Product Design Strategy
Product innovation stages
Perfection, excellence in design, and even the ideal work process are all open to interpretation.
There's no single right way. We can use different models and principles as building blocks to create our own custom workflow. The key is to be flexible and adapt our approach based on market needs and investor expectations.
UCD PRINCIPLES (UI, UX)
- Design for the user’s delight
- Empathy for user’s problems
- Maintain consistency
- Simple and natural dialogue
- Usability
- Accessibility
- Provide feedback
- Ask users to take only the necessary actions
- Empower users
- Offer assistance
UCD METHODS (UX, UXR)
Qualitative UX Metrics
- User interviews
- Focus groups
- Questionnaires & Surveys
- Usability testing
- Card sorting
- Participatory design
Quantitative UX Metrics: Analytics, A/B testing, Heatmaps, Eye-tracking, Biometrics
UCD PROCESSES
- Lean Iteration
- Agile Iteration
- Design Thinking Model
Maximise usability:
iterative design - test, learn, improve
MVP to MLP: The Evolution of Successful Products
Define the business vision, create a prototype, follow with an MVP and sell the product.
The product should evolve from one stage to the next, rather than extend time and time again. Instead of looking to cut features from an idealised version of the product, we need answers to 2 questions:
1. What is the problem we're trying to solve?
2. What is the easiest way to solve this problem?
MVP
Functionality First
MVP is a type of functional prototype used specifically for the market to understand the customer’s prospects (early adopters) and their reaction towards the product.
Cross-team collaboration: Stakeholders and Engineers
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Flexible architecture
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High-level scope (function, features)
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Customer advice + analytics
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QA analyst assistance
MMP
All Matters
Everything everywhere all at once. This is the first full release of a "real" product that solves user problems with the minimum number of features.
Cross-team collaboration: stakeholders, sales, designers, engineers
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Innovative features
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Customer feedback (Qualitative UX metrics)
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New functionality
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Solved user problems
MLP
Design First
Loveable features will make users pleased. A catchy, user-friendly design will make the product visually appealing and provide a positive experience.
Cross-team collaboration: stakeholders, Marketing, designers, engineers
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Visually-appealing user-friendly design
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Wow-factor (AI, ML)
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Technically perfect product
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Exceptional customer support
Design Process
Design sprints in Agile, Double-diamond model and Lean iterations
Perfection, excellence in design, and even the ideal work process are all open to interpretation. There's no single right way, just a process of improvement: Discover & Learn, Define & Plan, Ideate & Test, Deliver & Measure
We can use different models and principles as building blocks to create our own custom workflow. The key is to be flexible and adapt our approach based on market needs and investor expectations.
1. We know what to build
The innovation team works on a feature or product without necessarily trying new ideas along the way.
Waterfall is the most common non-iterative process. In the Waterfall model, you and your team will define project phases before the project starts. Each phase begins once a previous phase is completed in its entirety.
2. We don't know what to build
Iterative processes are a fundamental part of Lean methodologies and Agile project management. During the iterative process, we will continually refine a solution until the innovation team is satisfied with the result.
Design sprints typically span 5 days to cover the 4 steps of the Design Thinking process: discover, define, ideate, deliver. The goal of a design sprint (as a time constraint) is to rapidly prototype and test potential solutions.
Design sprints ➝ Development sprints ➝ Roadmap
For How Long?
Iterate with an end goal in mind. The iteration process must meet the estimated delivery date and the strategy from the product roadmap.
1. Design sprints (1 week) - From linear to iterative
Design Sprints are the answer to bringing your organization from a product-centric mindset to a customer-centric mindset.
By collaborating in a 5-day almost-linear fast sprint, we can shortcut the endless debate cycle and condense months of work into just one week.
Monday: map out the problem; research; discover new challenges; data collection
Tuesday: pick an important place to focus; innovation team discussions; sketch a few solution ideas
Wednesday: catch-up meeting with relevant cross-functional teams/current problem; define maximum 3 problems to be solved
Thursday: turn ideas into a testable hypothesis/assumption or high-fidelity prototype, and present it during a weekly design review meeting; during the meeting, check with the stakeholders if the assumptions meet the business vision
Friday: test the prototype with real live humans or using usability-testing online tools; identify usability gaps and document all outcomes in Jira; ideally a set of UI deliverables must be handed off to the development team.
2. Development Lean sprints (2 weeks - MVP) or Development Agile sprints (1 month - MMP) - Iterative process
Iterative processes are a fundamental part of Lean methodologies and Agile project management. During the iterative process, the innovation team continually improve the solution until the product manager is satisfied with the result.
A lean sprint is a streamlined version of a traditional Agile sprint, where the design process is minimized, and the iteration follows a learn-design-test approach. (Data-inspired Design diagram)
3. Product roadmap
An exceptional product designer is both creative and strategic.
As modern software development has adopted a more agile and lean approach, the product design workflow has become more integrated with the development team.
A roadmap is an effective tool for illustrating and communicating the effort to improve design maturity in the organization.
Collaborating with product managers on the roadmap is a great way for design leaders to communicate their design plans.
Tailored Design Process for Each Stage of Product Development
Each stage of a product's evolution (Proof of concept, MVP, MMP, and MLP) has a design process that is adapted to the development conditions.
1. Proof of concept
Duration: 0 weeks, Design Process: none
It is a basic architectural concept that is built on assumptions. Proof of concept typically focuses on a single functionality or minimalistic end-to-end implementation. It should be accompanied by tests and doesn't require design.
2. How to design an MVP (Minimum Viable Product) using a data-inspired design process
Duration: 2-4 weeks, Design Process: Design Thinking (Double-Diamond*), Iteration (Lean)
After the proof of concept is well defined, the design process will start with conducting research on competitors, users, similar products, and current design trends to define the design direction. This is followed by wireframing, user testing and further iterations before the designs are finalised.
Knowing the user needs, we identify the key features that make the product attractive for them. Prioritization is the key because we don't spend time implementing the full features list until testing the viability of the core idea.
MVPs are created to validate assumptions. Customers are coming on board and the feedback is given. The product evolves, backed by the data.
* There are many things to be said about this model. It’s not perfect. No model is. A model is not reality, it's a representation of reality to explain a process. It explained that there is a structure to be found in the design processes and necessary steps to be taken.
Discover
It helps people understand, rather than simply assume, what the problem is. It involves speaking to and spending time with people who are affected by the issues, exploring users' challenges and needs, understanding the business vision and opportunities, and collecting any data that might count for the project. Gather all the collected information and analyze it to identify patterns and potential opportunities.
Define
The insight gathered from the discovery phase can help designers to define the challenge differently, to better define the user types and their needs, to determine the app features and include these in the product roadmap, and to reorganise data relative to the brief.
Ideate
It encourages designers to give different answers to clearly defined problem, seeking inspiration from elsewhere and co-designing with a range of different people from cross-functional teams. It also involves testing out different solutions at small scale, rejecting those that will not work and improving the ones that will. It helps people understand, rather than simply assume, what the problem is. Designers produce wireframes, mockups and prototypes to simulate user experience and test potential solutions.
Deliver
This stage focuses on implementing and launching the approved design solution. The refined and tested prototypes for different use cases and user types are transformed into final designs. This involves finalising details, breakpoint system, layouts and grids, creating high-fidelity visuals, updating the design system with the newest components and preparing these for production and UI testing.
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 designers 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. Designers 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/innovation 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