Why Online Marketing Performance on Meta (And what you can do about it)
In the last year, many advertisers have noticed a decline in the performance of their Meta ad campaigns. While some of this might be attributed to broader economic factors, a significant portion stems from technical and systemic changes within the advertising ecosystem.
Meta’s attribution windows, evolving data privacy restrictions, and the resulting decline in event matching quality have collectively introduced challenges for marketers. Here’s a deep dive into why this is happening and what it means for your campaigns.
The Attribution Window Problem
Meta’s default attribution windows have shifted in recent years, moving from a standard 28-day click and 1-day view window to shorter windows such as 7-day click and 1-day view. This change, while aimed at adapting to privacy changes and user tracking limitations, has had a profound impact on advertisers:
Fewer Conversions Captured: Longer sales cycles, especially for higher-value products, are now underrepresented in Meta’s reporting. Sales that would have been attributed under the previous windows are now falling outside the attribution window.
Incomplete Campaign Insights: Shorter attribution windows mean less visibility into how campaigns perform over time, leading to inaccurate performance assessments and missed opportunities for optimization.
Marketers must now adapt to this compressed reporting model, which can create the illusion that campaigns are less effective than they truly are.
Data Privacy Restrictions: The ATT Fallout
The introduction of Apple’s App Tracking Transparency (ATT) framework has arguably been the single biggest disruptor to Meta’s advertising ecosystem. ATT requires apps to get explicit permission from users to track their activity across other apps and websites, and the majority of users have opted out.
The result?
Reduced Visibility: Meta can no longer track user behavior as effectively on iOS devices, leading to gaps in data and underreported conversions.
Less Accurate Targeting: With incomplete tracking, Meta’s algorithm has less data to optimize campaigns, making it harder to deliver ads to the right audience at the right time.
Worsened Event Matching: Without cross-app tracking, Meta is increasingly reliant on the data advertisers send through their own tracking tools. However, limitations in tracking setups and privacy-compliant environments can lead to missing or mismatched events.
The Impact of Incomplete Data on Event Match Quality
Event matching quality (EMQ) is critical for Meta’s algorithm to function effectively. EMQ measures how well Meta can match conversion events (e.g., purchases, sign-ups) to the users who performed them. A decline in EMQ leads to:
Weakened Algorithmic Optimization: When event data is incomplete or inaccurate, Meta’s machine learning models are less effective at identifying patterns and finding high-value users.
Higher CPAs: Lower EMQ reduces the efficiency of Meta’s bidding strategies, causing costs to rise and performance to decline.
Missed Retargeting Opportunities: With lower-quality data, retargeting campaigns may fail to reach users who have meaningfully engaged with your brand.
Factors such as browser privacy features (e.g., Intelligent Tracking Prevention on Safari) and limitations on first-party tracking implementation exacerbate this issue, further degrading EMQ.
What This Means for Online Marketing
The combined effects of shorter attribution windows, privacy restrictions, and lower EMQ have created a storm of challenges for advertisers:
Inaccurate Reporting: Campaign results may look worse than they are, leading to poor decision-making and premature pausing of potentially profitable campaigns.
Higher Costs: With Meta’s algorithm struggling to optimize effectively, advertisers often face higher Cost Per Acquisition (CPA) and lower Return on Ad Spend (ROAS).
Difficult Scaling: Scaling campaigns successfully requires confidence in your data and targeting, but the current environment makes it harder to trust the insights you’re getting.
How Advertisers Can Adapt
While these challenges are significant, there are ways to mitigate their impact and regain confidence in your Meta advertising campaigns:
Invest in Server-Side Tracking: Tools like server-side tracking allow you to send data directly to Meta, bypassing browser restrictions and improving EMQ.
Experiment with Attribution Models: Look beyond Meta’s default attribution windows by exploring tools that offer first-click, last-click, or multi-touch attribution to gain a clearer picture of your campaigns’ performance.
Leverage First-Party Data: Build and strengthen your own customer database to create audiences for targeting and retargeting, reducing reliance on third-party data.
Monitor Campaign Performance Holistically: Combine Meta’s reporting with analytics from other tools to cross-verify results and uncover hidden insights.
How MarvelPixel Can Help
MarvelPixel is specifically designed to address the challenges media buyers face in the current environment. By offering server-side tracking and enhanced event matching, MarvelPixel ensures that your data is more accurate and complete, significantly improving your Event Match Quality (EMQ).
Additionally, MarvelPixel enables first-click, last-click, and linear attribution reporting, providing a holistic view of your campaigns’ performance. This means you can identify the true impact of each marketing channel and allocate your budget more effectively, even in the face of privacy restrictions.
With MarvelPixel’s tools, you can also track key metrics like bounce rates, landing page performance, and ad ROAS across attribution models—all in one platform. This helps you regain control over your data, optimize campaigns with confidence, and maximize your returns in a privacy-restricted advertising landscape.
The future of Meta advertising is all about adapting to new realities. With MarvelPixel, you can stay ahead of these challenges and ensure that your campaigns are both efficient and profitable, no matter how the ecosystem evolves.
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