The news: Marketers are doubling down on content relevance and strategy as key drivers of performance, but personalization is being left behind.

• Nearly two-thirds (65%) of North American B2B marketers who say their efforts have been effective in the past year cite content relevance as a main reason, per Content Marketing Institute (CMI).
• 61% of those with a well-defined content strategy report stronger results and ROI growth over the past year, with three-quarters attributing improvements to refining their approach.

The problem: Marketers still face structural barriers that limit how far strategy can carry them. The top three hurdles are crafting content that sparks action such as conversions (40%); constraints on time, people, and budget (39%); and measuring impact (33%).

Compounding those challenges is the fact that resource constraints and measurement issues are deeply intertwined, per CMI. When teams can’t clearly show performance or quantify investments, executives may further tighten budgets, creating a cycle of underinvestment.

The opportunity and challenges: 95% of B2B marketers are using AI-powered tools in some way as AI becomes a key asset to demonstrate that teams are doing enough with the resources available. However, most applications remain in experimental phases, like tools for generating marketing or written copy (used by 89% of marketers) and creative assets such as images and video (53%).

This focus on production over optimization leaves higher-value applications underused and means opportunities in market research, content personalization, and analytics are being overlooked. The second oversight could be a costly mistake—personalization drives a 10% to 30% increase in marketing ROI, per McKinsey, and can cut customer acquisition costs by up to 50%.

• Despite the potential payoff, 94% of marketers say their use of personalization is either basic or moderate.
• Only 14% of marketers are using AI-powered tools for personalization, and just 12% are using them for predictive analytics.

What marketers should do:

• Pivot AI’s role from content creation to content intelligence, using it to surface audience insights, analyze campaign data, predict engagement, and tailor messaging.
• Focus on quality signals, such as content relevance, conversions, and timeliness, rather than sheer production volume.
• Implement data-driven personalization to get a sustainable edge in campaign efficiency and engagement.

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