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The Many Business Applications of Predictive Analytics

Predictive Analytics is hot field today, not only because it helps in driving smart business decisions, but also because it does that more quickly and effectively. Further, the Big Data phenomenon coupled with the improved data analysis tools has contributed significantly to the ubiquitous adoption of this technique across all major industries & sectors.

So what exactly is the buzz all about? Simply put, predictive analytics uncovers the best action to be taken in a particular situation. The magic of this technique lies in crunching historical data to identify the probability of future outcomes. It goes beyond descriptive statistics to render the most accurate predictions possible. Below is an insight on some of the business applications of this technique, and how it helps companies to optimize their performances and increase revenue:

  1. Determining the effectiveness of marketing & promotional strategies

Statistics reveal that various promotional strategies, such as discounts, special offers, coupons, events, and allied tactics garner varied responses from the audiences. This primarily occurs because each customer segment has different attributes and price sensitivities. The use of predictive analytics helps in determining these customer responses as well as pinpointing interested and uninterested customers, thus enabling the organization to focus all its energies on profitable customers, whilst eliminating those who display the least likelihood to respond to an offer.

  1. Managing business operations

Ranging from airlines, hospitality, consumer products, to banking, most sectors today are utilizing the power of predictive analytics for determining their pricing strategy, managing resources, ensuring seamless business operations, and most importantly, functioning efficiently. While airlines can harness the technology to decide the selling price of each ticket for a flight, hotels may make use of analytics to predict the number of guests that would arrive on a particular evening. After taking into consideration the demand & supply factors, retail companies can develop a predictive model, which would aid them in optimizing the price of a particular product.

  1. Credit scoring

By devising a predictive model, organizations can integrate and analyze the pertinent data related to a person’s credit worthiness, thereby allotting a specific credit score to each individual who has taken a loan. These scores render a fair idea about the likelihood of a default on a house, vehicle, credit card, and other purchases.

  1. Fraud detection

Most frauds exhibit a predictable pattern. By using the right statistical methods and analytical techniques, it is possible to prevent fraudulent activities, even before they actually occur.  With the help of linking analytics and anomaly detection methods, companies can gain insights on cyber-security threats, occupational frauds, recovery of losses, and much more.

  1. Better Patient Outcomes

This technique is seeing a wider application in the healthcare sector. This is because it equips the medical center to make fast decisions about treatments, predict the effectiveness of new procedures/medications, and enhance patient care. Think of a model that can actually predict the probability of a cardiac arrest of a patient exhibiting a certain set of symptoms, thereby guiding the caregivers to immediately undertake the best treatment decision.

  1. Customer Retention

By using statistical algorithms and machine learning techniques, this tool analyzes customer characteristics & behavior and provides valuable insight of those customer segments which have a high propensity of attrition. These insights help organizations retain these customers via communication and lucrative offers.

It is important to note here that the above-mentioned list is not an exhaustive one, and these are only the most pervasive applications of this analytical tool. Other applications include market research surveys, tax collections, predicting & preventing crime, supply chain management, and many more. With growing volumes of data and ever-increasing competition, more and more organizations are reporting to predictive analytics to boost their bottom lines, improve business performance, and drive better decision making.

Acer Innovation is a leading edge data analytics firm providing consulting services across a diverse range of industries. For more information on its use of technology and services provided, one may visit http://www.acerinnovation.com/

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