Impact of Machine Learning on Optimization & Personalization
Have you ever wondered how Netflix manages to get your movie preferences so right? Every time you go to Netflix, they show you a different combination of movies and television shows. And if you think about it, what they offer you is usually a good approximation of your tastes.
Similarly, think about your visits to Amazon. Every time you return to the site, they suggest items they think you would like to buy. In most cases, their predictions match your tastes, and budget permitting, I am sure you have considered purchasing what they suggest.
Netflix and Amazon are just two of many companies who use machine learning, artificial intelligence, and intelligent automation software to improve their customer experience.
What is Machine Learning?
Leading companies now use machine learning to allow them to provide personalized service on a mass scale.
Machine learning uses artificial intelligence to allow computers to learn independently of direct programming. In the “old” days, computers could only learn something if they were told it explicitly in their programming, e.g., COLOR=RED. Now computers can search through data and identify patterns. They modify their actions based on these patterns.
At a simplistic level, the Netflix algorithm may notice that you have binge-watched the first three episodes of Riverdale. It will learn from this that you are probably interested in Riverdale, and you would appreciate being served with the option of watching Episode Four of the show.
Of course, the Netflix algorithm is much more advanced than that. It has access to the records of every user. It can spot patterns. It recognizes when your tastes are similar to other people. They have shown their approval for particular shows, so the Netflix algorithm is likely to suggest those shows to you. At the same time, it may notice that typical followers of a particular show dislike a genre, so it avoids showing you any programs from that genre.
Machine learning gives opportunities for enterprises to process massive quantities of data, and discover trends and patterns. This gives them the chance to optimize systems and provide personalized service to their customers.
Businesses can obtain data from a wide range of sources. They are even beginning to use facial detection software to personalize marketing to individuals. Their intelligent automation software learns from the emotional reactions the consumers display and adapts its future marketing messages accordingly.
Using Machine Learning and Intelligent Automation to Personalize Customer Service
Enterprises are discovering they can improve customer service, and in turn, the customer experience, by combining historical customer data, complex algorithms, natural language processing, and even emotion analysis to better predict customer wishes.
Call centers are starting to use predictive analytics software to reduce the need for repetition and improve the customer experience. This software continually adapts and provides agents with up-to-date, relevant information to improve the call quality and improve the customer outcome.
Forty four percent of US consumers say they prefer interacting with chatbots than humans. If an organization uses sufficiently intelligent algorithms, it can lead to a deeper, more satisfying experience for a consumer.
Retailers Use Machine Learning to Adapt to Events Quickly
Retailers can use machine learning to speed up their reaction to external events.
Walmart is one business which has experimented with machine learning. They have a vast inventory range, and it can be challenging to ensure that they have the right product mix in each of their stores at any given moment. The sheer scale of Walmart’s operations makes it difficult to adapt to their environment.
Walmart now uses artificial intelligence models to better predict the optimal inventory mix for any particular store on a given day. They aim to be at the forefront of retail personalization.
For instance, they feed weather information into their systems so that they can adopt store stock to reflect customer demand better. They know that a store in an area where a hurricane is forecast will have increased demand for things like bottled water, sandbags, and wet/dry vacuums. Walmart knows to rush ship these items from their distribution centers to that store. The more weather events there are, the more the system learns customer demands.
WorkFusion Can Help You Use Machine Learning and Personalization to Optimize Your Business Performance
WorkFusion can help companies automate human data analysis by using machine learning algorithms. It can help enterprises combine human intelligence with machine learning to create a more optimal, better-personalized experience. WorkFusion can radically improve data quality, speed, and ROI. And all interested parties will welcome the increased insight it provides.
