Data Governance - The Unsung Hero of Performance Marketing

Editors note: Adverity is a LinkedIn Marketing Partner for Reporting & ROI, Lead Generation, and Audiences. Learn more about Adverity’s integration with LinkedIn. 

According to Accenture research, by 2025 we will be producing data at a rate of 463 billion gigabytes per day. To put that perspective: in 2009, the world’s entire digital storage capacity was “just” 487 billion gigabytes. By tomorrow’s standards, we’d fill that volume in under two days.

Marketers are expected to make sense of all this data, sifting through the exabytes to derive insights and plan effectively, but how is the question 

In this blog, we’ll explore how teams can implement data governance frameworks to make smarter, more profitable decisions.

Understanding the data-driven marketing landscape

Part of the issue is that as a marketer, you’re forced to juggle data from numerous sources — online, offline, across various channels — each piece crucial in mapping out the effectiveness of campaigns. However, the challenge lies in connecting this data with real business outcomes, like revenue, to understand what’s working and what isn’t. Data silos, fragmented insights, and unclear performance signals complicate this effort. To truly leverage the power of data, you need a smarter, performance-driven measurement framework that aligns marketing activities with overall business goals.

Now is the perfect time to step back, audit your current marketing analytics setup, and refine it for future success. By doing so, you’ll not only connect data to business outcomes but also ensure your marketing strategy is aligned with driving revenue.

Importance of a solid data foundation

Data silos, inconsistent data collection, and quality issues can wreak havoc on marketing efforts. Even small data errors can lead to big business problems, affecting both day-to-day operations and long-term scalability. For instance, imagine trying to target an audience in the United States but finding customer locations listed as “CA,” “California,” and “Calif.” Without standardizing states and countries, it’s nearly impossible to create accurate audience segments, leading to wasted ad spend and missed opportunities. Building a solid data foundation helps avoid these pitfalls, setting teams up for success and ensuring they can adapt to future demands.

Ensuring your marketing data is reliable and up-to-date may seem straightforward, but many businesses struggle with data management, often at a significant cost. In fact, poor data quality can lead to up to 20% revenue loss annually, with organizations potentially facing costs of $12.9 million per year due to data inaccuracies, according to IBM. 

This underlines the need for robust data governance frameworks that enable marketing and sales teams to manage, secure, and access data consistently. For the uninitiated, data governance encompasses the processes, standards, and roles needed to safeguard, organize, and maintain high data quality. 

Key components of a data governance framework include:

1. Foundational governance:

• Security: Implementing measures to protect data from unauthorized access and breaches and adhering to regulations like GDPR. 
  • An example of this would be encrypting customer payment details in your eCommerce platform to prevent unauthorized access, while implementing multi-factor authentication (MFA) for all employees accessing sensitive systems.
• Access and data stewardship: Establishing clear documentation of who owns and has access to data within platforms, including managing permissions and creating processes to govern access. 
  • In practice, this might look like restricting access to customer credit card information in Stripe to the finance team, while allowing the marketing team to access anonymized purchase trends for campaign optimization.

2. Structural governance:

• Classification: Organizing data through systematic classification and using data dictionaries to ensure consistency and proper data placement. 
  • One example of this could be organizing customer data by segmenting it into categories like demographics, purchase history, and engagement metrics, ensuring consistent labels such as “Customer Age” and “Last Purchase Date” across all platforms for streamlined analysis.
• Transformation: Setting rules for standardizing data values and ensuring data is appropriately formatted. 
  • For example, standardizing location data enables accurate geo-targeting for future campaigns.

3. Quality governance:

• Monitoring: Setting up alerts and notifications for errors, inconsistencies and incomplete data.
  • In practice, this could involve setting up automated alerts in your analytics platform to flag anomalies, such as a sudden spike in website traffic with no corresponding increase in conversions, so your team can quickly investigate and address potential issues.
• Reconciliation: Proactively checking data for inconsistencies, missing elements and anomalies to improve overall data quality. 
  • An example of this would be comparing monthly revenue reports from Shopify with ad spend reports from Google Ads to resolve discrepancies in ROAS calculations, ensuring accurate performance tracking.

