Being data-driven is a top priority for most marketers. In fact, 99% of marketers agree that an effective data-driven marketing strategy is crucial to achieving success.
Although we know the transformation from siloed reports to cross-channel insights will require new tools, new processes, new skills, and clear leadership, we often overlook two fundamentals that are the bedrock of data-driven marketing: data ownership and data integrity.
Instead of having real-time access to our performance data, we commonly have data that's held "hostage" in execution tools or with agencies, and that data may or may not be owned by us or even contractually accessible. And even if our partners provide reports, the reports often have missing data or they come in late, allowing us little or no time to respond to findings and adjust course.
Though we marketers trust our media partners, we must ultimately own, integrate, and align all performance data. That way...
- We can audit and validate it, and get the full picture of what's working and what's not.
- We would get not only 24/7 visibility into how marketing is performing but also faster reporting, analysis, and optimization cycles to make better, faster decisions.
- And by aligning our agency relationships around clear business goals and KPIs, we would build a more strategic relationship that unlocks the potential of a truly data-driven partnership.
One might assume that taking control of our data starts by finding new partners, but that's not necessarily the case. Marketers have successfully made the leap from siloed reporting to complete data ownership through a close collaboration with their existing partners. They all started with the common understanding that data ownership doesn't happen overnight. It is a deliberate journey that delivers benefits to both parties each step of the way.
Consider these nine tips as you embark on the path to bringing your data in-house and making data the foundation of your marketing organization's efforts.
1. Define your vision for the future
Before you start, get a consensus on what you wish to accomplish with your data. What do you want to measure? What do your teams want to learn? How will the data be used?