AI Marketing in Action: Selecting Who To Target with Predictive Audiences Increases Conversions 28%

ROI of AI in Marketing: Part 1 of 4

Marketing success starts with identifying the right customers to target for each customer strategy and marketing campaign. But what does that process look like for you today? Do you define customer segments based on specific demographic and behavioral parameters, pass the requirements over to your data team and then wait a week, or two, or more to get back customer lists before launching campaigns? Then, how often are your lists refreshed?

While you wait for your customer lists, your customers may churn, purchase from your competitor or simply lose interest in your brand because you failed to engage them. By the time you have your lists, a portion of customers may no longer even fall into those segments. In today’s world of fleeting attention you can’t afford to wait around. You have to get ahead of your audience. But how do you determine if customers engaging (or not engaging) with your brand today are simply browsing, looking for more information or are ready to convert? How can you tell if they are thinking of churning or are ripe for upsell?

That’s where AI is here to help.

At its core, AI helps marketers be smarter and faster about how they engage customers along the customer journey by optimizing WHO they should be targeting, with WHAT content, WHEN to engage them and WHERE is the best channel. This “AI Marketing in Action” series will explore AI’s impact on the 4 Levers of cross-channel marketing, the “Who, What, When & Where,” and quantify its impact on each lever based on a recent benchmark study that analyzed 3.8B marketing interactions from campaigns across channels and verticals. Lets begin by exploring AI’s impact on the WHO.

10x increase in live event attendees


AI helps you determine who are the best customers to target at any moment for each of your customer strategies by translating a holistic view of your customers – all the historic data as well as real-time behaviors – into actionable customer scores.

How involved is this process? You simply define your desired goal – such as driving first purchases – and AI algorithms surface the best customers to target. Each customer’s likelihood to respond is scored based on a complete customer view – including their profile, product interactions, historic brand engagement and their latest customer activity across channels. Scores continuously update and are immediately ready to use across campaigns.

Bonus points: You have full visibility into the attributes that influenced the score. You can also see the performance of predictions before using them in your campaigns.


The real question boils down to: do Predictive Audiences achieve higher ROI than rule-based, static segmentation? Analyzing customers who used both approaches the answer is, yes.                             

Our recent benchmark study found that Predictive Audiences drive 28% lift in conversion events such as orders, subscription upgrades and form fills. In fact, high propensity users are 5X more likely to convert than low propensity users.  

Why do these Predictive Audiences outperform? Because people’s propensity towards a desired action, affinities and lifetime value are based on a complex combinations of variables, which can’t be defined by set rules. For example, figuring out whether someone is ready to sign up for a subscription is determined not only by a specific milestone during their trial but other variables such as engagement patterns, recent activity, content consumed, time spent on site, email interactions, location, and potentially a host of other variables. And those variables can change over time. Predictive audiences listens and reacts.

+28% average lift in orders, AOV, and subscription upgrades
High propensity users are 5x more likely to convert than low propensity users


You no longer need to wait for your data team to create and maintain segments. With AI, you always have the right audiences ready to engage. More importantly, moving from an audience strategy that’s reactive to one that’s proactive drives incremental ROI.

For the full set of findings, as well as real examples of marketers who have used AI to drive revenue by making better, quicker decisions about the “Who, What, When & Where” of cross-channel marketing, download The ROI of AI in Marketing: 4 Levers for Cross-Channel Success.

In upcoming blog posts we’ll explore AI’s impact the other 3 levers of marketing:

  • “The What” with Predictive Recommendations: Determine the right piece of content, offer or product to show each customer
  • “The When” with Predictive Engage Time: Optimize the delivery of the campaigns to the times when each individual customer is most likely to engage
  • “The Where” with Predictive Channel-of-Choice: Deliver the campaign on each individual customer’s channel-of-choice