In an ever-changing digital and privacy landscape, the benefits of well-regulated data are many. For starters, you can count on your reporting to provide reliable information about creative effectiveness and ROI. It saves time and money, as uncontrolled data takes too much time to search through and can provide incomplete views. But with expanding data sprawl, establishing solid data foundations is the only way to access these benefits.
As part of Google’s Learn With GMP series, our Sr. Director of Tech Consulting & Architecture, Jackie Saplicki, and Sr. Director of Enterprise Data Transformation, Kosta Demopoulos, hosted a webinar on how to identify realistic and effective solutions that respect consumer privacy and help catalyze your brand toward digital maturity. Together with Google’s Ads Privacy Specialist, Lisa Tanzosh, they dove into the steps needed toward building trust in the quality of data—complete with key considerations including the importance of taxonomy in creating a functional approach. In case you missed it, you can watch the full session below, or continue reading for the main takeaways.
A strong data foundation starts with control.
For every organization, reliable data systems and good decision-making go hand in hand. At its core, that’s exactly what building solid data foundations is about: ensuring that the information we have is accessible, timely, trustworthy and fit for purpose so we can take the right steps toward our business goals. But that doesn’t happen spontaneously. Instead, it hinges on our capacity to exercise control over the data we own.
A good first step to gaining that control is building a list of all known data sources, such as ad servers, buying platforms and analytics tools. Data lives in many different places, and we need to bridge that divide in order to access a complete view.
If data lives in disparate environments, that leads to low quality. And if we have to spend all our time harmonizing that data rather than using it, we’re wasting time and, consequently, money.
Once you’ve conducted that streamlining process, the next phase is establishing data standards and rigorous governance practices to assess the quality of the data. “We can do so by leveraging media buying platforms and Cloud infrastructure to understand how the data is being reported out, how we can automate pipeline ingestion, things of that nature,” says Saplicki. “Identify vulnerable or error-prone areas and ensure that they are protected and have the proper standardization around them.”
Data quality is critical.
Proper data standardization means looking at the rules we’re using to make sure we’re off to a good start. And that includes how we’re naming things. “Solving the taxonomy challenge is a critical first step,” says Demopoulos. “A single error in an object taxonomy entry or in the glossary maintenance system will bring reporting issues, requiring manual effort to investigate the error and correct it.”
While it’s not always easy to have a full grasp of the relevance of taxonomy, the truth is this is the bedrock on which everything else is built—including all the steps that lead to more effective creative and cost-efficient campaigns. Working with Bayer, we built a highly complex but unified taxonomy that assists with analysis and provides a consistent data feedback loop. That way, the team was able to condense multiple sources of data into a single dashboard that empowered them to make optimization decisions with meaningful impact.
To build equally powerful taxonomy strings, take into account the different data sources and their specific terms and requirements. While doing so, consider future changes in the market or even within the organization. If done right, you’ll reap the rewards of this effort for years to come; and if you are ever faced with the need to make changes, minimize the risk by doing so during downtime.
Earning the trust of your organization.
A solid data foundation with impeccable taxonomy doesn’t only lead to good reporting, it also provides a common language for everyone to rely on. Especially when collaborating with external partners or even as new hires join the team, data that is labeled and structured becomes accessible to the entire organization.
Working with our partners, we break down silos and ensure the right stakeholders have rapid access to the right data.
After all, no single team is fully responsible for the data transformation program that building a solid data foundation requires. It spans data, tech, people, marketing, processes and more. Initially, putting together a series of use cases can be incredibly potent to get the buy-in from different stakeholders. As time goes by, trustable and transparent data will keep them on board.
Overall, data foundations yield unified data sets in an organized, secure environment. If you want to improve the performance of your content campaigns and access advanced solutions such as machine learning, you need complete, standardized data. Especially now that the privacy landscape is changing, there’s no better time to buckle down and bolster your journey toward digital maturity.
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