In-store Mockup Validator
Helping FMCG companies validate their products in supermarket through expressive, data-driven IoT product mockups.
Tools & Methods
Figma, Claude, Lovable Arduino, React.js
Duration
Solo, 5 months
My Role
Graduate Product Designer
Project Overview
I redesigned the In-Store Mockup Validator ™ initiated by Bamboo Brands to be an interactive IoT system that replaces costly, waste-heavy product pilot runs, with playful shelf agents capable of capturing real-time behavioural data.
Bamboo Brands builds in-store validation tools to help companies test new products before they hit the market. The idea was promising, but early tests with a simple mechanical string made shoppers fee “fooled” and “scammed”.
I led the interaction strategy and research to a new system architecture with Artificial Intelligence system to process data and interpret customer’s behaviour. By detecting intent at ≤ 7cm, we turned retail frustration into curiosity while capturing real-time behavior data via Data Foundry.
Problem Space
The current method of validation process of Fast Market Consumer Goods (FMCG) Industry is crucial to understand consumer behavior and ensure commercial success in high speed market. However, current method can be undermined by the attutude behavior gap which is the misalignment between consumer’s stated intentions in traditional research settings and their actual purchasing behavior in real purchasing environment.
The ISMV embeds the IoT technology into interactive shelf mockups to shift product testing to a much earlier stage, before everything is mass-produced.
Requirements
The mockup must visually integrate with the surrounding shelf products.
The interaction should occur at the shelf, with the mockup remaining in place.
The system must be durable and low maintenance for buys retail environment.
Interaction must be unobtrusive to the customer's shopping experience.
The system must capture and store customer engagement data for evaluation by Bamboo Brands.
Research & Discovery
I mixed field research, semi-structured interviews, workshops and rapid prototyping to explore interactions that would result in a delightful user experience in super market
Ethnographic Dive: Understanding the “where” and the “who”
I conducted a contextual inquiry in a local supermarket to observe real shopper behaviors and divide them into 3 categories: Quick (utility-focused), Explorative (browsing for inspiration), and Trying-Something-New (interested but cautious)
✦ Insight: Explorative shoppers were my primary target because they were the ones who's rhythm allowed for an interaction with a new product.
Failure of “Utility”: Why the string prototype felt like a scam
I did a user test where I tested with a lo-fi “string prototype” where the mockup was tethered to a shelf and there’s a counter sensor inside the mockup. This session revealed a deep sense of mistrust; participants used words like “fooled”, “tricked” and “scam” when they realized the product was fake
✦ Insight: I realized that a purely functional solution would damage brand perception and led to poor data reliability. So I pivoted from designing a tool to designing an experience.
The Magic Machine Workshop: explorative methods
I led a “Magic Machine” workshop where I asked participants to express their retail frustrations through abstract materials like sponges and balloons. Over half of the participants chose bouncy, elastic and soft materials which revealed hidden preference for a playful feedback and instant visual response.
Final prototype
The final design was presented in the Summer Demo day 2025 in Eindhoven University of Technology. The client stated that they were content with the result, providing a more interactive and unique approach to gather data from the customer.
Database Dashboard
The ISMV in action! Taken during a university-wide demo day with mini supermarket stand
I delivered a working prototype that is able to:
Do a proximity-first interaction: I replaced string with an ultrasonic sensor to detect a hand approaching at approx. 7 cm, triggering the mockup to “turn” and greet the user before contact
Gestural storytelling: I programmed a servo-based “dance” that responded to a survey participation, creating a playful dialogue between user and the shelf agent.
Phygital Data Loop: I engineered an IoT architecture using Arduino Nano ESP32 and Data Foundry, through vibe coding, the system enabled Bamboo Brands to monitor footfall and dwell time in real-time.
This Graduation project was awarded with 8,5/10.
Read the full report here.
Impact
While the client initially focused on tracking physical “pickup” , my contextual research revealed that customer interest begins well before contact. I discovered that the interaction actually starts at approximately 7 cm away. Therefore, I reframed the mockup from a “fake product” to an expressive character that acknowledges the shopper’s approach. We could turn this initial frustration into a moment of “magical” curiosity.
30%
Increase in user experience than previous model.
2/3
Score in ease of use based on the user testing.
Key Learnings
Business constraints aren’t barriers; they are design parameters.
By mapping the stakeholder value exchange, I discovered how to deliver the high-fidelity behavioral data Bamboo Brands required while protecting the user's emotional experience
Co-creation to prevent tunnel vision and uncovering hidden emotional needs.
This helped me look past the technical brief to find out user's needs that ultimately defined the ISMV’s character
Importance of continuous rapid prototyping
By failing fast and often, I was able to quickly eliminate these unpleasant interactions
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Side Projects
Some other projects that is also worth to show.