Experiential Design - Task 2: Experience Design Project Proposal

12.05.2025 - 03.06.2025

Michael Chan Henn Loong / 0363611

Experiential Design / BA of Design (HONS) in Creative Media / Taylor's University
Task 2: Experience Design Project Proposal

INSTRUCTIIONS

Working Process

So after we are done with Task 1, Ian and I started to discuss on which idea do we really want to work on we gone through all the ideas together and recalled on what feedback did Mr. Razif provided us with, after a long debate we locked our target on 3 ideas different ideas.

1. Interactive Product Demos — Sneaker Showcase

An AR experience that lets users interact with sneakers virtually — rotate, zoom, change colours, and even simulate wearing them on their own feet.

Why the idea: 

It creates a more engaging and informative shopping experience, helping users make better purchasing decisions and feel emotionally connected to the product.

How it can work:

Users point their phone camera at their feet or a flat surface.
AR renders the sneaker model on-screen, allowing rotation and zoom.
Tappable hotspots show materials, design details, and cushioning technology.
Optional pressure pad or mat detects stepping motion, triggering animations like a bounce or flex.

Basic user flow:

Open AR app → Select sneaker model → Point camera at foot or surface → Interact with AR model (rotate, zoom, tap hotspots) → save or share a virtual try-on photo.

2. Product Information Overlay — Food & Nutrition Focused
An AR experience that lets users point their phone at packaged foods or fresh ingredients to instantly view nutritional details like calories, protein, fats, carbohydrates, and allergens.

Why the idea: 

Helps users make more informed food choices while shopping or preparing meals, raises awareness about nutrition, and creates a fun, educational experience around everyday products.

How it can work:

Users scan a food item’s packaging or barcode with their phone camera.
AR overlays display key nutritional facts, serving size visuals, and health labels (e.g., vegan, gluten-free).
Optionally, users can compare two products side by side or explore recipe suggestions using scanned ingredients.
Retailers can use special AR markers on shelves to highlight promotions or sustainability info.

Basic user flow:
Open AR food app → Point camera at packaged food or barcode → View nutritional info overlay (calories, macros, allergens, sustainability tips) → Explore related recipes or meal suggestions.

3. Ghost Skater — AR Skate Spot Visualizer

Users scan a real skate spot (like a rail or ledge), and AR animations of tricks—like flips, grinds, and combos—appear in the space. Users can even follow a ghost skater’s path in a racing mode. It's like skate edits, but interactive.

Why this idea:
Skaters visualize their tricks before doing them. This gives them a virtual way to preview lines, share setups, or just enjoy a new way of looking at their favourite spots.

What makes it special?

Ghost skater animations performing real tricks
Trick trail overlays and slow-mo mode
Ghost race mode
Could add community leaderboard later on

Basic User Flow:

Scan a skate spot or marker
AR skater shows a trick or line
User can replay or try to follow it
Optional ghost race mode for fun

Fig 1.0, 3 Selected Ideas

After selected what we are interested in working on, we proceeded with a deeper analyzing on which one is more doable and unique. So both of us thought that the Food idea would be the most boring and money consuming one as we need to keep ordering food to scan and stuff and we need to make sure that the next time when we've set up the target in vuforia the food is gotta look the same if not the target scan is not gotta work. So we kicked that idea out as its not really a good idea for us since both of us doesn't own a cafe or anything.

After kicking out the food idea we were left with my skater idea and Ian's sneaker idea, it was hard for both of us to choose which one to work on as we both like our ideas pretty much. So we decided to start looking for 3D models online to see which idea have more 3D models to use then we will work on that idea. So I've went to sketchfab and looked for some 3D models but sadly there's not much the community can provide me, I've only found two tricks and 2 skatepark models and after giving it some thought doing the skater one would be hard too since we are both not familiarize with animations and stuff, so ultimately we decided to work on the sneakers idea.

After we are done with selecting our idea, we started to do some research on what do we require for our project since we are doing the AR sneaker try on idea we would need the 3D model to actually follow the movement made when trying on the shoe.

Fig 1.1, ChatGPT Suggestions on Set Up

We've also asked ChatGPT on how hard would it be for us to do the centering of the foot and gotten some ideas on how should we proceed with our project in the future as Mr. Razif mentioned before everyone have different size of foot so we need to make the virtual shoe actually fit on different size of foot.

Fig 1.2, ChatGPT Solution on fixing centering the 3D model

ChatGPT also provided us with some solutions but we are not sure whether it'll work for now, but at least we've got a gist on what we've gotten ourselves into.

