Marketing teams have more data at their fingertips than ever before. Every click, scroll, and interaction holds valuable insights, yet many struggle to turn that information into meaningful action. Our latest survey shows that while 81% of teams collect and analyze data, a significant portion finds it difficult to apply those insights in ways that drive engagement and revenue. Without execution, opportunities slip away.
Data alone isn’t enough—here’s why
Despite growing investments in AI, 40% of businesses say they are falling behind on real-time personalization. The biggest roadblocks include:
Unstructured data that makes insights difficult to access and apply.
Disconnected systems that prevent teams from seeing the full customer journey.
Underused AI tools that leave engagement opportunities untapped.
Personalization is one of the most common AI use cases, yet many businesses still have room to improve. While 65% of companies personalize product recommendations, only 54% use AI to tailor promotions, and just 35% use it to trigger chatbot responses. Additionally, 48% of teams prioritize optimizing user journeys, but gaps in tools and expertise make it difficult to deliver the seamless experiences customers expect.
Where things stand today
AI-driven personalization is proving to be one of the most effective ways to boost engagement and revenue. Companies that invest in AI-driven marketing strategies report stronger conversion rates, while those that hesitate risk losing ground.
AI maturity varies widely by industry. Software companies lead with an average AI maturity score of 2.75 (out of 5), while consumer and retail businesses trail at 2.4. Even among AI adopters, 41% are still in the early stages, leaving significant room for growth.
Beyond personalization, AI’s potential in automation and predictive analytics remains largely untapped. Only 28% of companies feel confident using AI to forecast customer behavior, and just 19% consider AI a primary driver of their personalization strategy. This gap between AI’s potential and its actual impact presents a major opportunity for digital marketing teams.
Four ways to turn insights into action
Collecting data is only the first step; success comes from using it effectively. Here are four key strategies digital marketing teams can implement today:
Put AI to work in personalization. Companies that integrate AI into content, promotions, and recommendations see higher engagement and conversion rates. AI-driven personalization ensures the right message reaches the right audience at the right time.
Unify data for a complete customer view. A connected approach to data enables teams to improve targeting, measure performance, and optimize campaigns. Yet, 28% of businesses still struggle to integrate data across platforms, limiting their ability to deliver seamless experiences.
Remove roadblocks in the user journey. Nearly half (48%) of companies prioritize reducing friction in digital experiences. Behavioral data helps teams identify sticking points and make improvements that keep customers engaged.
Adopt AI with intention. Only 17% of businesses consider AI a core part of their strategy, but those actively testing and refining AI applications are gaining a competitive edge. Starting with smaller initiatives—like predictive lead scoring or dynamic content—lays the foundation for long-term success.
The future of marketing belongs to teams that act
Marketing teams that embrace AI, personalization, and behavioral data are leading the way in engagement and revenue growth. As AI-powered strategies continue to evolve, businesses that take a wait-and-see approach risk falling behind.
Survey results highlight a major shift: real-time insights and AI-driven engagement are no longer optional, they’re the foundation of modern digital marketing. Teams that take action today will be the ones shaping the industry’s future.
For expert insights and deeper analysis, download the Reality Check Report and listen to our podcast series, where Fullstory’s thought leaders explore the future of AI and behavioral data in marketing.
