In today’s competitive economic world, organizations are relying on the Big Data for better decision-making. Therefore, analytics, has become a significant part of any organization IT road-map, helping to drive more revenue, gain competitive advantages over competitors, risk assessment & risk mitigation and to forecast the future needs.
What is Analytics?
Analytics is the process of analyzing the huge amount of data to derive the hidden patterns and their relationships with an objective to take effective decisions to influence the growth of an organization. The collected data could be either structured or unstructured. Structured data is the data contained in a relational database management system, which stores in a table and on the other hand, unstructured data which is not available in an organized manner and sources of this including files, images, videos, sensor data, social media posts etc..
To name a few of the industries where analytics are being used is the large retailers & e-Commerce, telecom, financial services and healthcare.
Everyone uses analytics in their daily life. For instance, the marketing folks have been collecting customer data and makes recommendation to their managers.
Most prominent analytic tools used to apply analytic techniques are MS Excel, SAS, R, Matlab and SSPS.
Diagnostic analytics is an exploratory process of discovering patterns in data or to conclude why something happened.
Predictive analytics uses historical data to identify the hidden patterns to predict the probability of future outcomes. For example, this type of analysis can be used by large e-commerce companies to analyze the customer buying behavior to cross sell or up sell the products, which leads to increased profit per customer and to make sure for good customer relationships.
Perspective analytics is a type of analysis of data that not only focuses on what will happen in the future, but also why it will happen. This type of analysis is used to derive answers to a specific question and conclusion can be represented on a dashboard.
Application of Analytics in telecommunication industry:
These day’s telecom service provides high consumer focus tends to make use of analytics to unify data from both structured and unstructured data and to draw meaningful insights, i.e. how subscribers are absorbing their services in order to improve their marketing tactics for cross selling, up selling, customer retention and loyalty.
After the introduction of mobile number portability in India, customer retention has become a hectic task for the service providers. To solve this problem, they are using predictive analytics to study the behavior of subscribers who already shifted to other Telco’s and in turn applying the insights on existing subscribers to understand who are likely to shift. Therefore, Telco’s are retaining their customers by providing offers, reduction in tariffs and improving services
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