Today, being data-driven is simply part of being a good marketer. From proving the value of campaigns to generating insights about the customer journey, data fuels marketers’ performance.
In this article, we’ll look at what being a data-driven marketer means today, and what the best marketers are doing to improve their data strategy ahead of 2025.
Data-driven marketing in 2025
In the past, assessing the performance of each campaign and making optimizations off the back of the insights was enough to call yourself a data-driven marketer.
2023 was a breakout year for generative AI and it gave marketers a glimpse at the possibilities. Finally, they could see how the huge volume of data at their fingertips could be utilized for more informed and informative marketing.
In 2024, AI adoption rates soared and marketers made AI-powered tools part of their strategies and processes, with varying degrees of success.
At the same time, we were taken on a data privacy rollercoaster, with Google announcing that third-party cookies would sunset from Chrome beginning early 2024 — and then taking a U-turn on that decision mid-year.
Finally, increasing competition, stricter filtering on emails and SMS, and a world of distractions made cutting through harder than ever and, as a result, every marketer felt the need to unlock their data for personalization efforts.
With all of this in mind, there's no doubt that the successful marketers of 2025 will understand how to utilize their data for more powerful marketing. This means understanding your data infrastructure optimizing it for AI-powered tools, and making data a central part of your strategy.
Three things great data-driven marketers are doing
The great data-driven marketers of tomorrow are using what they have today, while preparing for the new and improved technology set to launch in 2025.
1. Making behavioral data the hero of personalization
Personalization today is about responsiveness and relevance — sending fitting messages and information in response to your customer's behaviors and actions. While audience segmentation is still a part of this, it's not the whole story.
Behavioral data should play a starring role in your marketing. It should be used to trigger automated campaigns and messages, inform how you nudge leads further down the funnel, and support the conversations you have with leads and customers.
This is beneficial for a number of reasons — behavioral data tends to be more reliable than other forms of data, even first-party data from surveys where response bias can leave you with inaccuracies and demographic data only gives you so much insight into your audience's interests, goals, and emotional pulls. When behavioral data is used well, audiences typically perceive the information received to be relevant and helpful rather than invasive or overly familiar.
A behavior-first approach can also simplify your personalization strategy. Centering your messaging around behaviors helps anchor your customer journeys and allows you to achieve personalization without leaning on often inaccurate data. It also leads to better results — one action leads to the next, and you naturally build campaigns that drive desired actions.
2. Preparing for predictive analytics next wave
Some marketers have been led astray by predictive analytics tools that were launched too early. Many others are still struggling with disparate, messy, or incomplete data that is leading the AI astray. In either case, 2025 could be the year the promise of predictive analytics and decision intelligence is finally delivered.
As the tools improve, and newer, more sophisticated models launch, marketers will have the opportunity to use AI to make marketing decisions based on predictions about customer’s behaviors. No matter how good the tool, you will need robust, clean, and complete data to get accurate results, so if you're not there yet, spend some time figuring out how you can consolidate your data and fill gaps.
Predicting performance with marketing mix modeling (MMM)
Marketing mix modeling (MMM) isn't a new analysis technique — marketers have been using it to determine which marketing efforts drive performance for a long time now — but it has become a lot more accessible.
Many parts of the once-laborious process can now be automated and, with improved AI, predictions could happen in real-time, giving marketers a way to make real-time decisions based on predicted channel performance. It can also be an alternative to broken attribution models for some marketers.
Finally, as Supermetrics points out, MMM can help marketers who are struggling with new and enhanced privacy regulations, "As many institutions have rolled out privacy regulations to protect their citizens’ privacy and limit the data businesses can access, it’s getting harder to do multi-touch attribution without third-party cookies. That’s why more businesses start investing in MMM to better understand which growth levers to pull based on historical performance data."
Final word
We’ve long since graduated from the days of ‘big data’ overwhelming marketers who needed to reach out to analysts and wait days (or weeks) to get answers. We’re living in the golden age of data — marketers can now find what you want, when you want it, and - with the help of AI - use it to do anything. This doesn’t just make your life easier, it unlocks creativity and a true sense of no-limits marketing.
