My Grace Hopper conference schedule this year was largely driven by my interest in learning as much as I can about all things Internet of Things (IoT), retail, and edge computing. Why? I’m glad you asked! I recently joined the Internet of Things Group (IOTG) as a Software Architect in Retail, Banking, Hospitality, and Education (RBHE) <– Intel loves acronyms. I wanted to take the opportunity to learn what emerging technologies can be applied in retail settings, and understand some of the challenges that are present. My background is data center and cloud infrastructure automation, so the retail space and managing a heterogeneous set of devices with varying network architecture requires a different, or at least modified, set of tools.
My first session was titled: Mirror, Mirror on the Dressing Room Wall, What Looks Good with This Dress? Presented by Allison Youngdahl and Sunil Shettigar, of Accenture, this presentation explored how brick-and-mortar stores can improve customer experience and give better data to retailers by leveraging IoT.
We have grown accustomed to a very individualized experience online, but in real life (IRL), walking into a retail location is one size fits all. E-commerce sites track our behavior, purchasing history, make recommendations, and often have free shipping and returns to seal the deal…but, once we receive the item in hand, we’re likely to return it nearly 80% of the time. Why? Just Google “online purchase fail,” and you’ll find pages of hilarious results:
We want to touch and feel an item, in fact, shoppers who try an item in a store are seven times more likely to purchase it, so the dressing room plays a vital role in sealing the deal. Fashion designer Rebecca Minkoff leveraged technology — interactive mirrors paired with RFID tags and a video wall, in her stores to drive triple digit sales growth. So what is the architecture behind such a successful solution? Allison and Sunil presented the solution Accenture Labs partnered with the Council of Fashion Designers of America (CFDA) to build.
The Retail Interactions Platform allows retailers to:
- Understand the customer journey as they move through the store
- Track total number of visitors in the store
- Track item interaction from a clothing rack
- Determine when an item is taken to a dressing room
- Understand how item interaction leads to a purchase at the point of sale
Underlying technology:
- Estimote Sticker Beacons (Bluetooth proximity sensors for physical objects)
- Business Analytics – Calculate the product engagement score
- Video analytics – heatmaps for traffic during peak hours
- RFID Tags
- MAC sniffers – Raspberry Pi with a WiFi adapter
- Data visualization dashboard hosted on Google Cloud Platform
- RESTful APIs
Product tracking was accomplished using RFID tags to “see” how the product moves through the store. Data streams from the various sensors were aggregated using Google Cloud. To track the number and frequency of visitors, the MAC sniffer identifies the MAC address of cell phones probes, which have a unique identifier, and quantify how long the individual was in the store as well as the frequency of visits. An engagement score was determined by capturing the XYZ coordinates of the product from the Estimote beacon (was it picked up and handled? For how long?); all of this is available in a dashboard.
So how does this relate to mirrors?
Dressing room ambiance — temperature, lighting, music, can change how you feel about an item of clothing. Hate harsh, unflattering lighting that accentuates all of your flaws? So do I! So how can you make dressing rooms more hospitable places? Using the platform, you now have the product location, and with additional IoT devices in the dressing room, retailers can modify the environment, and also get immediate customer feedback on a product (new size needed? A different color?) to better serve you:
The final take away was that retailers should focus on customer education, entertainment, and community. As much as an e-commerce site is convenient, it can never compete with a great experience IRL.