Submitted by admin on Thu, 08/18/2022 - 17:02

Poor in-store customer experience

Sequence Number 3 Industry Retail Banner Poor in-store customer experience How 5G enabled

Personalised (and potentially immersive) experiences enabled by 5G; improving overall customer experience, leading to increased revenues.

Data Flows
Title Devices Icon Devices Description
  • Mobile phones and smart glasses that function as sensors for locational and user-consented data etc.;
  • Cameras and sensors deployed to identify customer purchasing behaviours
Title Connectivity Icon Connectivity Description
  • Camera images
  • Other relevant data
Title Edge Compute Icon Edge Compute Description
  • Time critical interactive content running on the edge
  • Smartphones, smart glasses etc. could also function as edge devices
Title Cloud Compute & Storage Icon Cloud Compute & Storage Description
  • All edge data collected stored to train AI algorithms
  • All data is stored at the Enterprise storage
Title Applications & Services Icon Applications & Services Description
  • AI (MV) to, optimize pricing, identify shopping patterns (e.g., spotting crowd bottlenecks), create personalized offers
  • MV also used to display immersive (AR) content direct to users’ smartphones and smart glasses
Title Inform Decision Makers Icon Inform Decision Makers Description
  • Real-time interactions and personalised messages for customers in CRM base
  • Targeted advertising overlayed on display of smartphones and smart glasses; Bi-directional interactions enabled between retailers and their targeted audience
Title Support Decision Making Icon Support Decision Making Description
  • End of process
Application Logic
Description
  • Deploy low-cost cameras at various critical locations around the store for data collection
  • Consumer-facing smartphone (and smart glasses) applications can be used to collect sensor data on shoppers in real-time using motion, imagery-based sensors (e.g., tracking physical and eye movement)
  • Relevant data will be stored either on-site or in an enterprise storage to manage multiple sites
  • Displays with personalised messages
Description
  • AI (ML) models will analyse users’ behaviours, spending and consumption patterns etc. to provide richer, targeted insights retailers. MV could be used to track eye-movement to understand shoppers’ viewing patterns
  • AI (ML/MV)-driven analytics could also be utilized to assess consumers’ engagement with products and in-store campaigns. These analytics will be rich sources of information for marketing teams
Description
  • Models could provide data to improve customer experiences:
  • Satisfaction levels with service personnel
  • Busy hours simulation to ensure sufficient service staff
  • Recognition of regular customer to push promotions in real-time (either via smartphone app or via XR-enabled device) based on customer-specific historical data
  • Displays in shop for personalised messages (e.g., pricing, etc.)
  • Robots for personalised messages
Expected benefits Key value created