Real-Time Signals Real Customer Value: How Marketers Can Implement AI the Right Way

When it comes to customer experience and relationship building, companies today are struggling. Despite access to petabytes of real-time data and cutting-edge AI technology, most are still stuck with one foot in the past. Even as consumers demand greater levels of personalization and a more “human touch,” marketers in particular have refused to adapt—relying on segments and campaigns to push products and constantly sell everywhere, all the time, instead of leaning into what any one individual really wants or needs.

For example, imagine a customer has a problem with a product and needs to resolve it ASAP. However, they struggle mightily to find the contact number on the web, reach an agent, or get any value whatsoever out of a chatbot or FAQ. Then, when they search their email inbox, all they’ve got are 100-plus unread marketing offers from that same firm.

It’s a terrible optic. Not only has the company failed to adapt to the individual’s context and needs in that moment, but every second the customer’s issue goes unsolved, it becomes more likely to cost them that relationship. To stay relevant, marketers need to understand what’s happening right now and adopt real-time technology they can use to engage customers quickly and effectively, with more relevant and timely offers, actions, or messages.

Brands need the tools to be constantly re-decisioning throughout the customer’s experience—sometimes 10 or 20 times during a single interaction—so they can keep pace as their context changes. Today, relying on data that’s one month, one week, one day, or even one hour old isn’t good enough. For many organizations, artificial intelligence has been instrumental in understanding real-time customer context and journeys. But not all AI is created equal.

The difference in an AI solution’s ability to gauge context in real-time will determine who wins and loses in today’s extremely competitive market. With real real-time technology, companies use propensity models to rank and score customer actions to select the next best action for each individual. This works because it enables them to understand a customer’s context, what they really care about, when to engage with them, and on what channels. Here’s what real real-time actually is in practice—and what it’s not.

Real Real-Time to Solve Real-Life Complexities

Real real-time means communicating only when there’s something relevant to say and the customer is ready to hear it. With this technology, organizations can pinpoint precisely where a customer is on their individual journey to engage them with the right offers in the right ways. It’s critical to have tools that enable fast decisioning and delivery based on immediate customer context, which includes their situation, environment, motivations, emotions, and behaviors, to drive powerful, real-time experiences.

In practice, real real-time-enabled technology stores data in one centralized location and uses AI to do the heavy lifting. AI triggers outbound communication tailored for a specific customer based on what they need with no intervention required. The teams running these systems can then spend their time tuning logic to make sure things run better, like building out a library of offers and messages that enable the brand to have different conversations for specific moments of need. It’s also about contextualizing these messages around what is happening in the world right now in terms of the date, time, economic situation, political landscape, or global crisis. During the pandemic, brands that came out on top were able to shift quickly from blasting marketing offers to appropriately empathizing to create better, long-lasting relationships with customers.

Using Technology the Right Way—for Employees and Customers

There is a right and wrong way to implement AI solutions. The right way involves collaboration and a proper evaluation of the solution. Technology and teams across the organization need to be aligned. Different from a traditional marketing stack, there isn’t one team solely responsible for delivering real-time experiences. Collaboration from marketing and sales to HR, IT, data architects, operations, and senior executives with the agility to move across real-time channels, outbound channels, and the customer data platform (CDM) all play a key role. 

With around 4,000 to 10,000 advertisements served daily to the average person, customers are inundated with offers, messages, web pages, and content that can send them down a new path within seconds. Getting a first impression right is equally as important as getting every impression right. Each interaction only has two outcomes—you either bring that customer closer or push them away. Data, including customer details, history, and digital signals such as website clicks, cursor hovers, chat conversations, transactions, or offer responses, provides the real-time context to detect impactful opportunities.

People are complex creatures who can act on impulse and change their minds frequently. The right AI tools should parse through and score customer data to identify the next best action within milliseconds. The right response now may not be the right response in ten minutes. By evaluating the effectiveness of predictions based on current and previous behaviors, companies can proactively select the action that will add the most value for that customer. Organizations using real real-time technology repeat this action up to hundreds of millions of times a day, delivering optimal interactions to their customers every time.

Customer experience is a complex, personal path that should combine real-time data streams with predictive analytics to understand context and take immediate action on that customer’s preferred channel, creating hyper-personalized connections with every interaction. The customer journey is rarely linear, and the old ways of segmenting data into broad audience insights no longer reigns supreme. By using AI to analyze customer data in real real-time, brands can offer customers exactly what they need at the precise moment they need it.

Matt Nolan is a director of product marketing at Pegasystems. Nolan has worked in the MarTech sector for the past 17 years, serving in a variety of senior product management, marketing, and analytics roles.