In today’s competitive landscape brands are running into various innovative technique to pull out the attention, for solving this problem companies are running toward machine learning technology which has the ability to dive deep into the customer data and uncover insight about different trends and preferences which allow future prediction and new angles of interaction between the two ends consumers and companies. Machine learning lets companies personalize their experiences across various channels which were otherwise not possible manually. Let us see how companies are exploring various aspects of machine learning for being in the competition or on the limelight spot, some of these companies are already the masters and rest are evolving to be in the big markets, but in the end all this work together highlighting the user experience and the business related to it.
One who is Pinterest user knows very well that Pinterest has attracted a large number of people surfing for the preferences; it has great influence over the internet and social media system. In 2015 Pinterest acquired Kosei, a machine learning automated system of a commercial application that allows specific content searching and recommendations. This touches the business operations and spam moderation of Pinterest, this also allows additions for the users like email newsletter subscription, monetization of the advertising. This strengthens the ecosystem of the interest which is basically based on the curating existing online content and processing the effective advertisement in the basic priority.
Introduction of chatbot by facebook messenger has snuggled off the difference between the virtual and human conversation. This new feature allows any developer to create as well as submit what not, that is inclusively for facebook messenger. This makes retention of customer services more focused and easier for many startups who have limited engineering support. Facebook has introduced other machine learning applications too like computer vision algorithms which read the image and enhances the visual experience by uplifting the poor quality content. Facebook has also introduced the read option for visually impaired people where the image description can be read out. This new addition has given a different experimental testing dimension to the world’s largest social platform.
On a daily routine, we come across numerous controversies and many of them are created over twitter, why Twitter is catching so many eyes? Answer to this the outreach of the tweet to millions of people in just one tagging system with @ either in replies or comment section. One more aspect of machine learning technology-driven change is the addition of the algorithmically curates twitter timelines that evaluates each and every tweet in real time and score them according to internal scoring and produce them in a chronological driven manner. This allows maximum engagement on the displayed tweets done by the machine learning applications technology which studies the individual preferences and past data and publishes the algorithmically managed feeds which completely change the social media platform.
Google is expanding its database on the basis of research and development which reflects the machine learning ambition of Google. Have you heard of deep mind network that has been recently launched by Google which is the recent update in neural network research of Google? This allows the virtual twist in the classical analog of the machine learning, this also includes natural language processing, speech recognition, and translation which further translates into search ranking and future prediction.
5. eCommerce companies
Gone are the days where retailers have to continue working on the connecting port between the stores and the consumers, e-commerce website retailers improve the experience of shoppers. Increase in the conversion rate edge case streamlines the consumer experience by analyzing the behavioral pattern of the customer and their actions while browsing online content.has changed everything, the introduction of companies like edge case earlier known as comparing metric that has evolved machine learning technology to help
Mazda utilizes digital personal assistant application of machine learning to find influencers to promote their products online especially cars. They use the ML Apps that allows scanning post and reviews online across the entire social media platform and finding the right target indicators through various exclamations and emojis. In turn, people who have experienced the product can post their experience on twitter and facebook. This data eccentric approach influences the thinking of consumer personally.
Have you ever heard of Chinese search engine Baidu that has expanded its user’s database all across the globe thanks to machine learning, Baidu is investing a lot in artificial intelligence lately? Using deep voice process, an automatic neural network system which generates artificial human voice, so real that it’s hard to distinguish between the two. This network system can understand and study really unique human subtitles and pronunciation. This can even create an accurate recreation of the speaker vice and experience.
The latest addition to the company is deep voice system 2 that allow long-lasting impact on the language processing and voice search and voice recognition pattern. This system can be used to explore other voice-based applications in the security system as well.
Being one of the largest and oldest technological companies IBM has managed the transformation of old business models into new business and revenue market. Renowned artificial intelligence system of IBM Watson allows self-learning behavioral model studies. This new technique has been put forward in many institutions like hospitals and medical centers where it provides the best treatment recommendations to doctors.
Watson is being used in retail sectors also where it is used to assist shoppers in offering options and recommendation through Watson ML technology application.
Introduction of the intelligent client management relationship managing system by one of the sharks of tech world system sales force matches the resource and target. Salesforce uses the Einstein business module of machine learning that covers the initial stage points of the customer relationship on both the ends. This allows them in capturing the crucial profiles of the customer allowing comprehensive scoring, lead detection and effective customer dealing service.
Yelp is enhancing the consumer the customer services and experiences by letting users post reviews along with images attached to them. Use of picture classification technology by the company has allowed companies to compile, manage, label and categories the images which are a reflection of the data of the reviewers and their reviews.
With the rapid advancement of technology grants not only ease but more scope for advancing research and development for the researchers. This changes the whole scenario of how developmental landmarks are changing the algorithms, internal architectural and human supervision.
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