What is Computer Vision and what is CX?

Computer vision is an AI capability that allows IT solutions to extract data from digital images, videos, and other visual inputs, understand it and take or recommend action. It uses cutting-edge ML and AI capability to replace the human eye.

As per Annette Franz, founder, and CEO of CX Journey, “Customer experience is the sum of all the interactions that a customer has with an organization over the life of the relationship with that company or with that brand”

Why is Computer Vision enabled CX important?

As consumers are increasingly embracing digital, many of their transactions and interactions are getting digitalized and personalized. Computer Vision is one of the technologies that enable this personalization, and the possibilities are immense.

What are some of the use cases of improving CX through Computer Vision?

The most common use cases these days are in the retail and fashion industry.

Effective CX in a retail store nowadays depends on hassle-free availability, quick checkouts, and customized offers. This may seem to be difficult to achieve especially during periods of high footfall. Retail Stores can use Computer Vision for quick self-checkout, automatic refilling alerts for empty shelves, monitor customer activity for suspicious behavior, measure footfalls, and do customer traffic management in real-time.

It can reduce waiting time in long shopping checkout queues by automatically alerting the activation of more checkout nodes seamlessly. It can also provide accurate footfall analytics with data on repeat customers in the store etc.

The Fashion Industry is leveraging Computer Vision to create image-based searches for design availability, virtual trial rooms for e-commerce to give a look and feel or to generate new ideas and provide intelligent recommendations. Similarly, it can also be used for the furniture, home décor, and eyewear industry to name a few.

Parking management in large shopping malls can be another use case. Computer Vision can be used for occupancy detection and management based on visual data inputs. Hassle-free parking will optimize the shopping traffic and improve the CX of customers shopping there. This can be extended to many other applications of parking management such as – at airports, public transport parking, or large trade shows or concerts.

 How can you apply Computer Vision to improve the CX of customer support?

Customers need a quick and effective resolution of their needs when they connect with a support center. The optimal CX here would mean minimal waiting times and minimal steps in an effective resolution process.

Customer Care centers can be upgraded with Computer Vision enabled Virtual Assistants. It can extract details, authenticate customers and automatically fill details based on visual data inputs of the customer or the product. It can zero in on objects in stills or videos provided by customers and recognize details like category, model no., and manufacturer.

Advanced solutions also have the capability of detecting the operational status of components of a device and detecting faults with high accuracy even for poor-quality images provided by customers.

 How can you apply Computer Vision to improve the CX of air travel industry?

Air travel passengers choose an airline based on the CX offered, besides cost and convenience. Computer Vision can help provide a better CX with intelligent baggage handling, quick check-ins, advanced airport security capability, better aircraft traffic management with the least delays, real-time snag detection of aircraft and in the airport infrastructure. It can also pull up details of repeat passengers for in-flight staff for a better and more customized flight experience. A customer would be delighted with the more customized, hassle-free, delightful, and on-time experience.

Do you think the time has come for Computer Vision to transform CX across domains?

The applications of computer vision are endless and can be used at every node of customer interaction that involves vision to create a better customer experience. It generates a large amount of accurate data for optimization of the experience with analysis and insights in real-time. Businesses that care for their customers want to provide a high customer experience that CX enabled with Computer Vision can provide.

Computer Vision-enabled CX is happening now!

Author:

Nitin Rai is the Vice President of Marketing and Growth Initiatives at IGT Solutions. He has spent over two decades working with leading information technology service providers and is currently enabling various aspects of Marketing, Demand Generation, CX, Digital, MarTech deployment, PR, and Communications at IGT Solutions. He aims to help the organization attain an enviable position as a leading Digital CX, Data, and Digital services provider in the chosen industries, globally.

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Frequent flyer programs were one of the first methods airlines used to gather customer data. To stand out from the crowd and gain a loyal customer base, they offered special services like lounge access, duty free shopping etc. to their frequent flyers. When customers signed up for a frequent flyer program, airlines got access to their data. As technology advanced, airlines were able to gather large amounts of data such as the location of the purchase, frequency of travel etc. Once considered key elements of a retention strategy, is now recognized as an efficient way of gathering user data.

While there are certain laws where airlines belonging to a certain geographical boundary (European region) are not permitted to use personal data from historical bookings available within the airline reservation system, other regions who don’t have such strict rules, started building profiles for their customers to market tailored messages to them. Over time airlines started integrating data analytics with loyalty program information to segregate customers based on the number of times they flew and money spent on auxiliary services. Data analytics helped airlines gain insights on customer behavior and preferences by looking at their travel history and spending patterns. By applying predictive analytics to this information, airlines were able to predict customer needs for the future by analyzing when they are likely to plan their next trip. With the help of predictive analysis, airlines can now shoot out customized offers on flight tickets, in-flight services, non-stop flights etc. The more the data, the more the analysis and more the opportunity to target their audience at the right moment.

As time progressed, analytics got integrated with customer data to cater to the ever evolving traveler. To diversify themselves, airlines partnered with other airlines, hotels, car rentals and credit card companies to not just gain further insight on their spending habits, but to offer customized catalogues and services based on the behaviour and preference of the user in terms of food, shopping and other interests.  Many airlines offer unique and useful purchasing options; Qantas frequent flyer members for example can use their miles to pay for their healthcare insurance or even buy a Jaguar!

Airlines don’t just want to be known for their air rewards but a brand that offers an assortment of rewards. It’s not just the airlines that have to gain, customers equally benefit from the information they submit; when their data is integrated with analytics, they are kept up-to-date on new offers, they receive alerts about flight delays or gate changes and their custom needs can also be addressed.

Frequent flyer analytics enable win-win partnerships for coalition partners and customers. In a highly competitive market, service providers in many industries have discovered the importance of customer retention. Airlines are investing and focusing more on frequent flyer programs to increase revenue while adding value to the customer’s overall experience by using the data received from different sources and by gaining insights on the customer’s future needs.

IGT’s analytics services offers significant business insights by integrating multiple data sources using a proven methodology, established frameworks, automated tools, and pre-configured data models for the travel industry

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