Machine Learning Helping Analytics in More Ways Than One

access_time April 14, 2019
by   TechmavenitAdmin
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Businesses of every type in the present day are in possession of vast amount of unstructured data generated from a variety of sources. It definitely is beyond the ability of most enterprises to manually segregate and analyze this huge cache of data and make productive use of it. But advances in analytics tools have endowed businesses with an exciting way to leverage this big data: machine learning. Machine learning is a type of artificial intelligence, which provides computers with the ability to act without being specifically programmed. It uses specifically designed algorithms that interactively learn from data, allowing computers to find hidden insights without the need of human judgment or manual segregation. Machine learning, besides, allows organizations to dig deeper in to the mindset of their customers, so much so that you can predict how customers will respond in a given situation. A recent survey by Gartner has concluded that 75%of companies are either investing now or planning to invest in analytics and big data solutions in two years. As a result of this increased interest level, analysts expect big data initiatives to touch $242 billion. Let us now take a deeper look in to the manner in which machine learning, by helping to analyze unstructured data, is helping businesses improve their business performance vis-à-vis their competitors. Gain Competitive Advantage The implementation of machine learning for analyzing data can provide companies with better insights enabling them to learn, innovate and gain definite competitive advantage over their competitors. This is made possible by analyzing the available data and then learning what opinions customers have with regard to certain products and rectify any shortcomings if any. Companies can then deliver products that will suit the general tastes and demands of customers. Besides, using predictive analytics, companies can deliver intent- based personalized products and this will guarantee better customer experience, higher retention rate and higher revenue generation. Helps devise better marketing strategy Predictive analysis done by machine learning and the subsequent insights received as a result, helps marketers understand the market trends, enabling for better customer targeting and decision-making process. It is able to look at consumer data regarding specific campaigns and tell what is appealing to consumers and what is not. Moreover, with its ability to interpret data, marketers can identify the preferences of individuals, tune the marketing campaigns and offer products targeting such individuals. Improving production efficiency Use of predictive analysis in the production and manufacturing sector will help industries better manage their inventories and bring in greater cost savings. The analysis will help companies with better product inventory forecast and avoid the possibility of large unsold stocks. Fraud detection Machine learning and predictive analysis will help companies in fraud detection by the process of recognizing patterns in behavior. By tracking the changes in behavior on a site, ML can spot anomalies that point to the possibility of committing a fraud. This fraud threat can be eliminated by taking preventive actions. Gaining competitive edge The use of machine learning in data analysis will give companies an insight into valuable customer data and see what customers preferences are with regard to certain product features such as price, look and feel, color packing, quality etc. Companies can also tap in to data to see why customers prefer your product to your competitors. Analyzing this customer data and using it to further promote your products will bring in greater competitive advantage , leading to greater business growth.

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