Your business maintains a website, churns out weekly content, and tracks how people react. You’ve divided your email lists into groups of existing customers and prospects. The team regularly sends messages to each, tweaking the wording and angle for perceived needs. But is all this enough to keep your audiences engaged? You’ve probably noticed you’re not sure your actions are leading to the ultimate end goal of boosting conversions.

You could be analyzing the wrong metrics or misinterpreting the data. Plus, there’s the possibility the team is relying on traditional versus predictive analytics. The latter goes beyond how audiences have behaved in the past and considers what they’re doing now. These tools forecast what consumers will likely do, including what will boost their engagement with your brand. Keep reading to learn how your company can leverage predictive analytics with its audiences.

Build a Stronger Email List

There’s nothing more frustrating than sending out a well-crafted, polished email only to have people unsubscribe from your list. You wonder what you did wrong. Was it what you said? Was the design of the email template off-putting? Maybe you sent the message at an inappropriate time. Perhaps the subject line or the sender wasn’t clear. 

You could take a wild guess and tweak any number of these variables. However, you’d be throwing spaghetti at a wall with a high likelihood of getting the same results. Why not use predictive audiences instead to target subscribers based on product interest, lifecycle stage, or lifetime value?

Say you identify a subset of your existing customers who tend to engage with promo emails about certain products. Let’s say those products are smartphones. Lately, this same segment has been spending more time on your website pages with information on these products. Their behavior points toward an increased interest in making a purchase. A timely email with targeted messaging about a special promotion could become the trigger.  

Likewise, you might also use predictive analytics to determine who on your list is most likely to unsubscribe. Have they ignored the past three or five emails you sent? Maybe they’ve only opened one out of the five but didn’t click on anything. In addition, they haven’t engaged with any website content for months. This group would be ideal to exclude from promo emails for a while as you find ways to reengage them.  

Recommend Desirable Products

Streaming platforms are a prime example of how predictive analytics can work in real-time. You log in and start watching. Meanwhile, the platform is gathering data on what you watch and how long you engage with the content. Predictive tools also look at frequency, such as how many times a week you watch certain shows.

With this data, the algorithm starts making suggestions for content it predicts will draw you in. Is it always on target? No, but it tweaks its recommendations as your behavior evolves. Whether you save content to your watchlist and give it a thumbs up or thumbs down is important, too. Ad-hoc purchases for premium content are yet another variable.

Ninety-one percent of consumers are more likely to purchase from companies that deliver appropriate product recommendations. In addition, 56% of online shoppers will go back to a website that suggests items. The catch is you can’t just make recommendations. They must be personal and relevant. Predictive audiences help ensure both by analyzing individual behaviors against the collective.

There might be similarities between what you and others watch. This is why you’re likely to see a list of top-rated content suggestions along with individualized recommendations. Brands can do the same with other product types, whether the company is a mass-market retailer or delivering financial services. The key is to ensure the data is constantly updated so you don’t send recommendations that are off the mark.

Minimize Churn

You might not be able to prevent every customer from leaving. But if you could stop most of them from going to a competitor, it would help your bottom line. You’re not just saving those customers and the revenue they bring in now. You’d also be preventing negative word-of-mouth, which could make future leads hesitant to convert.

Traditional analytics might identify churn risk by metrics such as whether someone has purchased anything in the last three months. To reengage these customers, you send them a one-time free offer or a deep discount on a favorite item. But what if you’ve missed a sizable number of at-risk customers who don’t meet the criteria? The traditional approach might also group clients who aren’t at risk into the incorrect category.

For example, people who did purchase in the last three months could be actively checking out competitors. They signed up for your service a month ago, but haven’t engaged with any welcome emails or your website. Simultaneously, you have some individuals who haven’t bought anything in the past three months for other reasons than dissatisfaction. They’re temporarily out of the area and your footprint is regional.

Now you’ve sent them an offer they can’t use before it expires. Plus, you’ve missed an opportunity to address churn risk amongst recent sign-ups. The predictive approach uses a broader range of variables to correctly pinpoint who’s most likely to leave. It can also help uncover why, allowing you to send more relevant messaging.  

Enhancing Customer Engagement

Audience behaviors can evolve, sometimes from one day to the next. It makes traditional analysis methods problematic for brands when it comes to boosting client engagement. These processes show you what customers did before, but ignore how they’re reacting in the moment. Environmental variables and preferences can change without much warning from the past.

More forward-thinking tools, such as predictive audiences, look at the big picture. Predictive methods reveal what consumers are likely to do based on individual and collective factors. They help brands increase the accuracy of data-driven decisions while boosting engagement through experiences with a personal touch.