A product design process for the real world 🚀🔖 Product designers have never had so many tools and techniques at our disposal to help us do our job. Research, journey maps, Figma, code, Keynote, data analysis… the list is huge and keeps growing. With so many options, how do we know which ones to use for our projects and when? Product Design Process I think about my design process not as a mandatory set of actions for every project, but rather a reference and a prompt I can use to either do a task or understand why it can be skipped. Like a carpenter’s toolbox, it’s helpful to remember what tools are available, and how and when they’re helpful. Phases: Discovery The goal of this phase is to help identify a problem statement, frame the problem, and gather enough evidence so we can confidently move forward into the ideation phase. Potential activities: - Make observations - Proto-Personas - Journey mapping - Service blueprint - Contextual inquiry - Generative research - Task analysis - UX tear downs - Stakeholder / SME interviews: Und - Data analysis - UX canvas Definition By defining a problem, stating a goal, and articulating success metrics, the team has helped define some guardrails to design within. Time in this phase can vary depending on the problem and how strongly the team feels about the solution. Potential activities: - Break down the project - Problem prioritisation - Design sprint - Design workshop - Rolling research - Wireframes & prototyping - UI design & prototyping - User testing - Design reviews - Manage up and around Development Product designers are responsible for the design that ends up in the product. For some designers that means creating a detailed design spec, for others it means pushing code directly. Regardless of your direct involvement in code, take an active role in working alongside engineering to implement designs as envisioned. Potential activities: - Finalize design details - Proactively QA designs - Maintain documentation, update artwork - (For teams with a design system) Create new components Great insights by @TedGoas Read the details here: uxdesign.cc/a-product-design… #ui #ux #uidesign #uxdesign #userexperience #uxui #productdesign #prototyping #uxresearch #usertesting #research #userresearch #design #digital #designthinking #webdesign #appdesign #uxprocess #uxstrategy #agile #mvp

Excellent matrix for prioritizing User Research 🔖 “…with limited time and resource, how should we decide on what action to prioritize first?” Here’s how it works: A. Ship it & Measure phase (High problem clarity, Low risk) Happens when: - You and your stakeholders already have concrete hypotheses and backup data (ie: facts supported by previous research or recent study regarding trends, user’s behavior, funnel analysis) about customers and their problems, AND - The risks of misinterpreting the situation tend not to be significant, since the problem is likely to be known and therefore, expected. - This tends to happen more when a concrete solution of said problems has been made and is ready to be tested/implemented. Main keyword: Analytics-driven What to do: - Skip primary user research. - Make an informed hypothesis, take courage to implement a new feature/design (it can be through experimentation or A/B test first, not full launch) - Measure the results - Monitor the data and learn from the experiment B. Research Light phase (Low problem clarity, Low risk) Happens when: - You and your stakeholders are clueless about what is going on (ie: lack of data and knowledge about the topic) that you guys can’t even form coherent hypotheses about the situation, AND - Research questions in this quadrant are often murky but don’t present the same types of risks as with the “Research Heavy” quadrant. Since the risks are low, the need to be accurate is diminished. Main keyword: Lean research support — increasing problem clarity while minimizing resource investment. What to do: - Collaborate with the broader team to identify and test hypotheses through rapid research activities (ie: guerilla test, desk research, quick survey/polls, rapid Q&A, etc) that will improve problem clarity so that team can move to design and solutions. - With enough findings from rapid research, the team will have quantitative and qualitative data to help refine the problem space. C. Design heavy (High problem clarity, High risk) Happens when: - You and your stakeholders already have a concrete hypothesis and backup data (ie: facts supported by previous research or recent study regarding trends, user’s behavior, funnel analysis) about customers and their problems, AND - The risks of not building the appropriate solution to address the problem is crucial and can bring big drawbacks to the company Main keyword: Design research-driven — this quadrant exists to empower and inspire designers What to do: - Collaborate with other divisions to create a design that is representative in answering the problem that is deemed crucial. This can be done in many ways (ie: using findings from primary research — ie: IDI, UT, Survey, Diary study — as the basis for ideation workshop, etc). - Provide decision-making confidence for those involved in a collaboration to make sure that the design work can be done efficiently and appropriately answer the problem. The expected outcome will involve around design prototype. D. Research heavy (Low problem clarity, High risk) Happens when: - You and your stakeholders are clueless about what is going on (ie: lack of data and knowledge about the topic) that you guys can’t even form a coherent hypothesis about the situation, AND - The risks of not building the appropriate solution to address the problem is crucial and can bring big drawbacks to the company. Solutions too quickly run the risk of solving the wrong problem–or no problem at all. Main keyword: Generative research, Research-driven — Questions in this quadrant ultimately save time by requiring you to slow down and invest in the research. What to do: - Spend time to carefully conduct primary research. This will help the team uncover the unknowns and sharpen the knowns of the situation. The team can then create blueprints from the findings, such as end-to-end user journeys or defining the JTBD of users. - The ROI will be experienced subsequently across the product team, as they will be able to form better hypotheses and craft more accurate assumptions due to the depth of their understanding. uxdesign.cc/a-matrix-for-pri… #ux #ui #uxdesign #uidesign #productdesign #webdesign #appdesign #uxresearch #usertesting #userresearch #usability #usabilitytesting #research #prototyping #leanux #agile #customers #design #mobile #uxstrategy #digital #userexperience #productmanagement

Excellent FREE Heuristic Evaluation Workbook 🚀👇 @NNgroup Use this workbook to conduct your own heuristic evaluation. For each of Jakob’s 10 Usability Heuristics, look for specific places where the interface fails to adhere to the guideline. Write your recommendations for how to fix those usability issues. Download the Workbook: media.nngroup.com/media/arti… #ux #uxdesign #ui #uidesign #productdesign #userexperience #webdesign #psychology #research #uxresearch #usertesting #usability #usabilitytesting #uxmethods #prototype #designresearch #webdesign #mobile #css #html #js #users #heuristicevaluation