3 Reasons for Predictive Analytics Today

A blog post by Swen Schreiter
Content Management
 

We have already looked at how the marketing game has changed. The key to thriving is to understand your customers – who they are and what they want.

Predictive analytics is one of the many ways you can stay relevant and engage your customer. It allows you to gain insights into what your customers are likely to do based on their previous orders and past behavior.

Data is now all around us – but what does all this data tell us? Predictive analytics and machine learning give you the power to go beyond knowing what happened, and to understand what will happen.

So what are some compelling reasons to take the plunge and start using it? Here are three reasons why you should use predictive analytics today!

1) It is already here


The rise of machine learning and predictive analytics in the digital sector have been game changers. That’s have been, not will be.

Just think: IBM’s Watson has learned different food combinations and is now considered a culinary chef with 65 recipes under his belt.

The ability to automate tasks and stay on top of your data is already here. While fully functional AI is not yet ready for prime-time, you can use predictive analytics to sift through all your data and decrease your daily workload. With no additional costs for using it, why shouldn’t you?

For example, right now refined machine-learning allows you to predict the following:

  • Conversion probability
  • Churn probability
  • Next basket value
  • Expected customer lifetime value
  • And more...

You can use the past to get a better grasp of the future – you can know what your customer wants and when they want it.

2) More time for important stuff


With the use of machine learning to automate work that might be tedious or monotonous, you will be able to focus on coming up with campaigns that truly fit the customer personas that your predictive analytics identifies.

For example, predictive analytics can help you create a list with customers that are more likely to churn, and target them with a specific email campaign that includes a discount. But how does that campaign look? What tests can you run to determine how big that discount should be?

Instead of focusing on finding your target groups, you can focus on creating valuable content. AI is ushering in the end of the one-size-fit-all campaign -- which is a blessing and a curse. While you are presented with the most relevant data on a silver platter, you also should know how you want to use this data. Predictive analytics and machine learning will give you a head-start, but it won’t go the last mile towards understanding the customer for you.

3) It is the future


The use of AI solutions and predictive analytics to analyze customer behavior is very real. This is not just a 2017 trend; it is the future.

What is possible today with predictive analytics is just the beginning. In the next 5 to 10 years, using more refined machine learning and AI to target the right segment and presenting them uniquely adapted messages automatically will give way to an entirely new breed of marketing.

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