Data is Behavior

Almost anyone with a website uses some form of analytics to understand past user behavior and to make decisions for future marketing campaigns based on that data. However, the sheer volume of data most companies collect these days makes it nearly impossible for any mere mortal to isolate useful insights without the help of AI.

That’s where predictive analytics can help. By employing machine learning to create algorithms that can analyze those large datasets and make predictions about future performance, predictive analytics empower businesses to make better real-time decisions that enhance the consumer experience.

There are many different ways your company can use predictive analytics to design digital campaigns and experiences that are more engaging to audiences, and to make sure you deliver the right message at the best possible moment. Below are a handful of ideas.

Suggestion engines

Ever wonder how services like Netflix and Spotify are so good at serving us content that aligns with our tastes and moods? AI allows these companies to build powerful suggestion engines that know just what you’ll want to watch next when you finish the third season of The Crown, for example, or how to tailor a playlist based on the songs you’ve just skipped. Even if you aren’t in the business of streaming content, you can still use predictive analytics to cross-sell and upsell, thereby increasing average order size and making sure customers find everything they need on your site and not a competitor’s.

Targeted content

Most of us are actively trying to provide more personalized, targeted content to our audiences. Doing so effectively can be a tall order, but it’s made much more achievable with the use of predictive analytics. Predictive analytics can identify, for example, when customers will need to replenish a specific product or order a complementary one based on past purchase behavior. It can also do things like predict when a customer is coming up on a relevant life event, such as moving to a new home, for example, which can help businesses get in front of consumers at these crucial (and high value) moments.

Reduce customer churn

Without predictive analytics it’s difficult to know exactly when a customer is most likely to abandon your business in favor of a competitor. Not knowing when customers are thinking of jumping ship means you are likely to miss the opportunity to try to retain them. Predictive analytics can proactively pinpoint customers who are at high risk of churn, allowing your business to make efforts to recapture them before it’s too late.

Identify and target high-value customers

It’s a universal fact of marketing that not all customers are created equal. Some customers are low value, while others are quite high value, and the majority are somewhere in the middle. Imagine the potential impact on ROI if your business were better able to identify your highest value customers very early on. The early identification of such high rollers means you will be able to direct more effort to closing these customers and retaining them in the long-term.

Predictive lead scoring

In a very similar way, predictive analytics can not only help you identify customers with the highest likely lifetime value, but also to pinpoint the ones that are the most likely to become customers (and quality customers at that) in the first place. Rather than spend countless hours of manpower of trial and error devising a formula for lead scoring, predictive lead scoring can do this work algorithmically with greater accuracy.

In closing

Predictive analytics is all about putting data at your fingertips to empower your company to make better business decisions that will impact the overall digital experience of your brand. Whether that means enabling you to strategically reduce customer churn or giving you the information you need to offer more personalized and relevant content to your audiences, predictive analytics has a powerful role to play in any digital marketing strategy.

Leave a Reply

Your email address will not be published. Required fields are marked *