the user engaged.
  6. User control: Allow the user to control, trust, and explore
  7. Perceivability: Invite interactions through intuitions and interactive media
  8. Learnability: Make user interactions easy to learn and remember
  9. Error handling: Take care to prevent errors, if they occur make sure to detect and recover them.
  10. Affordability: Simulate actions by taking inspiration from usual and physical world interactions.

10 Important Interaction Design Principles

#1 Match user experience and expectations

By matching the sequence of steps, layout of information, and terminology used with the expectation and prior experiences of the users, designers can reduce the friction and discomfort of learning a new system.

You can match your audience’s prior experiences and expectations by using common conventions or UI patterns, for example, Hitee Chatbot.

#2 Consistency

Along with matching people’s expectations through terminology, layout, and interactions, the design should be consistent throughout the process and between related applications. 

By maintaining consistency, you are helping users learn more quickly. You can re-apply their prior experiences from one part of an application to another to maintain consistency throughout the design. Design consistency is also an aid to intuitive interfaces.

Bonus – you can use the inconsistencies to indicate to users where things might not work the way they expect. Breaking consistency is similar to knowing when to be unconventional.

#3 Functional minimalism

“Everything should be made as simple as possible, but no simpler.” 

Albert Einstein

The range of possible actions should be no more than is absolutely necessary. Providing too many options will detract the primary function and reduce usability by overwhelming the user with choices. To achieve the Zen of functional minimalism, you should-

  1. Avoid unnecessary features and functions
  2. Break complex tasks into manageable sub-tasks
  3. Limit functions rather than the user experience.
Key elements of interaction design

#4 Cognitive loads

Cognition refers to the “process of thoughts.” A good user interactive design minimizes the user’s “effort to think” to complete a task. Another way to put this is that a good assistant uses his skills to help the master focus on his skills.

For instance, while designing an interactive interface, we need to understand how much concentration a task requires to complete it. Accordingly, you can design the UI that reduces the cognitive load as much as possible. 

Here’s a technique to reduce users’ “thinking work.” Focus on what the computer is good at and build a system that utilizes its abilities to the fullest. Remember, computers are good at-

  • Maths
  • Remembering things
  • Keeping track of things
  • Comparing things
  • Spell Checking and spotting/correcting errors

The point is – by knowing the attributes of users and products, one can create a design for a better user experience.

#5 Engagement

In terms of user experience, engagement is the measure of the extent to which the user has a positive experience with your product. An engaging experience is not only enjoyable but also easier and productive. Engagement is subjective to the system. I.e. your design must engage with the desired audience. For instance, what appeals to teenagers might be irrelevant to their grandparents. Apart from aligning your design for the appropriate audience, achieving and creating control is the key.

The interaction design principles state that users should always feel like they’re in control of the experience. They must constantly experience a sense of achievement through positive feedback/results or feel like they’ve created something.

In his book “Flow,” Mihaly Csikszentmihalyi describes a state of optimal experience where people are so engaged in the activity that the rest of the world falls away. Flow is what we’re looking to achieve through engaging interactions. We should allow users to concentrate on their work and not on the user interface. In short, stay out of the way!

#6 Control, trust, and explorability

Good interaction design should incorporate control, trust, and explorability to any system. If users feel in control of the process, they’ll be more comfortable using the system. If the user is comfortable and in control, they’ll trust the system and believe that the application will prevent them from making an unrecoverable error or from feeling stupid. Trust inspires confidence and with confidence, the user is free to explore further. Intuitive interfaces are extremely good at stimulating users to navigate and explore the app.

#7 Perceivability

People are aware of the opportunity to interact with interactive media. As interface designers, we must avoid developing hidden interactions, which decrease the usability, efficiency, and user experiences. In other words, people should not have to guess or look for opportunities to interact.

When developing interactive media, users should have the ability to review an interface and identify where they can interact. We must remember that not everyone experiences and interacts with interface in the same way others do. In the process of interaction design, make it a habit to provide hints and indicators like buttons, icons, textures, textiles, etc. Let the user see that these visual cues can be clicked or tapped with their fingers. Always consider the usability and accessibility of the interactive media and how the user sees and perceives the objects in the interface.

How users perceive the opportunity to interact with a digital media

#8 Learnability

Another important interaction design principle is inducing the ability to learn to use the interface easily. In other words, users should be able to learn to use the interface in the first attempt and should not face issues using it again. Please note that engaging interfaces allow users to easily learn and remember the interactions.

Even though simple interfaces may require a certain amount of experience to learn, learnability makes interaction intuitive. People tend to interact with an interface similar to other interfaces. This is the reason why we must understand the process of interaction design thoroughly and the importance of design patterns and consistency. 

Intuitive interface design allows users to learn to use the interface without much effort and gives them a sense of achievement. They feel smart and capable of grasping and utilizing newer interfaces. In a nutshell, product designers should let the user feel confident while navigating through the interface.

#9 Error prevention, detection, and recovery

The best way to reduce the number of errors a user makes is to anticipate possible mistakes and prevent them from happening in the first place. If the errors are unavoidable, we need to make them easy to spot and help the user to recover from them quickly and without unnecessary friction.

Error prevention techniques-

  • Disabling functions that aren’t relevant to the user
  • Using appropriate controls to constrain inputs (e.g. radio buttons, dropdowns, etc.)
  • Providing clear instructions and preemptive help
  • As a last resort, provide clear warning messages.

How to handle application errors through design?

Anticipate possible errors and provide feedback that helps users verify that-

  1. They’ve done what they intended to do.
  2. What they intended to do was correct.

Please note that providing feedback by changing the visuals of the object is more noticeable than a written message.

Error recovery techniques – 

If the error is unavoidable, provide direction to the user to recover from it. For example, you can provide “back,” “undo,” or “cancel” buttons.

If a specific action is irreversible, you should flag it “critical” and make the user confirm first to prevent slip-ups. Alternatively, you can create a system that naturally defaults to a less harmful state. For example, closing a document without saving it should be intelligent enough to know the unlikely behavior of the user. It can either auto-save or display a warning.

The spectrum of user interface : interaction design principles

#10 Affordance

Affordance is the quality of an object that allows an individual to perform an action. For example, a standard household light switch appears innately clickable. 

The point is – users should get a clue about how to use an abject through its physical appearance. While designing user interfaces, you can achieve affordance either by simulating ‘physical world’ affordances (e.g. buttons or switches) or keeping consistency with web standards and interface design elements (e.g. underlined links or default button styles). The thing is, in an intuitive interface, users are able to navigate and use the functionalities of the application without any formal training.

Interaction design is not always about creating a better interface for the users; it is also about using technology in the way people want. It is necessary to know the target users to design a desirable product for them. Interactive design is the basis for the success of any product. These 10 interaction design principles are based on the study and experiences of our team in designing mobile and web apps for a broad product portfolio and on multiple mobile and web platforms.

Drop us a word at hello@mantralabsglobal.com to learn more about our interaction design projects and services.

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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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