Icanknitthat
This project intends to utilise the emerging technology of generative AI to improve the experience of finding and creating a knitted piece. The design solution should prioritise customisation and helping users learn how to complete a project. Due to the nature and time constraint of the coursework, only one iteration of the design method was allotted.
Role
Product Designer, User Researcher
Process
Lean UX
Timeline
Feb - May 2024
Context
MSc Project
Design Process
For Icanknitthat, my design approach was focused on building potential ideas or areas of focus, investigating these claims, and then building solutions based on the claims proven to be true.
Developing Assumptions
As this project follows the Lean UX design process, the first stage of this project was to create and prioritise assumptions about our users and their needs. These were built off of beliefs about the users based on context of use, intuition, and general knowledge about the knitting community.
Assumptions were formed to help guide topics explored during the user research stage and determine the focuses of this project.
As this was a solo project, I utilised Chat GPT to conduct brainstorming sessions for creating my assumptions. This allowed me to consider potential concepts to explore I would not have considered on my own.
Once the assumptions had been written out, a prioritisation chart was made based on the value each assumption brings to project and risk if proven false.
Gathering Information
Secondary Research was conducted to assess how this application could contribute to the knitting pattern industry and determine the plausibility of this application due to its involvement with emerging technologies. User interviews were then conducted to gain insight into how target users were currently interacting with knitting patterns.
How are users currently finding projects?
Most participants sited social media sites such as Pinterest, TikTok, or Raverly as their main method for finding their next project.
Some participants said they find their next project in knitting books, preferring to select a pattern from the many available in just one book over searching online.
A few participants, who were at more advanced levels of knitting, said they preferred free-knitting, which is when a knitter decides on a garment type and then creates their own pattern as they go.
How are users currently learning more about knitting?
Most participants indicated that they used YouTube in some way, whether that be to find stitch tutorials, pattern walkthroughs, find new projects, or connect with the online knitting community while they knit.
Participants also sited friends and family as a source for getting them into knitting and helping them learn how to knit.
Some participants began knitting after seeing knitting content creators on platforms such as TikTok or Instagram and now use social media to find tutorials, get inspiration, and connect with fellow knitters.
What do users wish they had to improve their knitting experience?
Participants expressed frustration with the time it takes to source a project and make adjustments to the pattern to suit their needs for the piece.
Participants expressed wanting more flexibility with knitting patterns, allowing them to make small changes to the pattern such as size or sleeve type and still have a pattern to follow.
Participants wished for more inclusive sizing options as knitting patterns often don’t provide extended sizing options.
Participants wanted more guidance on how to complete projects including step by step tutorials or helpful tips.
Participants expressed wanting a quicker, more efficient way to find inspiration for their next project.
What currently exists on the market?
The Ravelry app is a comprehensive online community and resource hub for knitters and crocheters, offering pattern discovery, project tracking, and a platform to connect with fellow fiber enthusiasts. Raverly is an app specifically for knitting and connects users directly to knitting patterns, however it does not currently have a mobile application and does not address user’s desire for customisation of knitting patterns.
The Pinterest app is a visual discovery and bookmarking platform that allows users to find, save, and share ideas through images and videos. While the app isn’t specifically intended for knitting, many creators share their patterns or images of their pieces on this site. However, since the site merely connects users with images or links to a knit piece, the rest of the process of sourcing a new project is left up to the users to complete.
The DreamKnit app is a knitting and crochet project management tool that helps users organize patterns, track progress, and connect with a community of fellow crafters. This tool allows users to create their own knitting patterns using the set options. While this tool addresses users’ desire for custom pieces, the application has limited pattern and sizing options, which severely restricts users.
Defining the User and Their Needs
Using the findings from the user research step, the user types and their needs were further defined in this next stage.
After speaking with users and conducting research on young knitters, I separated users into two groups: casual knitters and business owners.
I chose to divide the user groups as such to capture the different approaches to knitting and finding projects that I observed during the user research stage.
Casual knitters enjoy knitting only in their spare time and as such needed a tool to help with sourcing projects and learning tutorials, whereas the business owner persona needed a resource to help cut back on the time needed to design and make a new piece for their knitting business.
Using the newly formed personas, I created user stories to better articulate the target users’ intended relationship with the application.
The app aims to follow the user through the entire knitting experience from ideation to casting off the piece so it was important that user needs were accounted for through that entire process.
Because the application is intended to be used while the user is knitting, I also wanted to ensure its design best facilitates this type of interaction.
Developing Hypotheses
Hypotheses were created using the assumptions and user information from the begin stages of this project.
Using all of the data I have collected so far, I developed hypotheses to be used during the design phase to focus efforts on features that would best serve the application’s intended purpose.
These hypotheses were also used during the testing phase to develop the research questions posed during testing phase of this project.
Ideation
The next stage of this project began with brainstorming features using the ideation techniques: rapid idea generation and How might we? The ideas were then translated into low-fidelity interface sketches.
My intention was to produce as many viable feature concepts and then work backwards to assess how the feature would address user needs and the overall fit of the feature within the product.
A NUF test was then performed to determine which ideas would bring the most value to the project and should then be progressed forward.
All relevant screens were drafted as well as a potential overall application layout.
