What Can Predictive Analysis Help Your Company?

What is predictive Analysis?

Predictive analytics involves advanced statistical, modeling, data mining and one or more machine learning techniques to dig into data and allows analysts to make predictions. Predictive analytics is used to forecast what will happen in future.

For any kind of business, the ability to generate predictive analytic which enables businesses to identify potential events and opportunities, and either avoid or capitalize on them, as the case may be. In order to identify the indicators of events and opportunities, the use of data to make predictions that benefit the business.

The real value of predictive analysis can best be illustrated by describing the major use cases that exist in business today, below are the main 7 use cases and applications.

1. Churn Prevention

According to Neil Patel’s article on their website, the most famous SEO and online traffic expert. Predict churn can help massively for subscription model business.

2. Customer Lifetime Value

Measuring customer lifetime value is highly used on retailer and media industries. Predict customer lifetime value can facilitates marketing decisions and budget.

3. Product Propensity

Propensity modeling tracks customers buying habits as well as other actions such as opening a marketing email, signing up to a loyalty program, or participating in feedback surveys. The model correlates customer characteristics with anticipated behaviors or propensities.

4. Sentiment Analysis

Sentiment analysis is the process of determining the emotional tone behind a series of words, used to gain an understanding of the attitudes, opinions and emotions expressed within an online mention.

Sentiment analysis allow retailers and brands alike to understand the opinions of consumer feedback and User Generated Content. Is it negative or positive? What is the context of their opinion? Are they talking about the product or just a feature within the product?

As a result, more and more companies are using sentiment analysis to make sense of the huge amount of consumer feedback that is coming their way and it helps to drive conversion.

Shop.com, for example, is using sophisticated sentiment analysis and Artificial Intelligence technologies to analyze online opinions about the products they sell. Moreover, those opinions are then displayed on product pages and across the site and are turned into actionable insights and recommendations. Now shoppers can find the answers according to their own specific needs.

5. Up- and Cross-Selling


Amazon attributes up to 35% of its revenue to cross-selling – both the “Frequently Bought Together” and “Customers Who Bought This Item Also Bought” 


 JetBlue’s “Even More Space” initiative, which allows passengers to buy seats with more legroom. This upsell was projected to net JetBlue $190 million in additional revenue in 2014 (compared to $45 million in 2008, when it first launched). Even broader, let us consider statistics from the travel industry: 48% of airline passengers and 59% of hotel guests are interested in upgrades and additional services

The Value of Predictive Analytics

Those use cases mentioned above are widely needed in the current businesses. If your company has not started to have a plan to implement predictive analysis, the company will suffer extremely lose of money. With predictive analytics, your company can have a proactive approach to the increase the revenue and reduce the costs. Predictive analysis can help you to plan for the future, and identify new areas of business.

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