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Increasingly, marketers are embracing the opportunities that artificial intelligence affords by processing data at scale to make better decisions.

Econsultancy’s latest AI, Machine Learning and Predictive Analytics Best Practice Guide delves deep into the key areas involved in the adoption of these technologies, including the actions marketers need to take before applying them, how to apply them effectively, and how to avoid any unintended side effects.

What is predictive analytics?
Predictive analytics does not describe a specific approach. As the Best Practice Guide states, “At its simplest level, drawing a trend line (or regression) through some historical sales data to forecast next year’s sales is an example of predictive analytics using a mathematical model.”

There is lots of room for confusion or nuance here. “There has always been a relationship or overlap between predictive analytics and aspects of AI and/or ML. For example, neural networks (which have a clear element of self-learning) have been part of the predictive analytics toolbox for decades, but not necessarily promoted as “AI” in their usage by customer analytics teams.”

Predictive analytics uses machine learning or statistics to predict the future of anything from sales trends to patterns in consumer engagement.

In marketing, predictive analytics can be applied across a range of different touchpoints, from initial brand awareness to post-purchase activity. It can help more efficiently and accurately predict behaviour along the customer journey by drawing on historical browsing data and the profiles of other users.

As a result, the implementation of this technology can have a positive effect on metrics like conversion rate as it allows marketers to target users with more personalized and relevant content based on their likelihood to take certain actions Anime Sprout .

Below, I’ve outlined some ways predictive analytics are used in a marketing setting and how it can help improve the performance of key metrics, alongside some real-life examples.