Machine learning and Artificial Intelligence can be referred to as one of the breakthroughs in technology advancement in the 21st century. This cannot be talked about without talking about Big Data and how data processing has seen a completely new landscape when it comes to data processing.
This is because Big data has not just allowed the gathering vast amounts of data but also finding out ways of analyzing that data to identify trends, consumer behavior and different consumer preferences. What is important to understand is that along with technology, consumer behavior is also constantly evolving and it is technologies like these that will make all the difference. Let us look at some brands that have used these technologies to their advantage:
One can’t talk about machine learning without talking about Google. Google’s parent company, Alphabet, has been working on listing different areas in the field of scientific R&D which have included explorations into anti-aging technology, inventions of medical devices and of course, the much talked about- neural networks. One of the most exciting developments in Google’s neural network has been the “DeepMind Network” or “The Machine that dreams”.
This example is perfect for understanding how different companies are using Machine Learning to anticipate and predict customer behavior. Walmart has recently tested facial recognition software to create an effective anti-theft mechanism.
However, this software has gone beyond just serving anti-theft needs as it is also being tested out for customer service related problems. The problem that has been recognized as one of customer service is an expensive affair and in order to cut down on staffing issues, the facial recognition software will be used at checkout counters to check the frustration level of the customer. This information will then be relayed back to the nearest customer service executive for resolution.
IBM has transitioned from being one of the oldest technology companies to be at the forefront of adopting newer technologies. Their latest addition, IBM Watson is one such example. IBM Watson is being used in different hospitals and medical centers to make accurate recommendations in the different kinds of treatment response for cancers. This has also been extended to the retail sector where Watson can be used as an assistant to help shoppers.
Alibaba has used machine learning in understanding offline customer behavior. One of the major achievements of Alibaba has been to decentralize the process of data processing, giving different retailers that are part of their ecosystem, a chance to understand the larger scheme of things. This has been specifically targeted towards offline retailers where shoppers can order online for their delivery through their grocery store HEMA. Or they can make an in-store purchase, pay via their application and get free delivery even for their in-store purchases. How is this beneficial? This gives retailers and Alibaba an idea of how customers are using their mobile applications in the context of an in-store purchase.
Facebook Messenger has recently mobilized an army of chatbots. Anybody, even with limited resources, can create a chatbot for Messenger. This can be particularly beneficial for companies that are investing heavily in customer service and customer retention. Having said that, Facebook is also leveraging Machine Learning to sift through poor content and eliminate it.
One of the major successes behind Netflix’s extremely effective interface has been done through their adoption of Machine Learning. This is an example of a company that has adopted Machine learning to understand how their consumers consume their content. Auto-play features and show recommendations are all based on this technology.