Target once famously figured out a teenager was pregnant—before her father did. By analyzing her purchases (like unscented lotion and supplements), Target’s predictive model pieced it together, triggering pregnancy-related ads before anyone in her family even suspected it. This discovery led to an uncomfortable conversation between the family and the store, but it showed the sheer power of predictive analytics in marketing.
Modern AI-driven analytics are far superior with years of data, making the predictions even more accurate. This is why companies are rapidly adopting it, making the predictive analytics market size valued at $10.2 billion in 2023.
Predictive analytics allow you to anticipate your customers’ behavior so accurately that you know their needs before they do. In the case of Target, it was understanding purchasing signals. But for marketers like you, predictive analytics can unify your marketing channels, optimize your marketing spend, and help you generate better ROI.
What is predictive marketing?
Predictive marketing is a data-driven marketing approach that leverages statistical data modeling to analyze big data and make informed predictions about future outcomes. The analysis process is called predictive analytics. It’s like looking into a crystal ball, except the predictions are based on real data—not magic.
So, how does predictive marketing analytics work in practice? Instead of waiting to see what worked (or didn’t), you make smarter moves from the start. It’s the difference between driving with a GPS telling you where to turn in real-time versus navigating with an outdated map.
Predictive analytics in marketing can help you by:
- Anticipating customer actions: Using data collected from past behavior, you can understand what your customers will likely do next. Be it making a purchase, clicking on an ad, or even unsubscribing from your email list, these insights allow you to adjust your strategies accordingly.
- Refining your targeting: Predictive models help identify which customers are most likely to convert, enabling more precise and personalized targeting. This means you’re not wasting money targeting people not interested in your product.
- Optimizing budgets and campaigns: Predictive marketing isn’t just about customer behavior—it’s also about maximizing your budget. By predicting where your marketing dollars will have the most impact, you can allocate resources more effectively, improving return on investment (ROI).
Predictive marketing takes you from playing defense to playing offense. And in the current competitive marketing game, you need to be proactive.
The role of AI and predictive analytics in marketing
Collecting data is no longer the challenge; you’re probably overwhelmed with it—email performance, social media engagement, website traffic, sales, and ROAS.
But data by itself? Not much use. The difficulty lies in figuring out how to make sense of it all. That’s where AI and predictive analytics in marketing help you.
With AI-driven marketing mix modeling optimization, you can:
- Predict future outcomes: AI uses machine learning to analyze past campaign performance and find patterns that aren’t immediately obvious. Maybe your email campaigns perform better on Wednesdays, or your customers are more likely to spend on a Facebook ad than Google. Finding the data-backed trends takes the guesswork out of decision-making, giving you more confidence in your strategies.
- Automate tedious tasks: Instead of manually poring over reports, AI tools can do the heavy lifting, allowing your team to focus on strategy and creativity.
- Function in a cookie-less digital world: Predictive analytics help create personalized user experiences with the end of cookies. In a recent Keen study, 81% of marketers said that predictive analytics tools are important for personalization in the absence of traditional cookies.
Read next: Data-driven media planning: Boost results with analytics
Overcoming data overload with intelligent systems
You’re not alone if you’re swimming in data and feeling overwhelmed. That’s where intelligent systems like Keen’s AI-powered platform come in, helping you cut through the noise and focus on the data that matters most.
There are various types of predictive modeling systems with different accuracy. For example, Keen’s platform uses the Bayesian marketing mix model that continuously updates predictions as new data becomes available, helping you adapt to changing customer behaviors. Unlike traditional models that may struggle with data limitations and overfitting, Bayesian systems evolve over time, offering more accurate predictions as they integrate both past knowledge and new evidence.
Our Bayesian model is so accurate that a leading retail client increased their profit ROI by 49% by implementing Keen’s system.
Here’s how intelligent systems help you stay on top of your data:
- Filter out irrelevant information: Avoid getting bogged down in hundreds of metrics with intelligent systems highlighting the data points that will move the needle.
- Make smarter decisions: With continuously updated predictions, adjust your strategies in real time, always making data-driven moves.
- Simplify complex data: Instead of getting lost in spreadsheets, intelligent systems transform your data into actionable insights you can implement.
How can predictive marketing help in cross-channel optimization
Cross-channel optimization ensures all your marketing channels work together, not in isolation. In a fragmented approach, you might have great results in one area, like email marketing, but your social media efforts could lag behind. Or worse, you might under-utilize a channel’s potential and invest more into another. In fact, a recent study by Keen shows that 38% of marketers overspend on the wrong campaigns.
You need a holistic approach to maximize the power of predictive modeling marketing. This means bringing all your marketing channels under one umbrella so they work together toward a common goal.
Predictive analytics enables marketing teams to unify channels by providing insights into how each contributes to overall performance. A McKinsey study shows that companies that optimize across all channels see a 15-20% improvement in marketing ROI.
Predictive analytics help optimize your cross-channel marketing by:
- Identifying top-performing channels: Which channels are driving the most sales? AI will tell you in real time so you can double down on what’s working.
- Adjusting budgets dynamically: With real-time behavioral data, you can shift your budget between channels on the fly. If one channel outperforms others, predictive analytics will signal that it’s time to invest more in that area. No waiting for end-of-month reports.
- Measuring incremental impact: With predictive analytics, you can analyze the revenue contribution of each marketing channel. The analysis depends on the data you input, helping you measure your incrementality and understand the campaigns that worked and didn’t.
Keep learning: How to Identify the Right Channel for Product Launches
Take a holistic approach to marketing with Keen
Predictive analytics give you the power to plan your marketing mix strategy. And when accurate data drives your marketing, you’re not just keeping up with the competition; you’re leading the way.
Keen’s patent-pending Marketing Elasticity Engine (MEE) informs our platform’s Bayesian priors with over 40 years of academic research and $7.5 billion of sales data. Based on this vast amount of data, Keen predicts your ideal ROI with the availability of only two variables:
- Your marketing spend across different channels
- Your industry
The best part: our prediction model is trustworthy, with only a 4% margin of error.
Adopting a holistic, data-driven approach with Keen can unify your channels, improve your campaigns, confidently predict outcomes, and adjust strategies in real time.
Request a demo to see how you can use Keen’s predictive analytics in marketing and consolidate your marketing channels.
