John is walking towards Grand Central Station to board the 9:55 am train to work. He is flipping through messages and emails on his phone while trying his best to avoid his fellow pedestrians and not take a wrong turn. He’s also getting bombarded with communications from brands for his attention and action—a click on a CTA, for instance. It’s a frenzy of activities, and in situations like this, brands have, according to research, about eight second to engage John before losing his attention.

The ability to tailor experiences optimizes the chances of audience engagement, but with skyrocketing customer expectations driven by advancements in technology and the explosion of data, it is no longer possible to manually personalize each communication. AI and machine learning, however, grant brands the ability to analyze large volumes of customer data to derive individual profiles and tailor engagement accordingly—at scale, in real time, and with unprecedented precision.

• Channel

Brands today are spoiled for choice when it comes to the number of avenues for communicating with their consumers. Machine learning can analyze a consumer’s past interaction with the brand to understand the best channel for reaching them. This paves the way for AI to leverage these insights to adjust where to communicate with each individual.

• Time

In our fast-paced world, it’s more important than ever to reach out to consumers at the right time to seize their attention. But how do brands know when to do this, especially at the scale of communications today? Machine learning derives the answer to this question by examining each audience member’s behavior and using the insights to optimize send-time at scale.

• Content

Every consumer wants to be treated as an individual. They want experiences that are uniquely theirs, and the content that brands present to them is a key part of all this. It is therefore critical that brands develop the ability to engage in continuous conversations with consumers across a wide variety of touchpoints, dynamically contextualizing and adjusting what content each individual consumes.

This is where AI will come in. When incorporated into an integrated marketing automation platform, it helps brands keep track of their audience’s individual journeys and the content they respond to at every touchpoint. It enables them to align their content marketing strategy with their audience’s real-time content consumption patterns—optimizing where, what, and how often they consume for better outcomes.

• Product

The easiest way for a brand to lose customers is to not acknowledge the relationship that they have shared with them. One of the most important things to keep track of is the products that they have purchased and they kind of products that they are interested in. AI and machine learning make it possible to gather such insights and generate individualized product recommendations for greater potential revenue growth.

• Offer

In a sea of undistinguishable offers, the ones that are truly tailored to the individual consumer will surely stand out. Marketing solutions that provide AI-driven next-best offer management and delivery capabilities give brands precisely this advantage. By studying each individual’s past offer response data—as well as a wide variety of relevant attributes like demographics, propensities, persona, and more—the AI and machine learning models that power such next-best offer features are able to generate and optimize the offers to maximize the likelihood of purchase, at the segment-of-one level.

• Action

The impact of AI and machine learning on individualized audience engagement goes far beyond elements like offer, content, channel, time, and product recommendations. They enhance the brand’s ability to orchestrate relevant, impactful audience experiences in general. A new generation of marketing solutions have tapped into the power of AI and machine learning to better create evolving audience journeys, contextualize responses in real time, and even automate the entire process of optimized omnichannel orchestration.

When AI is present, 49% of consumers are willing to shop more frequently while 34% will spend more money. It has become essential for brands that wish to gain and maintain a competitive edge as individualized audience engagement becomes the norm. AI-driven individualization requires potentially significant changes—technologically, talent-wise, and at the process level—but the returns will be worth it. 80% of customers are more likely to purchase a product or service from a brand who provides personalized experiences.

Get a glimpse of how Resulticks has utilized AI and machine learning to deliver next-level marketing capabilities.