What is predictive AI?

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Predictive AI forecasts what’s likely to happen next based on patterns in historical data. Unlike generative AI, which creates new content, predictive AI identifies likely future outcomes. In marketing and customer engagement, predictive AI helps you stay one step ahead, reducing the guesswork involved in decision-making.

Predictive AI analyzes everything from past purchases to browsing activity to surface insights in customer profiles, like who’s likely to buy soon, who might leave you for a competitor, or which products someone might buy next. These predictions help marketers and service teams prioritize efforts, personalize communications, and create more relevant experiences for every customer.

With predictive AI, brands can automate smarter marketing, support retention efforts, and reduce manual analysis. It’s a practical way to improve internal efficiencies and deliver more relevant experiences, whether you’re running a small ecommerce shop or an enterprise retail brand.

What does predictive AI do?

Predictive AI helps businesses make more informed, proactive decisions. Here are some of the key jobs it handles:

  • Identifying churn risk: Predictive AI flags which customers are less likely to buy again, so you can intervene before they drop off.
  • Calculating customer lifetime value: Predictive AI estimates how much money a customer is likely to spend with your business in the long term, helping you allocate resources and tailor experiences for potential VIPs.
  • Forecasting customer actions: Predictive AI analyzes purchase patterns to identify when a customer is likely to run out of a product and make their next purchase, what products they might be interested in next, and more, so your communications always feel relevant, timely, and genuinely helpful.
  • Pinpointing the best send times: Predictive AI identifies optimal send windows for your audience, so your email, text, and WhatsApp messages are more likely to land at the right moment.

Key features of predictive AI

Predictive AI includes several essential building blocks that make it work in real-world marketing and service use cases. Here’s what you’ll find:

  • Behavioral data analysis: Predictive AI continuously scans buying history, engagement, and browsing patterns stored in your customer data platform to spot trends and forecast future actions.
  • Dynamic segmentation: When predictive analytics are stored as data points in customer profiles, predictive AI can guide your segmentation efforts, grouping customers based on their likelihood to buy, churn, or engage.
  • Next-best action recommendations: Predictive AI suggests the right offer, product recommendation, channel, or timing for each customer based on what they’re likely to care about most.

Benefits of predictive AI

Predictive AI can help teams operate more strategically and efficiently. Here are some ways it can support your work:

  • Smarter timing: Reach people with more relevant messages and offers at moments when they’re more likely to engage.
  • Proactive re-engagement: Spot customers who may be drifting and reconnect thoughtfully to help maintain strong relationships over time.
  • More thoughtful use of resources: Focus efforts on audiences that are most relevant to each campaign.
  • Automated personalization: Deliver the kinds of tailored experiences and personalized outreach consumers expect, without the manual guesswork.
  • Faster decision-making: Get clear insights quickly, so your team can move with confidence.

Predictive AI helps you move from reacting to anticipating, which makes for more timely and considerate customer interactions.

Ready to take action on what your customers will do next? Learn more about how Klaviyo AI (K:AI) can help today.