Digital Collaboration and the 21st C.

With new tech-enabled features, the store of the future will be able to provide a more frictionless and personalized experience that meaningfully engages shoppers. The following infographic visualizes the expected 2030 in-store journey for a customer named Rachel. Here are some of the technologies and innovations that will impact each step of her shopping experience.

Organizations should first consider how the behind-the-scenes logistics of their “Full Service 2.0” offering will be best facilitated by advances in technology. Ride-sharing services could provide a chauffeur-like experience by modifying their algorithms to allow a user to request trips with the same driver instead of the first available car. Hotels may accelerate the introduction of robots to handle room deliveries or other in-room services in a socially distant manner. Technology gives organizations new options to address the previously high costs of high-touch, full-service models or the uncertainties around service and delivery times that turned away consumers from these services.

Integration, Speed To Insights, And Real-Time Decisioning Matter Most For Orchestration

Vendors that take a technology-agnostic approach to integration can deliver insights at speed across all permutations of journeys. They also have a proven track record in real-time decisioning across a wide variety of systems and can help companies drive business results and CX differentiation.

Aura connects to the existing cameras of the location you want to monitor. Thanks to a plug and play installation, Aura will be functioning almost instantly; while the results will be available in the next 24 hr. Besides the general demographic information such as age, (7 range are provided) and gender; Aura can, as well, help to monitor what the customer is doing. The latter is possible by providing: Footfall, Area dwell times, Heatmaps, Service wait times. 

Why Technology is Core to the Evolving Retail Landscape



Data and analytics are key to any retail strategy, but what’s the best way to deploy these insights with digital signage? Samsung’s Harry Patz explains how retailers can create actionable insights from customer data. Credit Samsung Busin

The challenge of search and recommending products online is increasingly being solved with data science as e-tailers compete on personalisation. New e-commerce platform Psykhe makes recommendations based on personality traits by identifying both the user and the products; its models can assign products a “personality profile”, informed by traits such as openness or neuroticism, in addition to traditional details, without human input. Resale platform Rebag has developed a universal taxonomy for designer handbags to better appraise products. And Facebook recently unveiled GrokNet, a tool that automatically identifies and describes items in pictures to help people sell items on its marketplace.

Learn how you can combine the power and data across a single cable to reduce cabling, improve safety, and simplify installation.

The trends in this report — while buttressed by data and evidence — are meant to shake our faith in steady trend lines. They point to areas where conditions are ripe for discontinuity and disruption. This report asks us, in effect, to “watch these spaces,” and expect to see surprises and opportunities. In that spirit, here are 14 tech trends that deserve close attention in the first year of the 2020s

Chinese startup UDI deploys self-driving vans to deliver food to lockdown areas. To do that, the startup has hired 100 employees and is preparing to put its assembly line into high gear in the next several months. “I’m not saying we solved all the problems,” Professor Liu says, citing system integration and cost as the biggest challenges. “Can we do better? Yes, it can always be better.”Click here to edit the content

When Google researchers presented a deep bidirectional Transformer model that addresses 11 NLP tasks and surpassed even human performance in the challenging area of question answering, it was seen as a game-changer in NLP/NLU.