It’s the oldest question in the book: What do customers want?

As business owners and managers, we all wish we had a crystal ball. Data science is a close second. It provides information about where customers are coming from, what they’re clicking on, and how quickly they’re leaving. It shapes every campaign we create, from our word choice to the images we use. In short, it tells us what is working to meet our customer’s current needs and what’s not. The problem is, though, it doesn’t give us insight into what they’ll need next.

Enter the predictive economy. T3 President Ben Gaddis, who spoke on this topic at the American Advertising Federation’s February Breakfast Serial, says data science is shifting—and if harnessed properly, can help us anticipate our customers’ needs before they have them, and ultimately serve them better than ever before.

According to Gaddis, it’s not about predicting what will happen, but when. With customer expectations and the consequences for not delivering them at an all-time high, it is up to businesses to use data science to close the gap between what a customer is likely to do and when they will do it, rather than simply analyze past behavior.

Gaddis outlined three key trends that are signaling the change toward a predictive economy—and how successful businesses are using them to stay ahead.

Extreme personalization: These days, marketing personas or avatars aren’t enough to earn your customer’s loyalty and retention. Instead, use your data to build one-to-one relationships with your actual customers based on their individual needs and preferences.

The example: Using personalization and predictive behavior, Pizza Hut’s Game Plan promotion asked customers to share their favorite team and used that data to market to those customers when they were most likely to purchase—when their team was playing. So for instance, a Houston Texans’ fan would get an email or a text message right around game time, suggesting their favorite pizza.

Proactive experiences: Think about every aspect of your customer’s journey and really hone in on the small details. Your customers’ pain points are not minor inconveniences—they are prime opportunities to provide proactive experiences.

The example: With one small tweak, Delta’s app eases one of the most frustrating and anxiety-inducing aspects of airline travel: It notifies passengers when their bags have been loaded onto the plane before takeoff—and onto the conveyor belt at their destination.

Intelligent assistance: While artificial intelligence still has a way to go (sorry, Siri and Google Assistant), it’s no secret that technology makes life easier—and leveraging it can greatly enhance your brand experience.

The example: A recent integration allows Marriott hotel guests to compare and book rooms directly through Slack by adding their rewards app to the messaging platform. Anyone in the Slack channel can view the available rooms and rates and vote on where they’d like to stay, making business travel easier.

Is your business ready for the predictive economy? If not, these recommendations from Gaddis can help you get started:

  1. Pinpoint moments when your customers need you most. Take an exhaustive look at your customer journey to identify opportunities and pain points.
  2. Collaborate with data teams to understand your predictive capabilities and challenges. Often, we don’t understand our data’s limitations—or possibilities—until we ask.
  3. Develop a predictive vision that combines customer experience and data and identify three to five pilot initiatives.

Jennifer Reed is a member of Austin Ad Fed and the director of marketing at Khaana Marketing.