The ‘Edge’ of New Computing – and What It Means for CX

By Allan Frank

The ‘Edge’ of New Computing – and What It Means for CX

Consider these three scenarios - in California, a project is underway that will enable traffic lights to integrate with connected vehicles, thereby freeing people from having to wait in their cars at empty intersections. A mining company deploys Internet of Things (IoT) sensors on their trucks to continually track and prevent goods in transit from being stolen for resale. A large supermarket chain deploys sensor-laden interactive shelves to detect shoppers, monitor foot traffic, and analyze shopping habits to offer them personal pricing coupons and product suggestions.

In each of these scenarios, what’s really happening is that a huge amount of data is being collected, processed, and analyzed in order to provide meaningful, actionable results, whether it be from cars and traffic lights, mining trucks or supermarket customers. IoT is revolutionizing the world as we know it. By 2020, it’s predicted that over 50 billion smart devices will be connected to the Internet, all of them sending trillions of pieces of data that can be analyzed and potentially turned into actionable insights.

Referring to the many remote smart devices that, in effect, exist at the farthest reach of the network, this architecture is sometimes called “edge computing”. Edge computing is a logical extension of cloud computing. The ‘cloud’ allows users and enterprises with various computing capabilities to store and process data either in a privately-owned cloud, or on third-party servers, giving rise to a gamut of operating models including SaaS, IaaS, and PaaS to name just a few. However, the sheer amount of data generated today is growing to over 1.6 zettabytes1 by 2020, according to ABI Research. This “Big Data” requires special vast amounts of storage and compute power to process in real-time.

EdgeComputing-250.jpg (Print) Edge computing is characterized by devices that generate large amounts of data at the ‘edges’ of the network such as smartphones, autonomous cars, traffic lights, or other IoT sensors and the like. These devices may store some or all of their data locally (at the source) to enable real-time processing, and transmit only the data that is required for later use to the cloud or in order to leverage large pools of computing power.

Customer Experience Redesigned

The notion of a “smart city” infrastructure of interconnected devices like streetlights, parking meters, and surveillance cameras is a frequently used example of edge computing at scale. There are many other real-life scenarios with the potential to transform the way businesses connect with their customers in new and different ways. Near real-time data analytics allow businesses to:

  • Gather instant intelligence and consumer insights
  • Custom target content dynamically
  • Provide experiences using geo-targeting or device targeting
  • Enable dynamic customer surveys and feedback

One of the largest retail chains in the world uses near real-time analytics to reduce cart abandonment and improve customer engagement. Using a combination of sensors and beacons that link to customers’ smartphones, the company can gather unprecedented insights into customer behavior and transactional history to better target merchandise and sales promotions. The data is also used to help redesign store layouts and influence product placement to improve the in-store experience for the customer.

Another example of edge computing comes from a tech startup that LiquidHub is currently working with, TAPPTEK, that has recently introduced the use of IoT sensors in Beer Taps. The technology creates a unique way for beer marketers to influence the consumer at the point of purchase in a bar or restaurant. IoT sensors are hidden inside actual beer tap handles; with every handle pull, the sensors relay the quantity of the frothy beverage poured. That data is transmitted out, aggregated and, along with a video display, is transmitted back to the bar where the total amount consumed is tracked and presented visually as part of a marketed beer promotion using a game motif. For instance, a marketer can create a contest whereby, donations are made to a specific not-for-profit based upon the amount of beer consumed in a given period of time. As I write this, TAPPTEK technology is taking the beer industry by storm as it introduces this unique capability in pilot tests across the country.

The possibilities are endless. As businesses increasingly thrive on engaging the customer at every touchpoint of their journey, the ‘Edge’ is definitely here to stay.

Footnote1: 1 zettabyte is 1021