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Maintaining high-quality marketing data is becoming more difficult as digital ecosystems grow increasingly complex. In this article, Google Analytics pioneer Brian Clifton shares actionable insights on how to ensure data accuracy, align global teams, and prepare your organization for a privacy-first future.
With decades of experience in digital analytics, Brian Clifton has observed a consistent challenge across industries and regions. Even with a solid initial setup, marketing data quality often degrades quickly. Websites are frequently updated, product launches introduce new tags, and turnover among staff and agencies leads to inconsistent practices.
The problem is subtle but serious. Poor-quality data often looks identical to good data. There are rarely visible red flags, and even when issues exist, they can be hidden beneath noisy reporting or incomplete dashboards.
According to Brian, marketing teams should monitor data quality just as consistently as they monitor conversion rates. In other words, measuring the quality of your data should be considered a core performance metric.
Over the years, Brian has audited hundreds of enterprise setups and found that even digital-first companies often struggle to maintain data accuracy. This widespread issue led him to co-found Verified Data, a platform that automates Google Analytics audits and helps identify quality issues at scale.
To maintain accuracy and consistency in campaign data, two principles are key: coordination and centralization.
Coordinate campaign tracking
Training teams on how and why campaign tracking is implemented is essential. This coordination should not be a one-time initiative but an ongoing process. A kickoff workshop can provide a foundation, followed by weekly or bi-weekly check-ins to ensure marketers stay aligned and are aware of evolving tracking standards.
Marketers should also feel empowered to solve tagging challenges creatively. A well-coordinated team knows how to apply consistent logic, even when no out-of-the-box tracking solution is available.
Centralize responsibility
While teams across regions and business units should have autonomy to run campaigns, there should be a centralized owner of campaign tracking. This person or team takes responsibility for training, reviewing, and maintaining consistency across departments.
When campaign tracking is not centralized, results become fragmented. Teams cannot compare campaign performance across markets, and valuable insights get lost. Independence in campaign execution is fine, but measurement requires a coordinated ecosystem to ensure results are valid and actionable.
Brian makes an important distinction between being data-driven and being data-informed.
Both approaches are necessary. Being data-driven helps you act quickly and survive in a fast-changing market. Being data-informed helps you learn, adapt, and avoid repeating the same mistakes. Organizations need both to thrive.
Many organizations hesitate to invest in analytics due to limited resources. Brian suggests a mindset shift. Digital is no longer optional. The pandemic made it clear that the online channel is essential for business continuity and growth.
For companies with small internal teams, a strong partnership with a reputable agency or consultancy can fill capability gaps. The key is ensuring knowledge transfer. Agencies should not just deliver results—they should also help internal teams grow their skills and own more of the analytics process over time. This reduces long-term dependency and enables better internal decision-making.
Looking ahead, Brian predicts that this decade will bring significant shifts in how consumers think about privacy—and how platforms monetize data. As awareness grows, he anticipates the decline of personalized ads as we know them.
This shift will likely require marketers to adopt new measurement strategies and rethink how they target and engage audiences. Organizations that build a strong data foundation today will be more adaptable in a future where third-party data becomes harder to access and trust becomes a competitive advantage.
Marketing data quality is not something you fix once and forget. It requires continuous oversight, cross-team alignment, and centralized responsibility. As analytics matures and privacy expectations evolve, organizations that treat data as a strategic asset will be the ones positioned to make smarter decisions and build long-term value.
Brian Clifton’s advice is clear. Focus on governance. Train your teams. Monitor quality. And embrace both real-time responsiveness and long-term learning.
Marketing data quality often suffers due to website updates, CMS changes, staff turnover, and inconsistent campaign tracking practices. These factors introduce errors that may go unnoticed unless data is continuously monitored.
Organizations should coordinate campaign tracking through regular team training and assign a central owner to enforce standards. This ensures consistency across markets and enables valid comparisons of campaign performance.
Data-driven decisions are made in real time using immediate inputs, while data-informed decisions rely on accumulated data, pattern recognition, and long-term learning. Both approaches are necessary for strategic agility.
Partnering with an experienced agency that emphasizes knowledge transfer allows internal teams to build skills while scaling analytics capacity. Over time, this reduces dependence and improves efficiency.
Privacy expectations are rising, and the use of third-party data is being reevaluated. As a result, marketers should prepare for a shift away from personalized advertising and focus on building trust and first-party data strategies.