Predictive Analytics – Machine Learning – Artificial Intelligence – Use Cases

Today, businesses regularly use predictive analytics to analyze the target customer to gain operational insights and results. 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 customers at most risk for leaving. Businesses can make the necessary modifications using predictive data to keep customers happy and satisfied, eventually protecting their revenue.

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

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.

4. Next Best Action

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.

5. Predictive Maintenance

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.

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.

7. Quality Assurance

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.

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 collected from most organizations.

By analyzing the potential risks and suggesting 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.

9. Sentiment Analysis

However, by crawling tools with customer posts and feedback, you can create analytics that can give you a clear picture of your business reputation within the market.

Predictive analytics models provide you with proactive recommendations as the best way to enhance that reputation.

10. Up-Selling and Cross-Selling

Purchasing history data can be utilized to determine which goods and services might benefit from being offered together.

Predictive analytics use case provides suggestions on market segments to increase your customer value and revenue derived from your customer. The business sales are raised, and your customer walks away with items that work together.