Content teams aim to craft experiences that speak to customer needs. Data teams focus on turning requirements into clean audiences, triggers, and technical systems. Both teams share the ultimate goal of driving business outcomes, yet cross-functional miscommunication often slows momentum before a campaign even launches.
At the MarTech Conference, free and online Sept. 2, Cyndi Greenglass, president, Livingston Strategies; Natalie Jackson, director of demand generation, CBIZ); Ruth Stevens, president, eMarketing Strategy; and AnnMarie Wills, CEO, Leverage Lab LLC, will explore practical ways to bridge this gap.
The gap usually reveals itself in simple requests. A content team sets out to reach “high-intent prospects.” But defining which behaviors indicate high intent, identifying the necessary data, and confirming whether the tech stack can execute that vision require early alignment. Without shared context up front, strong strategy risks getting lost in execution.
Two teams looking at the same customer differently
Content and data teams approach shared goals from distinct, necessary angles.
Content strategists focus on customer intent, narrative, and experience — framing work around how messaging influences behavior. Data teams translate those concepts into system logic, working with identifiers, rules, and technical architecture.
Disconnections occur when concepts meaningful to one side lack a corresponding technical counterpart on the other. Terms like “engaged buyer” or “churn risk” are great starting points, but they require concrete, measurable signals before a data team can reliably build those segments.
In this session, our expert panel explores how to establish common ground before technical differences impact your go-to-market timeline.
Which customer signals can you actually trust?
Building strong cross-departmental partnerships requires a clear agreement on the data driving your campaigns.
Marketing teams have access to vast behavioral inputs, but not every signal carries equal weight. Email opens, site visits, and content downloads tell different stories — and combining those signals introduces complexity.
Content teams need visibility into what data is realistically available to confirm. Data teams need campaign context to determine which signals map to strategic goals. Alignment here ensures personalization efforts reflect true intent rather than logical assumptions.
You will gain a framework for evaluating signal reliability, helping your team make confident, data-backed decisions.
Turning creative ideas into executable requests
Closing the divide doesn’t mean content marketers must become data engineers, or that data teams need to write copy. It comes down to establishing a clear translation layer.
Instead of submitting a broad request for “prospects interested in Product X,” marketers can specify the behaviors indicating that interest and share the intended business outcome. Data teams can then validate available signals and outline what is technically achievable.
Bringing this collaboration forward in the planning process protects both creative strategy and technical efficiency.
When both teams connect story to data and data to business value, marketing functions operate with greater speed, clarity, and authority.
Register for free for the MarTech Conference, taking place online Sept. 2, 2026.