The process of tying revenue to sales and marketing activities begins long before you start analyzing. It requires collecting relevant, high-quality data from the outset. Without a solid system to gather and cleanse this data, any conclusions drawn could be flawed, limiting your ability to connect campaigns with revenue effectively. 

Check out Adverity’s data governance checklist to make sure your data foundations are up to scratch, or for more on this you can check out Adverity’s full guide to data governance here.

Essentials for effective data management

To build a strong data foundation, early alignment between departments is critical. Marketing, sales, and data teams need to agree on what data is being collected, why it’s important, and how it will be used. Establishing clear data requirements helps ensure that everyone is on the same page, and that the data collected will provide value across the entire organization.

Data quality is another essential factor. Ensuring the data entering your reports is accurate and consistent will enable you to trust the insights and make informed decisions. Regular checks for errors, duplicates, or missing data will prevent issues from snowballing. Additionally, marketing teams should consistently evaluate their KPIs and adjust reports to stay aligned with changing business priorities. Access to historical data allows you to analyze different metrics over time, providing a complete view of performance.

Don’t forget about system maintenance — CRM systems, data visualization tools, and storage solutions all need proper management to ensure they function smoothly. Keeping CRM hygiene top-notch will help you merge data from sales, marketing, and other departments seamlessly. A well-maintained CRM ensures that your data is clean and organized, allowing you to draw meaningful insights from combined sources.

Adverity integration with LinkedIn Ads offers the granularity you seek

Imagine a potential customer’s journey that starts with a casual scroll through LinkedIn, progresses to engaging with a webinar, and ends with a demo request. For marketers, understanding how each touchpoint contributes to the final sale is essential for measuring the true impact of their campaigns.

As Emily Gustin, Senior Associate for Business Development at LinkedIn, explained on a recent podcast, “When you have a little bit more visibility on how stuff is actually converting, you're able to see that link pretty clearly.”

However, mapping out these touchpoints and linking them to actual sales can be complex. That’s where Adverity’s integration for reporting comes in. Granular attribution metrics enable marketers to track these interactions and directly attribute their efforts to pipeline growth and revenue, providing a comprehensive look at how LinkedIn campaigns contribute to business outcomes.

One of the key ways you can measure revenue and effectively track business outcome metrics is through integrations such as Adverity’s with LinkedIn Ads. By integrating LinkedIn’s reporting capabilities with CRM data, marketers gain a clearer view of how their LinkedIn campaigns drive key metrics like revenue and opportunity win rates. This approach not only helps connect marketing efforts to business outcomes but also supports cross-team collaboration by providing comprehensive data insights that inform strategic decisions.

Unlocking the power of a solid data foundation – what’s next?

A strong data foundation isn’t just about accuracy; it’s about driving adaptability and success in your marketing campaigns. Data without a purpose holds no value, but when tied to revenue, it becomes a powerful tool for shaping strategies. Marketers must focus on connecting their data, ensuring it is accurate, and using it to make decisions that align with business goals.

By tying data directly to revenue, you can fine-tune KPIs and make sure they evolve alongside your business. This alignment leads to measurable outcomes, enabling impactful budget shifts and investments in channels that drive results. Furthermore, understanding the buyer’s journey through precise data allows you to refine campaigns, adapt your strategy to customer behavior, and even link brand awareness efforts to tangible sales outcomes.

With a consistent and well-organized data strategy, you can unlock a host of possibilities: focusing on regions or campaigns that bring the biggest returns, polishing marketing approaches to match buyer needs, and ultimately driving more significant business success.

Conclusion

In summary, understanding and managing your marketing data is crucial for long-term success. First-party data will play a vital role in the future of marketing, ensuring that every campaign, effort, and dollar spent is tied back to revenue. By adopting the right tools and maintaining a strong data foundation, you can transform raw data into actionable insights, driving both marketing performance and business growth. Now is the time to embrace data-driven marketing and ensure that your efforts consistently deliver measurable, revenue-driven results.