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Top 8 Real-Life Predictive Analytics Use Cases

Predictive analytics refers to machine learning algorithms and statistics to predict future outcomes and performances. A technique like data mining and predictive modeling estimates the likelihood of future results and alerts you about upcoming events to help you make decisions.

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:

1. Churn Prevention

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 of leaving. Businesses can make the necessary modifications using predictive data to keep customers happy and satisfied, eventually protecting their revenue.

Key Industries: Banking, Telecommunications, Retail, Automotive, Insurance

2. Customer Lifetime Value

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 allows the business to optimize their marketing strategies to gain customers with the most significant lifetime value towards your company and product.

Key Industries: Insurance, Telecommunications, Banking, Retail

3. Customer Segmentation

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.

Key Industries: Banking, Pharmaceutical, Automotive, Retail, Insurance, Telecommunications, Utilities

4. Next Best Action

Determining your primary marketing goals and customers is a critical use case for predictive analytics. It only provides an incomplete picture of what your marketing approach should be.

Predictive data analytics is the best way to approach such individual customers within given segments and analyze everything, from buying patterns to customer behavior and interactions, which offers you insights into the best times and modes to connect those customers.

Key Industries: Banking, Telecommunications, Insurance, Education

5. Predictive Maintenance

In businesses, maintaining cost plays an essential role in increasing revenue. It is difficult for an organization with a significant investment in equipment and infrastructure to manage capital outlay. It’s where predictive maintenance machine learning techniques come in.

By analyzing the insights and metrics of the maintenance cycle of technical equipment, companies can set timelines for maintenance events and upcoming expenditure requirements by streamlining the maintenance cost and downtime. You can simplify your maintenance costs by performing actions that can increase the lifespan of your equipment.

Commonly, most systems become inoperable during maintenance. Predictive analytics use cases will help you with the best time to perform maintenance to avoid lost revenue and dissatisfied customers.

Key Industries: Automotive, Logistic & Transportation, Oil & Gas, Manufacture, Utilities

6. Product Propensity

Product propensity combines purchasing activity and behavior data with online behavior metrics from social media and e-commerce. It enables you to identify the customer’s interest in buying your product and services and the medium to reach those customers.

It helps to correlate the data to provide insights from different campaigns and social media channels for your business services and products. Predictive analytics applications never fail to maximize those channels that have the best chance of producing significant revenue.

Key Industries: Banking, Insurance, Retail

7. Quality Assurance

Quality assurance is key to your customer experience and the bottom line of all your operational expenses.

Ineffective quality control will affect your customer satisfaction scale and ultimately impact the revenue and market share. Also, it leads to more customer support costs, warranty issues, and repairs for inefficient manufacturing. Industries using predictive analytics use cases can provide insights into potential quality issues and trends before they become critical issues.

Predictive analytics use cases can help identify high-risk modules in your application, prioritize critical areas, and reduce time to market through shift-left testing. With predictive analytics, your approach to QA shifts from reactive to proactive.

Key Industries: Pharmaceutical, Manufacturing, Automotive, Logistics and Transportation, Utilities

8. Risk Modeling

Prevention and prediction are two sides of the same coin. Risk comes in various forms and initiates from a variety of sources. Predictive analytics can draw potential risk areas from significant data insights from most organizations.

It sorts them to analyze the potential risks and suggests the development of situations that can affect the business. By combining the results of the predictive analytics applications with the risk management approach, companies can evaluate the risk issues and decide how to mitigate those risk factors.

For instance, health organizations generate risk scores to identify the patients who might benefit from enhanced services, preventative care, and wellness consultations.

Key Industries: Banking, Manufacturing, Automotive, Logistics and Transportation, Utilities, Oil and Gas Utilities, Pharmaceuticals

Read about all the use cases - 17 Top Use Cases of Predictive Analytics.



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