UX Design Process
Define, Plan, Ideate, Deliver
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Once all the research has concluded and a good amount of substantial insights has been gathered from the users, it’s time for the designers to step in.
During the UX design phase, research findings are interpreted and incorporated into design works to create functional features that solve users' pain points and problems.
MVP
Functionality First
MVP is a type of functional prototype, created with minimum effort and development time. It is not the first version of product, but the most basic form of it, to provide the initial users with a minimum set of features, allowing them to evaluate and explore more.
UX FOCUS: usability, core features
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Define a basic form of the UX Design Process
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Identify the primary user types (Early Adopters). User Personas
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Sitemap. Basic form of content and navigation for essential presumed features
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Navigation for Core Features. Set up the preliminaries for a home screen/dashboard/landing page
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Clear Navigation Paths for core features. Useflows
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Basic/most relevant Data Collection (forms, surveys, questionnaires) and Data Representation (lists, tables, graphs)
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Filters to Improve Product Listing are optional
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Empower users with necessary simple actions (Add, Edit, Delete, Save, Confirm)
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Conduct user testing (online) and then revise product Assumptions
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Minimum accessibility principles: perceivable, operable, understandable, robust
MMP
All Matters
MMP is the first full release of a "real" product that solves customers' problems with the minimum number of features. The aim is to document market feedback and translate it into a few new features that can bring value and solve previous user's problems.
UX FOCUS: UX metrics, new features
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Establish a UX Design Process and incorporate it into an R&D workflow
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Consider adding New User types
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Sitemap. Content hierarchy and seamless Navigation
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Navigation. Landing page evolves into a more complex space with important features
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Complex Navigation Paths as the product evolves. Useflow exploration
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Data Collection and Data Representation are refined/redefined based on the user's feedback
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Filters to Improve Product Listing become a must
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Empower users with a streamlined process of Actions Flow that best serves their needs
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Conduct User Testing with real users and then Revise Product/Features Definition
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Accessibility principles to ensure the product satisfies the needs of all user types
MLP
Design First
Building an MLP will help the business protect its reputation, stand out against competitors, and create a feedback cycle to drive continuous improvement. It focuses on features that are impressive enough to delight users. Customers will tell others about the product.
UX FOCUS: user-friendly, cool features
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The Design Process rapidly responds to the Changes, highly functioning Agile development team
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Customers become Ambassadors for the product
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Sitemap is revised and updated with Cool Features
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Navigation. Home/Dashboard/Landing page becomes the starting point for most of the features and includes access to other products from the company's portfolio
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Flawless Navigation Paths - Useflows
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A perfect synergy between Data Collection (input), Data Representation (results) and the user's needs
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Filters, Sorting options, and a Search bar to minimize the time spent searching on a product listing
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Empower users with a streamlined process of self-service Actions Flow that best serves their needs
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Conduct User Testing and then revise the Product Definition to create an Emotional Connection with the users. Emotional Mapping for User Flows
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All Accessibility requirements have now been met
UX Design Templates
User journey maps, User personas, User flows and many more
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Why customer-centric teams prefer a data-informed design process?
"Data-driven" involves teams guided by data. But being data-driven doesn’t always lead the team down the path that’s best for the business' customers.
Data-driven means making decisions based solely on data. Data-informed means using data as one of several inputs, alongside factors like your company’s objectives and employee expertise, in decision-making.
Customer-centric product teams need to combine quantitative, numerical data with qualitative data analysis to reveal real user behaviour and needs. Some of the best ways to get deeper insights and make data-informed product decisions include heatmaps, recordings, surveys & feedback, user interviews.
More data isn’t always better. The product team can have all the data in the world, but if it’s not accurate or doesn’t address the right questions, it will not help the team to make the decisions that lead to meaningful results. Being data-informed means the team understands which data is the most important, and to prioritize quality data to underpin the business decisions.
How to build a Design Systems at Scale? Can it be considered a digital product itself?
Decades ago, we didn’t know the difference between a visual style guide, component library, design language, or design system.
A healthy design system will make it easier to scale design patterns and components alongside a growing design/product team. It ensures consistency and quality across all experiences and increases the speed without losing best practices or consistency within the product.
There are a few steps to follow in scaling the design system across different products and platforms:
- align the design system with product vision and goals: purpose, scope, and value of the design system, and how it supports the company's brand identity, user needs, and business objectives.
- establish a governance model that defines the roles, responsibilities, and processes for creating, updating, and using the design system
- modularize and standardize the components, so that they are easy to reuse, customize, and maintain across different products and platforms
- adapt it to different contexts and needs of the products and platforms by considering: the diversity and specificity of the users, devices, environments, and scenarios. How do these factors affect the design decisions and outcomes? The design systems need to be tested and evaluated in different contexts and needs, then collect and analyze feedback.
- promote a culture of collaboration and learning among the design, product, development team and other stakeholders.
- evaluate and measure the impact and value of the design system, and test if it meets the business vision and goals. Identify the gaps and opportunities, and prioritize and implement the necessary changes and enhancements.
Why choose qualitative research over quantitative research?
It depends on what kind of project is going to be handled. Qualitative Research is a method generally used for understanding user's views and perceptions. It offers visions for different problems and helps in developing concepts or theories for potential quantitative research.
This method uses various kinds of unstructured or semi-structured practices for data collection such as group discussions or individual interviews. It helps in interaction among respondents, as they depend on the comments, perceptions, views, opinions and ideas of people. It involves respondents more than in a structured survey (Quantitative Research). It uses in-depth analysis of small groups of people for building theories. The results of qualitative research are not predictive, but descriptive.
What are design tokens in Figma?
Design tokens are a method for managing design properties and values across a design system. Each token stores a piece of information, such as colour, sizing, spacing, font, animations, and so on. To make them easier to refer to, each token also gets a name.
The tokens become a source of truth and a shared language between design and code, making updating the designs and design systems more efficient.
Source: Figma Learn