The Applications of Machine Learning in the E-Commerce Industry
Not long ago, the thought of artificial intelligence and machine learning seems coming straight out of a sci-fi movie. I mean who in their right mind (except for the few crazy technology geeks and scientists) would have thought that one day the technology would enable machines to operate like a human brain (even better at times). They have the ability to learn, recognize, and identify patterns, as well as, make intelligent decisions on their own.
Well, we live in a different world now. Today, smart machines have taken over all aspects of our lives from personal to professional. All of this progress is owed to the development of disruptive technologies like artificial intelligence, machine learning, deep learning, artificial neural networks, natural language processing, and much more.
While the rise of technology has influenced almost each and every industry that we know. In this blog, we will keep it restricted to the e-commerce industry, which is one of the fastest-growing industries in the world.
The developments in the machine learning technology have opened up massive opportunities for the e-commerce industry, which today goes far beyond what we traditionally think of like analytics. Below we have come up with some major influences of machine learning technology for the e-commerce industry and how the technology is reshaping the industry for the future.
Enhanced Search and Display
The powerful machine learning algorithms integrated into e-commerce stores today enable users to find the right products that they want from their search queries. The search function in e-commerce stores works on the “keywords” written by the users. That’s why an e-commerce store needs to attribute all relevant keywords to their products.
Machine learning improves the search functionality for users using a wide set of synonyms. The algorithms are able to perform searches for the most relevant product using synonyms for the keywords used by the users. This is highly helpful for e-commerce stores, as it’s almost impossible to attribute all possible variations of keywords for a product. The ability of machine learning algorithms to conduct such extensive analytics comes with its strong metrics and analysis powers.
Apart from analyzing the keywords for synonym matching, machine learning algorithms are able to predict the need of customers and show them the best suggestions in line with their needs. For instance, users are able to filter the search results by “Relevance”. It will show them the most relevant products against the keywords that they typed for the search. Moreover, the ability of machine learning to learn and adapt means that the quality of the suggestions will keep on improving with time, thereby, constantly increasing the chances of selling more products for the online store owner.
The rise of the Chatbots is yet another game-changer for e-commerce stores looking to boost their sales and improve customer support services. This is again attributed to the development of strong and robust machine learning algorithms. They are now able to conduct “human” conversation, by understanding the structure of sentences and coming up with the most relevant answers.
The machine learning powered Chatbots can be programmed with the customized store information, as well as, frequent queries made by the consumers. And given the learning and adaptation power of the machine learning algorithms, online stores can be sure of continuously improving the quality of service delivered by the bots. Over time, the bots will be able to understand more and more functions of the store and come up with better answers for the uses.
By adding a machine learning powered Chatbots, e-commerce stores not only reduce their operational cost of hiring 24 hours customer representatives but also greatly improve their efficiencies for customer support services.
A key consideration here is to ensure the privacy and protection of customers’ data. Since most of the Chatbots integrated with the online stores come as a third-party application. There is always a possibility of data collection by the bots on behalf of the company. Thereby, it is important to keep up with the data protection rules and ensure that your customers’ data is always well-protected with you.
What makes Amazon the largest e-commerce store in the industry is partly because of its highly integrated and strong recommendation engine, which again is powered by machine learning. You can take recommendation engines like magazines rack, which remind them of other products that they might be interested to buy. Again, the recommendation engine will continue to learn and adapt to its experiences and predict better products to hook users into buying more products than they originally intended.
Today’s online customers demand personalized shopping experience from the store. With so many choices to pick from, they are only rational to go with the stores that “understand” them and “listens” to them.
In order to meet the high expectations of customers, e-commerce stores need to maintain a complete and updated profile of the user, which can be used to suggest them with the most relevant products/services customized to their preferences. Again, machine learning is enabling e-commerce stores to achieve an incredible level of personalizing by using the behavior data and making intelligent predictions for their choices.