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Analytics Definition

Analytics is the systematic analysis of patterns in data. The systematic analysis includes discovery, interpretation and communication. Simultaneous application of computer programming, statistics and operational research forms the essence of analytics. The field of analytics is important especially in areas rich in recorded information. Analytics especially hold importance in business and can be used to describe, predict and thus move forward in business.   Analytics holds within itself a plethora of areas like retail analytics, promotion modeling, credit risk analysis, predictive science, market optimization, store assortment etc.

Analytics is the process of obtaining an optimal and realistic decision based on examining existing data, typically large sets of business data, with the aid of mathematics, statistics, specialized systems and software.

In the last few years use of analytical methods to extract useful insights from data have gained immediate importance and has helped several companies improve their business performances.

Application of Analytics

Marketing Optimization: Earlier considered as a creative process, it has now has evolved more to be a data-driven process. Analytics is now used everywhere right from determining the effectiveness of a marketing campaign to making decisions in a marketing sphere. Using techniques of demographic studies, customer segmentation etc, analytics is now used for a better understanding and communication of marketing strategy. Marketers also use web analytics to collect user’s interactions on a website even at a session level. This is made possible by an operation called sessionization. Google analytics is one of the most popular tools put into use by marketers to serve this purpose. The information collected can then be utilized to serve a variety of purposes like information architecture, improving marketing campaigns etc.

Some of the most commonly used marketing analytics techniques include marketing mix modeling, sales force optimization and prizing and promotional analytics. Now, traditional marketing analysis techniques work together with online campaigns, website optimization etc. This helps organizations in targeting potential customers with the most effective marketing message, through the right medium at the right time.

Predictive analytics:

Predictive analytics help us make predictions about things to happen in the future. Several modern technologies like statistics, data mining, artificial intelligence etc are put into use to make such predictions. The models found in historical and transactional data is being leveraged to analyze and predict the risks that can arise in the future. It accelerates industry or business organization to be proactive and ready for the future, not based on assumption, but on the results of the interpreted data.

People Analytics:

This analytics is used by companies in human resource management. This analytics will help in deciding who to hire, whom to assign duties to, whom to give promotion to and the like.

Portfolio Analytics:

Portfolio analytics is one of the most popular applications of analytics. A bank will have a number of accounts with differing values in it.

The value can change according to the status of the holder, the location etc. A number of factors go beyond lending money by these organizations. Balance, ensuring the maximum return and minimum risk should always be maintained in such organizations. Here they use analysis to formulate the equation on when to lend money to which category of people in order to maintain this balance.

Risk Analytics:

This is carried out especially in the industry and insurance sector. Online payment gateway companies make use of this technology to check how genuinely the monetary transactions made. A common application of this can be linked to credit card transactions. For example, if there is an abrupt increase in the credit card transactions of a customer, he might get calls to check its credibility.

Digital Analytics:

An arrangement of business and technical activity to, collect, verify and change digital data into research, understandings, recommendations, forecasts and so on.

Search Engine Optimization (SEO) is also included in this. Here the access pattern of users is tracked for marketing purpose. The number of marketing firms and brands relying on digital analytics is at its increase in the recent times.

Security Analytics:

Information technology solutions that collect and check on the security events and bring awareness about the situation. It helps the information technology staff to evaluate such events, to come up with solutions.

Risks Involved in Analytics

There are a number of risks involved with analytics. The risk of personal information of users being stolen and used for the developer’s benefits is of the major concerns.

There are also chances of a user’s private information be made public over the internet, given the identity of the user is not securely protected. There is also the risk of concepts and ideas being stolen.

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