Scan & Go Self Checkout
Objective
Our goal is to envision and prototype innovative self-service technologies for payment services in Woolworths, aligning with the company's commitment to technological advancement by 2033.
Our Work
Our team used qualitative research methods like in-depth interviews and observations, guided by Design Ethnography principles, to create speculative scenarios for future interactions with self-service technologies. We employed creative sensory and visual techniques such as photography and videography, analysed data using affinity maps, and incorporated immersive elements like Augmented Reality (AR) to enhance user experiences and explore potential impacts of emerging technologies.
Approach
We adopted a Speculative Design approach, leveraging user insights and qualitative research to create speculative design experiential scenarios. By exploring potential future interactions and experiences, we aimed to anticipate and shape user expectations for self-service technologies.
Data Collection Insights
Rewards and discounts
Users appreciate rewards being automatically added during payment, avoiding extra activation steps.
Some users face issues where discounts don't appear during check-out, requiring staff assistance.
Users express a desire for simplified reward systems.
Compulsive buying and Data trust
Some users are concerned about impulsive buying and overeating when items are automatically scanned.
Users generally trust corporations to use customer data responsibly.
Perception of self-checkout technologies at Woolworths
Some users see little difference between Scan&Go and traditional self-checkout, as both involve scanning items.
Users wish for smoother, lag-free, and glitch-free motion in the self-checkout screens.Users generally like the current system but are open to more convenient technologies.
Users sometimes encounter inaccurate price labels, leading to concerns about pricing transparency.
Users find self-checkout suitable for a small number of items but frustrating for larger purchases, citing an average purchase of 20 items as an example.
Affinity Mapping Findings & Inferences
Our affinity mapping revealed key user preferences: quick and easy experiences, short queues, spacious bagging areas, ethical design, error-free technology, and personalised rewards. These insights will guide speculative scenarios for enhancing user interactions with self-service technology in Woolies.
Relevancy
Shops more frequently
Tech savvy
Wants to buy more items but with no human assistance
Target demographic
User Scenario
Lia has stopped by at Woolworths after her work, for a spontaneous purchase of her weekly necessities. She needs to buy things for her meal prepping, stock up on her pantry and weekly groceries, since she won’t get time again in the next few days due to her busy schedule.
She knows exactly where to find her items and heads towards the checkout since she has a lot of items in her basket.
Primary Persona
This persona is based on the combination of our common interviewees personalities and responses.
Current Journey Map
Future Journey Map
Our Proposal
Combining the aspects of assisted checkout, scan & go check-out technology and smart ai-powered counters we present the following design solution for the problems discovered through this research.
Imagine a self-serving smart checkout counter with ample of space, deep enough to hold at least 15 - 20 items. It operates autonomously and effortlessly scanning the items and handling the entire process simultaneously such as: Profile --> Payment --> Rewards --> Exit.
