AI Marketing in Action: Delivering Perfectly Timed Content on the Right Channel Improves Engagement 4X

Optimizing send times has long been standard practice for marketers. Traditional send time optimization requires manually analyzing historic trends and running A/B test campaigns at various times of day to determine optimal send times. But there are problems with this approach. For one, it treats your customer base as a uniform group and neglects the dynamics of today’s always-on, mobile, multi-device consumer. More importantly, it focuses on optimizing for opens, rather than downstream actions that drive revenue, such as website engagement and conversions.

If you’re not learning from customers’ behavior patterns as they use different devices, apps, and channels for different purposes at different times of the day, you’re taking a guess as to how to best engage with them. Can you afford to do that?

Fortunately, AI is here to help.

AI empowers marketers with incredible leverage, helping them better engage customers across every channel. By generating insights from every aspect of customers’ behavior and previous engagement with the brand, it makes precise recommendations as to how to engage with them depending upon your desired outcome.

It optimizes WHO marketers should be targeting, selects WHAT content they engage with, WHEN to engage with them and WHERE is the best channel. This “AI Marketing in Action” series explores AI’s impact on these 4 Levers of cross-channel marketing and quantifies its impact on each lever. Our findings are based on a recent benchmark study that analyzed 3.8B marketing interactions from campaigns across various channels and verticals.

In our last posts, we explored how AI helps you determine WHO are the right customers to target and WHAT is the best content to bring customers at any moment for each of your customer strategies. Now, we’ll explore how AI helps determine WHEN and WHERE customers see that content.

Predictive Engage Time and Predictive Channel-of-Choice work in close partnership to ensure that your messages get noticed and acted upon.

Today’s perpetually connected customers are much more likely to have many frequent bursts of activity around the clock than a recurring habit of opening their emails at certain times of day or clicking onto sites or apps at specific hours. Unlike traditional Send Time Optimization, Predictive Engage Time Optimization uses AI to examines campaign clicks, website browsing behavior, total engagement time, engagement depth and transactions to determine windows of time in which each user is most likely to engage. From analyzing the full downstream activities, AI identifies and optimizes send times to when each customer is most likely to engage with your brand, not simply open a message.

Predictive Channel-of-Choice steps in to determine the best channel to engage your customers. It similarly uses AI to learn on which channel each individual customer is most likely to engage at a given moment by performing an ongoing, deep analysis of customer engagement and transaction behaviors. As campaigns run, it automatically adapts the channel on which each customer receives your message accordingly.

Of course, these optimizations aren’t of much use if they don’t provide real-world ROI. Our recent benchmark study found that Predictive Engage Time drives 3X engagement over email and nearly 5X over mobile push. Why the significant lift? Because research shows users prefer to engage deeply at certain hours of the day, while casually browsing throughout others. Adapting individual send times to when users are most likely to engage in downstream activity pays off in real-world results.

Beyond that, combining Predictive Audiences with Predictive Engage Time drives up to 3.8X over email and 7.2 over mobile push.

With Predictive Engage Time and Predictive Channel-of-Choice, marketers can ensure that their messages capture customers’ attention without their constant monitoring. Their messages are continuously optimized to reach each individual customer at the moment and channel where they are most likely to take action. And that translates directly into engagemnt and revenue.

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.