How to Use Predictive Audiences to Enhance Cross-Channel Marketing Strategies

Consumer behavior has changed radically over the past 20 years. Driven by advanced technologies, buyers are now exploring a variety of channels to discover, evaluate, and purchase goods and services. In fact, Impact Marketing and Public Relations estimates it takes at least six touchpoints to make a sale — and those touchpoints tend to take a criss-cross journey across diverse digital sites.

With this in mind, marketers have developed cross-channel marketing strategies. However, cross-channel marketing efforts can fall flat due to confusing, inconsistent messaging and non-intuitive content deployment. Fortunately, there’s a solution to make cross-channel marketing more streamlined and effective: The use of predictive audiences.

Predictive audiences leverage the power of predictive analytics. As explained by Nativo, a leader in the predictive audience space, predictive analytics use a combination of first-party data, AI, and machine learning to more deeply understand consumers based on their former actions. Consequently, it’s possible to reliably predict what a consumer is likely to do in the future. And when you can correctly anticipate the next moves of a customer, you have something akin to a crystal ball in your hands.

With predictive analytics and audience, you can segment consumers into audience cohorts and market to them accordingly. This is extremely beneficial when you’re taking a cross-channel approach because it allows you to tailor your content efficiently. Not only do you know what to say in an email to a consumer, but you know exactly how frequently to make contact, as well as when to engage with the customer on other channels like social media or display ads. As a result, your conversation rates and ROI should improve, giving you a leg up over the competition.

Not a “set it and forget it” tool

To get the most of predictive audiences for your cross-channel plans and campaigns, you’ll want to keep some best practices in mind. After all, you want to glean the full value from this marketing approach.

1. Start bucketing customers into predictive audiences

If you’ve been hesitant to pull the plug on your third-party cookie reliance and dive into predictive analytics, now is the time to make your move. Third-party cookies are falling out of fashion fast, even though Google hasn’t gone 100% cookieless yet. The sooner you begin to ramp up your collection of first-party cookie data, the faster you can begin to use the data insights to fuel and inform your cross-channel marketing decisions.

Remember that first-party cookies are those that come from visitors’ and customers’ behaviors on your owned sites. These can be anything from their purchasing patterns to their past interactions with different product pages. Amassing this information is critical to being able to determine the “next moves” of specific customer segments and avoid wasting energy and funds on blanket marketing campaigns.

Of course, you can’t start putting audiences into buckets until you have a software in place that will work with your existing CRM. IBM recently noted that when AI-based predictive analytics and CRM are combined, companies can gain plenty of advantages. However, even though 78% of leaders say they have this type of capability, more than half aren’t sure they’re using it efficiently. Consequently, when investigating software, look for a product with a user-friendly dashboard interface, a solid reputation for working with top-tier clients, and scalability potential. That way, you’ll be able to successfully develop predictive audiences and move onto the next stage in using them during your cross-channel marketing initiatives.

2. Explore techniques to personalize content across channels

Being able to deliver personalized content to certain audience segments allows you to engage in what feels like an individualized way to your customers. McKinsey research has shown time and again, personalization is becoming a must-do for all marketers. According to their surveys, more than seven out of 10 consumers expect to receive personal content from brands. And that means you need to structure your content to be customized no matter what channel you’re using.

For instance, your predictive analytics might tell you that a certain audience is likely to buy a product in the next two weeks based on historical data. You can then develop and deploy a tailored coupon to text to only those audience members. But that’s not all: You can further rely on your predictive analytics to further divide audiences into those who tend to respond to follow-up texts versus those who respond to follow-up emails.

Essentially, you can keep the messaging highly individualized throughout every touchpoint. Ultimately, your goal is to realize as many conversions as possible based on the predictive analytics that are driving different predictive audiences.

3. Keep applying A/B tests to your prediction-based marketing

Over time, your customer base may shift, especially if you move into different markets. To stay ahead of changing customer needs, you’ll want to keep testing a variety of messaging formats, flows, and frequencies based on the predictive audiences that stem from your predictive analytics outcomes.

What does this look like in practice? Let’s say that you have a predictive audience that tends to make repeat purchases about every three months. Knowing this, you could divide the predictive audience into two groups and experiment with two campaigns. The first campaign could prompt one audience to make their purchase two weeks sooner than they normally would. The other campaign could prompt the other audience one week sooner. You could then use the outcome to figure out if you can encourage customers who usually make purchases at the 12-week mark to make them at 10 or 11 weeks instead, thereby increasing their repeat buying patterns.

As you become more familiar and comfortable with relying on predictive audiences, you can conduct other types of experimentation as well. While not all experiments will work, some may produce surprising — and appealing — results. Case in point, you could find out that just by changing to a different channel during a stage in the sales funnel, you can increase the likelihood of a consumer becoming a customer.

It takes a commitment to embrace predictive modeling, and you and your team might not feel wholeheartedly comfortable with it overnight. Nonetheless, if you’re looking for a way to get more from your cross-channel marketing, constructing predictive audiences is a worthwhile endeavor.