The first draft sketches were presented to target users for feedback, after which another round of sketches were created with updated design to reflect the findings of those feedback sessions.
When deciding how to design the screens for the application, my objective was to create minimalist layouts to ensure the primary focus remained on the knitting pattern, as to not overwhelm the user.
Creating a new pattern was drawn out into multiple screens so users can focus on the action or decision needed for each step.
Slide-in menus were also utilised wherever feasible to keep information concealed until necessary.
Creating a Wireframe
The sketches made in the previous stage were then translated into a mid-fidelity wireframe to allow for a better understanding of space and how the sketched ideas would translate digitally.
The sketches made in the previous stage were then translated into a mid-fidelity wireframe.
This allowed me to gain a better understanding of how the sketched ideas would translate digitally.
Further adjustments for things like size and visual look were adjusted to match the true scale of the interface.
Visual Design
A visual design and guide was created to facilitate the moving from mid-fidelity to high prototype and ensure the product’s design aligns with its overall mission.
A visual design guide was created to facilitate the move from mid-fidelity wireframe to high prototype and ensure the product’s design aligns with its overall mission.
As the product’s target users are young beginner to advanced knitters, the brand is described as fun, collaborative, and innovative.
To align with the product’s brand, the visual design is characterised by warm, playful colours, modern san-serif fonts, and simplistic UI layouts to focus on the content created by users.
Prototyping
Using the mid-fidelity wireframe and visual design guide created previously, a high-fidelity prototype was developed.
The overall design was made to feel minimalist to draw users to the content and help create clarity when working through knitting patterns or creating new patterns.
The utilisation of colour was done to highlight potential actions available to the user.
Usability Testing
The product was evaluated via usability testing to assess the product for any further design improvements and usability issues. This ensured that the product was meeting it’s intended purpose set in the beginning stages of this project.
Key Findings
The testing sessions conducted had minimal task errors and no task failures reported.
The average SUS score of this application was 85, significantly above the overall industry average score of 68.
Users expressed enjoyment with the breadth of customisation options when creating a new pattern, especially the inclusive sizing.
Some users struggled with understanding how to login versus sign up for the application due to a lack of language on the login screen. Language was added to resolve this issue.
Users also struggled to understand the difference between the pattern customisation and pattern details page so additional language and breadcrumb techniques were used to improve this experience.
Some users also struggled to identify the settings screen so further language was added to create more clarity.
Process
Research Questions
How does the addition of a search feature that allows users, particularly knitwear business owners like Audrey, to query and find knitting projects reflecting current trends, impact their ability to find appealing and inspiring knitting patterns?
How does the addition of a camera or upload feature for knitwear project ideas impact the ability of beginner users, particularly Carrie, to create knitwear that matches their inspiration and enhances the communal and fun aspects of finding knitting patterns?
How does the addition of an AI-powered preview feature for detecting knitwear impact the time and effort efficiency for users, particularly knitwear business owners like Audrey, in creating appealing knitting patterns?
How does the addition of a step-by-step slideshow feature for knitting patterns affect the ability of beginner users, particularly Carrie, to understand and follow traditional knitting patterns?
Tasks
Tasks were chosen based on the hypotheses set in the previous stage of this project to assess if the application was fulfilling it’s intended purpose.
Tasks were chosen based on actions anticipated to be taken by all user types.
Users were provided with example data for any task requiring them to enter user data.
Task order was kept the same across all participants.
Participants
Participants were chosen keeping in mind the desired target groups set in the research stage of this project.
Participants falling into both persona types were chosen to evaluate the prototype.
Procedure
Testing sessions were performed remote using applications such as zoom.
Potential participants were given a screening questionnaire and then asked to test provided they match the participant criteria above.
Participants were allotted twice the expert completion time to allow for more than sufficient time to complete the task, while not causing excess frustration.
After completing the tasks, participants were given the opportunity to discuss their overall feelings towards the prototype.
Upon completing the tasks, participants were given a SUS-standard questionnaire to complete.
Features
Customise Patterns
Made a pattern but it’s not exactly what you want? Make adjustments to the design and Icanknitthat will adjust the pattern.
Problem statement
Users found knitting patterns that they were interested in creating, given that they could make some alterations while still being able to follow a pattern.
Solution
Users can customise their knitting patterns to change aspects of the pattern’s design or select from the size inclusive options.
Create a New Knitting Pattern
See a knitwear piece you like? Take a picture and upload to our application. Icanknitthat’s technology will create a knitting pattern with step by step guidance on how to create it.
Problem statement
Users could find knitting pieces out in the world that they wanted to wear, but struggled to find knitting patterns that matched what they were looking for.
Solution
Take photos of knitwear pieces you find and Icankniththat’s technology will build a knitting pattern for you. Users may also browse through a catalog of knitting patterns created by other users.
Follow Along With Your Knitting Pattern
Unsure of how to complete the pattern? Icanknitthat knitting patterns include both detailed written instruction and video tutorials for each step in the pattern. Users may also bookmark or leave notes for themselves to return to a step later.
Problem statement
Users wanted clear and interactive knitting patterns.
Solution
Users can learn how to complete their next step in the knitting pattern through video and written tutorials, bookmark their spot in the pattern, or leave notes about each step.