I've also asked regarding the Vuforia, like would vuforia work well for our project on all the motion tracking

And after comparing Vuforia & ARKit we think ARKit would be a better choice for us be working on our AR sneaker idea as it is more flexible also. We've also asked for permission to use stuff other than Vuforia from Mr.Razif. So after all that research we decided that we will stick to this sneaker idea and started on distributing our jobs and parts, since ARKit is something only open to Apple user and I'm using Apple product so I'm tasked to explore the ARKit and I'll mainly be working on all the center foot and AR virtual try ons, and also since Mr. Razif mentioned that each person need to at least produce one feature, so Ian decided to work on the UI tools kits and also all the information that will be popping up when the users are asking for the infos of that sneaker, so that makes it two features in one app and both of us have our own features to work on.

So after distributing on that, Ian and I started to work on the proposal slides and document for Task 2. So since Ian will be working on all the UI and information layouts and stuff for task 3 so he took the part of visualization and creative direction. I took the overview as well as the research part.

So for overview there is nothing much to do, I started with coming up names for our AR app

Name Ideas:

KickFit: Step Into Style
Try-On Kicks
Sneakpeek
NextStep AR
HoloSneaks
Lace Up in AR
Feet First: The AR Sneaker Try-On
SoleMate AR
Kicks Cam
SneakerVerse
FitXR: Footwear in Mixed Reality
StepSync AR
HyperKick: Immersive Sneaker Demos
Virtual Laces
SnapFit AR

After I came up with the ideas I sent it to Ian and we discussed on which one is better and ultimately we chose Sneakpeek as its a play on the words it’s a pun combining “sneak” (short for sneaker) and “peek” (suggesting a preview), which perfectly describes an AR try-on experience. After deciding our name I continued with our Introduction, Problem Statement and Goals of project.

After all that, I reached the research part where we should have target audience, user personas, user journey map and solutions.

So I started with target audience first it was not that hard to locate our target audience since the ones who would buy sneakers online are mostly young adults and sneaker enthusiasts.

So I created two target audience for our project proposal.

Fig 1.3, GenZ Shoppers.

So the first one I have in mind are the Gen Z consumers the ones who are usually around age 18 - 25 and are used to using technology in their daily lives. Since They’d prefer more fun and interesting ways to shop, especially if it feels exciting and fun to do. So I think they are a solid target audience we can have.

Fig 1.4, Young Adults & Online Shoppers

The second one would be young Adults and Online Shoppers like the ones in their 20s or early 30s tend to shop online due to its effectiveness. But one of the problem with online purchase is not being able to touch or feel the product, especially for items like shoes. It’s hard to tell if the shoe’s gotta look or feel right just by looking at pictures. Which is why they can be one of our target audience since our project can help them solve their problem.

After I'm done with the target audience I worked on the user persona I created 3 user persona for our project and all 3 of them are related to our target audience

Fig 1.5, User Persona 1, Sofia

Fig 1.6, User Persona 2, Aiden Tan

Fig 1.7, User Persona 3, Joshua Lee

After finishing up the user persona I continued with the user journey map, I created the user journey map on canva and heres the result of the User Journey Map.

Fig 1.8, Original User Journey Map

Fig 1.9, UJM

So these are all the stage, actions, feeling and pain points that I have included in the Original User Journey Map. So after locating our pain points I'm supposed to proposed solutions, below are the solutions to all these problems if we included AR features for the users.

Fig 2.0, Solution

So after getting our solution I created a new User Journey Map showing how the users would feel and react after having their pain points solved with this AR sneaker showcase.

Fig 2.1, Updated User Journey Map

Fig 2.2, UJM

Until here all my part are done and it's up to Ian to finish up the other parts.

Below are the Google Doc, Canva Slides, Figjam and Presentation Video.

Google Docs:

Canva Slides:

Figjam:

Presentation Video:

Feedbacks

No Feedback-

Reflections

At the start of this module, I felt quite overwhelmed. Because all the ideas me and Ian came up with are quite hard for us and every single one of the ideas we thought of requires animation skills and 3D modeling which both of us are not familiarize with.

Task 2, however, gave me a chance to reset. We started working on idea that we really think is doable, we went back and forth a lot — changing directions, refining ideas — trying to figure out what would really work and also what are the set ups we need for the project. It wasn’t easy, but I learned a lot just from that trial-and-error process.

Mr. Razif’s feedback on our ideas really helped me. He pointed out the areas that needed more thought and gave us advice that helped us notice stuff that we would really miss out if he didn't pointed them out.

Looking ahead, I’m aiming to carry what I’ve learned into the next task of the project. I want to be able to really make this project work applying everything we've learned into this project. Even though this module has been challenging.

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Michael Chan Henn Loong (0363611)