November 20, 2017 | Written by: Peter Sommer
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Artificial Intelligence, Machine Learning and Cognitive Computing are trending buzzwords of our time. I read about them every day in different media, but as a regular customer it is rare that I get a “wow experience” as a result of new technologies. Where are the actual implementations? I have decided to investigate this subject over the next couple of months with the aim of uncovering what new technology can do for the customer experience through specific examples.
New technology opens up new opportunities, but in the very end it’s all about providing a better customer experience. In a digital world, where everything related to product and price is completely transparent, and where the distance between store and customer is shorter than ever, the 4Ps are dying. Instead, we are now talking about the 4Cs: Consistency, Content, Convenience and Contextual – with focus on the customer experience (learn more about the 4Cs here).
In this article, I will primarily focus on explaining the central terms in relation to real life implementations and business value – I am not in pursuit of academic truth on these terms:
Machine Learning provides computers with the ability to continuing learning without being pre-programmed after a manual. Machine Learning is algorithms that learn from data and create foresights based on this data.
A simple example of how it can be used: Building a model, that can predict customer demand by understanding the correlation between sales numbers from a store correlated with historical weather data and local events happening in the area. I can recommend this link, which gives a visual explanation of a specific Machine Learning example.
Artificial Intelligence is when machines work “intelligently”. The intelligence emerges from a business point of view when machines – based on information – are able to make decisions, which maximizes the chances of success in a given topic. By the use of Machine Learning, Artificial Intelligence is able to use learning from a data set to solve problems and give relevant recommendations. If we continue the example from above, we can use the learning about the correlation between weather, local events and sales numbers to create a fully automated system, that decides upon the daily supply shipped to a given store.
Cognitive Computing are systems that learn at scale, reason with purpose and interact with humans naturally. It is a mixture of computer science and cognitive science – that is, the understanding of the human brain and how it works. By means of self-teaching algorithms that use data mining, visual recognition, and natural language processing, the computer is able to solve problems and thereby optimize human processes. Learn more about it here or here. Examples:
Visual Recognition applies a pattern recognition that makes it possible to identify what is in a given photo/video. Based on this, the technology can come up with recommendations or even make decisions. Try the technology here.
A good commercial example is the company ”The Hunt”. The business idea is simple: take a photo of a piece of clothing – e.g. a pair of shoes – and the service will help you track down all stores that sell the product or likewise products. Learn more here and click here to try it yourself.
Natural Language Processing is the ability to understand common sentences while being able to sense the mood – if there is e.g. anger, frustration or happiness and excitement. The technology can be used to create chatbots, which are systems you can communicate via regular talk. The best customer experience I have tried is with The North Face. Here, a chatbot helps me find the exact right jacket. Try it yourself here.
Based on this: does the new technology belong in the future or is it already relevant in the Nordic today? The technology is a reality and it works – but in a Nordic context we are still in the very early stages, and Nordic examples are still few. During the next couple of months I will share with you the best examples of implementations of the new technology that I encounter. I am very interested in learning how you have experienced a better customer experience by the use of new technology?