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Data visualization

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We data scientists spend so much of our effort helping you understand your users that… you forget that we are users too.

Article by Cassie Kozyrkov
Data Science Effectiveness as a UX Problem
  • The article discusses the need for user experience (UX) design tailored to data scientists, emphasizing the importance of understanding their diverse roles and preferences for creating effective data science tools.
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6 min read

Banking and finance have dwelled in an ivory tower throughout their history.

Article by Adam Fard
Fintech UX Design Trends for 2023
  • Many banks are implementing innovative solutions to make the user experience not only effective but also fun.
  • The article covers the following fintech-driven trends:
    • gamification;
    • product identity;
    • centralization;
    • fully mobile banking;
    • social banking;
    • data visualization;
    • human language.
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5 min read

Visualization of different ways of thinking about and solving complex problems.

Article by Houda Boulahbel
A linear thinker, a design thinker and a systems thinker walk into a bar…
  • The author provides a vivid example to demonstrate the differences between various types of thinking — linear, design, and systems.
    • Linear thinking divides the problem into smaller sections, addressing each one independently.
    • The search for the best solution starts with the user’s needs and behavior in the search for design thinking.
    • With a focus on interactions and relationships between things, systems thinking adopts a more comprehensive perspective.
  • We place a lot of emphasis on linear thinking as a society. The author believes that the key to the most effective solutions lies within all three types combined.
Share:A linear thinker, a design thinker and a systems thinker walk into a bar…
3 min read
A linear thinker, a design thinker and a systems thinker walk into a bar

The I in AI.

Article by Max Louwerse
How Cognitive Science and Artificial Intelligence Are Intertwined
  • If we want to understand the mechanisms behind AI, cognitive science might come to the rescue.
  • Artificial intelligence and cognitive science have surprising similarities.
  • AI focuses on artificial minds with human minds as an example.
  • Cognitive science focuses on human minds with artificial minds as an example.
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4 min read
How Cognitive Science and Artificial Intelligence Are Intertwined

A deep dive into the map apps rivalry.

Article by Peter Ramsey
Apple Maps vs Google Maps
  • Apple and Google have battled for control of the map applications market for almost ten years. The article provides an illustration of the advantages and disadvantages of each app.
  • The success of Google Maps can be explained by the following aspects:
    • The breadth of data.
    • Better сontextualization of data.
    • Reliability partners for sourcing data.
    • Accuracy of routes and shortcuts for pedestrians.
  • Nevertheless, Apple has some strong features, especially when it comes to handling stressful situations (e.g. calming and very human narration, detailed parking location information).
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7 min read
Apple Maps vs Google Maps

A framework to take organizations from output to outcome focused product metrics.

Article by Sol Mesz
The Full Loop Analytics Framework

A few months ago, while creating a metrics dashboard for a client I had an epiphany: “if a product is only viable when User, Product and Business are equally present (thinking of the product triad), how come most of the existing frameworks focus on isolated parts of the trilogy?”

I created a framework for considering all 3 parts of the equation:

  1. Key Experience Indicators measure the relationship between User and Product, understanding product performance as a result of user satisfaction.
  2. Key Performance Indicators measure the impact of product performance on business results. In other words, KPIs look at product metrics in terms of business results.
  3. Key Business Indicators measure how user experience impacts business results.

This way fo measuring performance:

  • provides a holistic view of product performance,
  • makes sure that improvements in one area don’t have a negative impact on others,
  • and ensures that everybody is thinking in outcomes (company-wide results) rather than outputs (individual metrics)

Read the full article below for information on each triad, how I created the framework, and ways of applying it to your organization.

Share:The Full Loop Analytics Framework
9 min read

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