Top 17 Real-Life Predictive Analytics Use Cases | 7wData

• Read original article here

Who doesn’t want to predict what actions could keep your business ahead of the curve? Organizations worldwide have automated some portion of their operations, which has increased overall data points and data collection.

As you can never predict for one hundred percent what the future might hold, some practices come close to help you with the plans for the future. predictive analytics is one of these practices.

predictive analytics refers to the use of machine learning algorithms and statistics to predict future outcomes and performances. Technique likes data mining, and predictive modeling estimates the likelihood of future outcomes and alerts you about upcoming events to help you make decisions.

Predictive analytics vendors provide businesses with many product offerings for different domains, which eventually help them to leverage their historical data store by analyzing the complex correlation between unknown patterns and insights. Predictive analytics applications help the business answer questions like “Which marketing strategies might be successful for the product?” or “Is the product acceptable by the Customer in the market?”.

In this guide, we talk about predictive analytics use cases and the corresponding industry verticals. But before jumping on industry use cases for predictive analytics, let us understand what predictive analytics is.

In simple terms, predictive analytics helps to predict future trends and patterns using historical data. It uses different data patterns and identifies the correlations between the variables. It helps to reduce business risks and costs by predicting the future values of certain variables.

For instance, the organization can determine the profits for the coming months by analyzing the output and revenue of the company. The model focuses on two variables; one is dependent while the other is independent. 

There are numerouspredictive analytics modelssuch as classification models, clustering forecasts, time series, etc. These models help predict future variables based on the insights and data arranged in multiple ways.

Today, businesses regularly use predictive analytics to analyze the target Customer to gain operational results. The list of predictive analytics applications in various industries is never-ending. Therefore, below are some of the everyday use cases for predictive analysis in multiple domains:

When a business loses a customer, it has to replace the loss of revenue by bringing a new customer. It proves to be expensive as the cost of acquiring a new customer is much higher than retaining the existing customer.

Predictive analytics models help prevent churn in your customer base by analyzing the dissatisfaction among your current customers and identifying customer segments at most risk for leaving. Businesses can make the necessary modifications using predictive data to keep customers happy and satisfied, eventually protecting their revenue.  

It is pretty challenging to identify the customer in the market who is most likely to spend large amounts of money consistently over a long period.

This kind of data through predictive analytics use case allows the business to optimize their marketing strategies to gain customers with the most significant lifetime value towards your company and product.

Customer segmentation enables you to group the customer by shared traits. Different businesses determine their market differently depending on the aspects that offer the most value to their company, products, and services.

Profound use of predictive analytics techniques helps target the markets based on accurate insights and indicators and analyze the segments of those most interested in what your company offers. Using these predictive analytics applications, you can make data-driven decisions for each part of your business. The same data also enables you to potentially identify the entire markets that you didn’t even know existed.