Examples of How Marketing Teams Use Predictive Analytics

There’s an integral facet of artificial intelligence that doesn’t get top billing often — and that facet is Predictive analytics . While companies try to integrate it into their daily operations, applying predictive analytics in marketing can help use data and forecasting to enable businesses to make better decisions, save time, and reduce stress.

Marketing professionals use data to understand and improve the effectiveness of their campaigns and initiatives. As marketing evolves, data and analytics have become the foundation of all decision-making and marketing initiatives with various predictive analytics techniques leading the efforts.

Predictive analytics in marketing leverages AI and machine learning to combine the insights generated through various datasets, algorithms, and models to predict future consumer behaviors. In this blog, we’re going to outline different use cases and examples of predictive analytics in marketing and explain how its implementation helped revolutionize different businesses. 

Understanding Consumer Behavior

Predictive analytics can give an understanding of consumer behavior based on past interactions. It allows marketers to segment audiences based on interest and demographic information. 

This equips marketers to design targeted messaging for specific platforms and devices resulting in better performance, customer  experience and loyalty.

Optimize Marketing Budgets

Predictive analytics allows marketers to allocate their budgets based on  consumer behavior. The data can indicate which channels are effective, and what ad schedules result in maximum returns on their spending.

This helps marketers to decide when and where to increase budgets and when and where to cut them.

Prioritize Leads For Better Conversion

Predictive analytics in marketing allows marketers to identify, quantify and prioritize leads based on behavioral patterns. Consumer behavior data and insights enable marketers to determine which audience segments lead to the highest conversion rates.

Predictive analytics identifies how a lead will act with a lead form, a website, or other channels, allowing marketing teams to prioritize the most effective channels.

Customer Retention

Predictive analytics can help marketers to identify cross-selling and up-selling opportunities that can lead  to better lifetime value (LTV) of a customer. Predictive data evaluates consumer purchase history and interests, leading to a better understanding of customers’ needs and the development of products and services that complement them.

Learn to Make More Per Dollar With Predictive Analytics in Marketing

Marketers should always look forward to making their marketing decisions more data-driven to improve their conversion and retention rates. 

Learn to apply predictive analytics in marketing to solve real-world business problems with our Predictive Analytics for Business Nanodegree program

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Ritika Pradhan
Ritika Pradhan
Ritika is the Content Manager at Udacity and is passionate about bringing inspirational student stories to light. When not talking to the amazing Udacity students, she can be found reading an article or watching a video on the internet.