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“Holistic design” sounds like a new flashy trend that’s used without a real meaning behind it. However, the term was present long before UX design was born. Nowadays, when we use “product design” for digital products and “industrial design” for things, “holistic design” makes a comeback to UX design.

What Is Holistic Design? The Future of UX or a Buzzword?
  • To apply holistic design principles is to consider different facets of a product, stakeholders’ interests and the environment within which it functions.
  • Best practices of holistic design consist of involving stakeholders, being sustainable, creating an ecosystem, and, last but not least, going beyond digital.
  • When it comes to holistic design in UX, it’s essential to apply design thinking and reflect on the design system, make sure that solutions are inclusive and consistently invest in UX research.
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Frame 1 Holistic Design
Building digital products for the web’s next billion users
  • Connectivity issues are further inflated by accessibility gaps. This, in turn, undermines user experience and creates obstacles for the wider use of digital products.
  • When designing for users, it’s worth considering such issues as poor connectivity, accessibility constraints, levels of technological literacy within different countries and cultural barriers.
  • In order to satisfy the needs of the next 3 billion users, it’s vital to build inclusive and accessible products that will provide solutions to the critical problems the next generation will face.
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A New Design-Centered Meeting Framework: Better Capture the Product Design Narrative
  • Understanding what users feel when using the product is the path towards a great user experience.
  • A good starting point is to research who are the users and subsequently map their emotions at different stages of using the product.
  • Once users emotional background is figured out, it’s easier to frame problems, prevent negative emotions and build a greater user experience.

Read the full article to learn about designing great interactions that suit human emotions.

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Simple is exponentially harder than complex, namely because there’s a psychological chasm that most teams cannot surpass… or perhaps they have not been setup to succeed.

5 Reasons Why Designing Simple Experiences is Psychologically Impossible
  • Designing simple and seamless experiences is exponentially harder than designing complex solutions
  • Simple solutions require an extraordinary amount of time, money, and skill
  • Other obstacles to simple design include complexity bias, loss aversion, unpredicted behavior, and fear of risks
Read the full article to learn more about the psychology behind designing a simple experience.
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Questions to get the most value out of your internal or external design teams.

Design Killer, Killer Design
  • Critique is a vital component of the design process as it enables improvement. However, it has to be well-thought-through to be beneficial for the design process.
  • 3 key questions might help to provide constructive feedback: What is the purpose behind the design? Are the design principles respected? Is there a visual hierarchy of elements/information?

Read the full article to learn a helpful method for and some key ingredients for design critiques.

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An expert’s view on the massive strategic opportunities and potential challenges of leveraging conversational AI solutions

The Disruption of Customer Experience: How Conversational AI is upping UX and CX standards
  • By transforming the way humans interact with technologies and making them more accessible to the public, conversational AI is raising the bar for customer experience.
  • One of the most tangible impacts of conversational AI has been on customer support and sales conversion. Thanks to the automation of conversations, the load on human staff is reduced, which leads to greater customer and employee experience.
  • As technological development advances, more opportunities to make good use of conversational AI will emerge. Nevertheless, it’s also necessary to not underestimate potential challenges related to legacy systems, data availability, shortage of conversational AI specialists.
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