McLean Donnelly
  • Hi
  • AI
  • UI
  • UX
  • ME

A.I. Meets Retail
​Less Friction, More Sales

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PROJECT OVERVIEW

In the fast-moving world of retail—especially pop-ups and small-format markets—brands need tools that are flexible, fast, and frictionless. I designed a tablet-based retail experience tailored for these environments, combining clean UX with powerful AI to help small teams sell smarter.


  • AI-driven table scan for instant product setup
  • Streamlined checkout with email capture and follow-u
  • ​Real-time sales insights and restock recommendations
MARKET & STRATEGY

​Pop-up stores and small markets are a $50B+ retail segment, offering low-overhead, high-agility ways for brands to connect directly with customers. But most sellers still rely on outdated tools that slow them down. We designed an AI-powered tablet experience built for speed, simplicity, and sales.
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  • 70% lower overhead than traditional retail
  • No-code setup: scan, sell, and follow up in minutes
  • Live AI insights for smarter inventory and promotions
KEY FEATURES
Staff Mode AI product Scan to update inventor and product details
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Retail Tablet eCommerce for Selecting Products for Try on Our By In Store
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Customer mode AI product scan to learn about sizing and AR/VR virtual try on
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Retail Tablet Experience to Allow Self Checkout for Customers
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STAFF MODE

OVERVIEW
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Pop-up retail runs on hustle—and the staff powering these moments deserve tools that work as fast as they do. Enter Staff Mode: a secure, AI-powered workflow designed to streamline setup, inventory, and selling. AI powers real-time product recognition, instant page creation, and automated inventory updates—all from a single camera scan.
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  • Designed for speed: minimize setup and maximize selling time
  • Staff-informed: built from direct interviews with frontline retail workers
  • AI-powered tools that reduce manual entry and inventory management
GENERATIVE RESEARCH

Before designing Staff Mode, we hosted product panels with retail associates, pop-up staffers, and small business owners. We conducted on-site interviews during live market events to observe real workflows and pain points. Insights from these sessions led directly to features like one-tap inventory confirmation and simplified product editing.

  • Manual setup eats up valuable selling time
  • Inventory gets lost or duplicated
  • Staff want smart tools—without needing training



PROTOTYPE & UI

  • Staff accesses Staff Mode by switching from Customer Mode on the tablet interface.
  • A secure PIN is required, ensuring only authorized personnel can view and manage operational tools.
  • Staff Dashboard unlocks essential tools: AI-Powered Product Scan, Inventory Management, Checkout, and Real-Time Sales Insights.
  • Using computer vision AI, staff simply point the tablet at a new product—no barcode or manual entry needed. 
  • AI-driven inventory management syncs scanned products in real time, tracking stock levels, flagging low inventory, and even predicting restock needs.
A secure PIN is required, ensuring only authorized personnel can view and manage operational tools.
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Staff Dashboard unlocks essential tools: AI-Powered Product Scan, Inventory Management, Checkout, and Real-Time Sales Insights.
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Staff Dashboard unlocks essential tools: AI-Powered Product Scan, Inventory Management, Checkout, and Real-Time Sales Insights.
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Using computer vision AI, staff simply point the tablet at a new product—no barcode or manual entry needed. The AI automatically identifies the item, extracts relevant visual and textual data (e.g., logo, shape, label, size), and generates a draft product page with suggested tags and categories.
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The AI automatically identifies the item, extracts relevant visual and textual data (e.g., logo, shape, label, size), and generates a draft product page with suggested tags and categories
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AI-driven inventory management syncs scanned products in real time, tracking stock levels, flagging low inventory, and even predicting restock needs based on historical sales and seasonal trends.
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​AI-powered Sales & Insights Report analyzes real-time and historical sales data to surface trends, top-performing products, and customer behavior patterns—giving staff actionable recommendations to optimize pricing, promotions, and inventory decisions.

CUSTOMER MODE

SUMMARY 

In fast-paced retail spaces like pop-ups and markets, shoppers want quick answers, seamless interactions, and personalized moments. Customer Mode transforms a tablet into a guided shopping assistant.Behind the scenes, computer vision and generative AI make it possible for customers to visualize products, get personalized info, and shop independently—all from one screen.
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  • AI-powered product scan reveals instant AR/VR visualizations
  • Tap to explore details, request try-ons, or ask for help
  • ​Self-checkout designed for speed, clarity, and ease


GENERATIVE RESEARCH

To shape Customer Mode, we surveyed users across in-person pop-ups and digital retail pilots. Our goal was to understand what shoppers need when staff are busy—or when they simply prefer to browse solo.These insights led us to design a lightweight, intuitive UI that makes discovery delightful—and shopping stress-free.


  • Shoppers want to try before they ask—AR helps build confidence
  • Many prefer learning through self-service rather than interrupting staff
  • Checkout needs to feel trustworthy, fast, and frictionless


PROTOTYPE & UI

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IMPACT & LEARNINGS

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AI Technologies Learned
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  • Computer Vision: Scans physical products to identify and auto-generate product pages

  • Generative AI: Creates product names, descriptions, and follow-up email content
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  • AR/VR Integration: Visualizes scanned items in 3D to support customer decision-making


Key Learnings on AI + UX Design
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  • Clarity matters: AI features must feel explainable and trustworthy to gain user adoption

  • Speed is value: AI is most impactful when it shortens or eliminates manual steps
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  • Context shapes use: Staff and customers have different AI needs—tailored UI is essential

Want to learn more about AI and UX?
Check out my  "On the Record" ​podcast episode

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  • Hi
  • AI
  • UI
  • UX
  • ME