A good case study tells the story behind a design — the research, decisions, and process that went into its creation.
A UX case study is a storytelling tool designed to communicate the decisions and processes behind designs. It allows a designer to showcase their work in a way that highlights their skills and processes. Case studies can be read by anyone, but are generally aimed at potential employers.
Case studies are formatted and presented much like a long-form article: they are preceded by an informal information section and contain lots of images and diagrams.
Your case study should have a catchy, descriptive name that provides some context and draws readers in.
Bad: “Nick’s Restaurant” Okay: “Nick’s Restaurant UX Case Study” Good: “Nick’s — An App with Menu and Ordering Capabilities for Patrons of a Fast Casual Restaurant”
A good title formula: [Product Name] + [What It Is] + [Who It’s For]. If a company wants to hire you to work on their mobile app, it’s helpful for their team to be able to take a look at your case studies and determine right away whether there’s a relevant one for them to read.
The intro and overview section is a bit less formal and often written in bullet points or single sentences, rather than a paragraph. You can get creative with the formatting of your overview section, like in this case study, or this one.
Problem statement — what problem were you trying to solve? Goals — what were the intended outcomes of this project? Target audience — who is your end user? Scope and Constraints — a brief outline of the project specs, including any constraints like budget, time, etc.
Team members — roles and responsibilities, including yours! Introduction — a quick intro to the project, much like the abstract in a scientific paper.
Follow a battle-tested methodology baked by years of experience. to build effective solutions and apply the tools to solve the real AL & ML challenges across a variety of different industries.
The challenge of doing it at scale becomes enormous without the power of ML techniques to understand each customer uniquely for their preferences, historical buying trends. Building the infrastructure to handle datafrom scratch.
Data pipelines enable large scale AI & ML modeling for data scientist and data engineers in an organization, helping to cut down the time needed to produce a model, and therefore increasing overall data strategy ROI.
The design process contains the meat and potatoes of your case study and outlines your research, methods, frameworks, and design decisions. Identify each of the steps you took to solve your problem. For each one, write a paragraph explaining: