Building a Future-Proof Data Foundation

Over the past few weeks we’ve been going deeper into the role of validation and calibration in marketing measurement. This is the fifth post in a series of posts derived from our recent webinar. Catch the full event on demand here, also read the first, second, third, and fourth posts.

The success of any marketing measurement strategy hinges on the strength of its underlying data foundation. Without consistent, reliable, and actionable data, even the most sophisticated methodologies—like MMM, incrementality testing, or attribution—can falter. During the webinar, panelists highlighted the critical steps marketers must take to ensure their data infrastructure is both robust and future-proof.

1. Track Everything

“Collect as much data as possible, with as much granularity as possible,” emphasized Will Burghes, Head of Professional Services at Rockerbox.

A comprehensive data collection strategy is the cornerstone of future-proofing. This means going beyond basic metrics and capturing detailed, nuanced data across every touchpoint—whether from ad platforms, onsite interactions, or external factors like economic trends.

Why it matters:

• Having detailed historical data allows for more accurate modeling and analysis, especially when building tools like MMM that rely on long timeframes.
• Granular data enables marketers to dig deeper into channel performance, uncover hidden patterns, and adapt quickly to changing consumer behaviors.

However, Burghes also cautioned against neglecting privacy and compliance standards, underscoring the importance of collecting data ethically and securely.

2. Standardize Taxonomies

A strong data foundation isn’t just about volume—it’s also about structure. Eli Hile, Senior Director of Data and Analytics at Tombras, stressed the importance of consistent taxonomies—the way campaigns, channels, and tactics are labeled and organized.

“If your taxonomies are inconsistent across campaigns or platforms, you’re setting yourself up for a nightmare when it comes to analysis,” Hile warned.

Best practices include:

• Create a unified framework: Define clear naming conventions for campaigns, channels, and tactics, ensuring consistency across all teams and partners.
• Categorize by hierarchy: Use a tiered structure (e.g., Channel → Sub-Channel → Tactic) to enable easier roll-ups and comparisons.
• Future-proof your framework: Design taxonomies with scalability in mind, anticipating the integration of new channels or emerging technologies.

By standardizing taxonomies, marketers can avoid “scavenger hunts” to reconcile data inconsistencies—an all-too-common challenge when working with multi-year datasets.

3. Maintain Data Hygiene

“Regular data audits are non-negotiable,” noted Aoun Jafarey, Senior Vice President of Client Solutions & Data Science at Publicis Groupe.

Data hygiene is the practice of ensuring your data remains accurate, complete, and up-to-date. As methodologies and technologies evolve, legacy data structures or errors can become major obstacles.

Actionable steps for data hygiene include:

• Regular audits: Periodically review your data systems to identify gaps, outdated taxonomies, or inconsistencies.
• Dealing with duplicates: Remove redundant entries or mislabeled campaigns to ensure clarity.
• Adapting to change: Stay ahead of emerging trends, such as privacy regulations or shifts in channel performance, and update your systems accordingly.

“Think of your data like a tree,” remarked Burghes. “The best time to plant it was years ago; the second-best time is today.”

4. Build with Flexibility in Mind

Future-proofing isn’t just about the present; it’s about preparing for what’s next. Jafarey highlighted the importance of creating infrastructure that can adapt to evolving methodologies and technologies.

Key considerations:

• Invest in tools with scalability: Choose platforms and technologies that can handle increasing volumes of data and integrate with new sources.
• Centralize your data: Consolidate data from disparate platforms into a single warehouse or BI tool (e.g., Snowflake, Tableau, Power BI) to ensure a holistic view.
• Enable accessibility: Make data readily available to analysts and stakeholders, ensuring they can extract insights quickly and efficiently.

The Long-Term Payoff

Panelists agreed that a strong data foundation is an investment that pays dividends. Consistent, well-organized, and future-ready data enables brands to:

• Build more accurate models with longer time horizons.
• Run seamless, repeatable testing and validation efforts.
• Quickly adapt to new channels, tactics, or market conditions.

As Hile summed up, “Data isn’t just a resource; it’s your competitive edge. The more reliable and actionable your data, the more agile and effective your marketing efforts will be.”

By adopting these best practices, marketers can ensure that their measurement strategies are not only robust for today’s challenges but also resilient against the uncertainties of tomorrow.