Table des matières
Walled Garden - What are the impacts on your SMA analyses?
- Par Emilien Roux
- 9 min de lecture
Walled gardens, or closed ecosystems, now dominate the Social Media Advertising (SMA) landscape, with platforms like Facebook, Instagram, Pinterest, and TikTok leading the way. These controlled environments present significant challenges for advertisers leveraging multiple digital acquisition channels. One of the most critical obstacles lies in the difficulty of linking conversions generated through SMA to the full user journey.
For those striving to optimize campaigns and gain a true understanding of performance, overcoming these limitations is crucial. In this article, we explore the impact of walled gardens on performance analysis and campaign attribution in SMA.
What is a Walled Garden?
A walled garden is a digital ecosystem where a platform strictly controls access to user data and performance information. Unlike open ecosystems, where data can flow freely between various analytics tools, these closed platforms restrict access to critical data, forcing advertisers to adhere to the rules and tools dictated by each platform. These restrictions significantly complicate campaign performance analysis and conversion attribution across the different touchpoints of the customer journey.
This means that even if a campaign appears to perform well according to the tracking tools provided by platforms like Facebook or Instagram, a comprehensive analysis of its true impact often remains incomplete—especially when compared with data from independent analytics solutions. This lack of transparency hinders a clear understanding of actual performance and prevents campaigns from being optimized based on objective data.
What is the Impact of Walled Gardens on SMA Analysis?
1. Fragmented and incomplete data
Walled gardens often provide limited and aggregated data, making it challenging to obtain a comprehensive and accurate view of your SMA campaigns. For instance, platforms like Facebook or Instagram only share global data that combines post-click and post-view metrics, complicating the granular analysis needed to understand user behavior at each stage of the journey. This data fragmentation hinders advertisers’ ability to accurately assess the contribution of each SMA channel to overall performance.
This issue is further exacerbated by the inclusion—but not isolation—of post-view sales in SMA platform reports. Post-view conversions are attributed to ad impressions even when the user did not click directly on the ad. According to our study conducted last year with 120 TrackAd clients, post-view sales account for between 72% and 96% of the conversions reported by Facebook, while these sales are often excluded by traditional analytics solutions. You can download our Meta report for more information.
2. Conversion attribution in Walled Gardens: a headache for advertisers
Attributing conversions within these platforms is particularly challenging. Traditional attribution models, such as Last-Click attribution, fail to effectively capture the contribution of each interaction throughout the user journey. For advertisers, tracking the entire customer journey across different channels becomes a daunting task, potentially leading to under- or over-evaluation of certain channels and skewing the optimization of advertising campaigns.
Take Facebook as an example: conversions reported in Business Manager often do not align with figures obtained through external analytics solutions. For one in three advertisers, discrepancies exceeding 90% in Facebook’s favor have been observed, raising questions about how these conversions are calculated. As discussed earlier, such gaps can partly be explained by the inclusion of post-view conversions—but that’s not all. Campaigns redirecting users to external domains, discrepancies in how clicks versus sessions are recorded, and the limitations introduced by iOS 14+ are additional factors that contribute to these differences.
3. The challenge of linking conversions to user journeys in walled gardens
One of the greatest challenges posed by walled gardens is the difficulty of connecting post-view conversions generated by SMA to the full user journey. In an environment where each platform keeps its data locked away, tracking a user’s complete path—from the first touchpoint to the final conversion—becomes an arduous task. For example, a user might see an ad on TikTok, visit your website through a Google search, and ultimately convert after viewing another ad on Instagram. However, for advertisers, these multiple visual interactions are often siloed, making precise attribution impossible.
This lack of visibility is particularly problematic when managing multi-channel campaigns. You might observe high performance on a specific platform but fail to understand how that performance fits into the broader user journey. As a result, your optimization efforts could be misguided.
4. The Impact of iOS 14+ on conversion tracking
Since Apple’s iOS 14+ update, restrictions on user tracking have significantly affected how conversions are measured by SMA platforms, particularly Facebook. This update introduced limitations on cross-app tracking and user data sharing, leading to an increased reliance on estimates rather than precise conversion counts.
For advertisers, this means that the data provided by Facebook may include a significant proportion of estimates—up to 20% of conversions—which can distort analyses and complicate comparisons with external analytics solutions. This reality forces advertisers to account for these approximations and adapt to a new environment where data transparency and accuracy are more constrained than ever before.
5. Case study: Atlas for Men and Facebook conversion attribution
A concrete example of the challenges posed by walled gardens is Atlas for Men, a European leader in online sales of men’s clothing and accessories. During a presentation at the One to One Monaco event in March 2023, TrackAd highlighted the difficulties Atlas for Men faced in attributing conversions on Facebook.
Atlas for Men primarily used single-touch attribution models to evaluate the performance of their campaigns. However, these models did not account for the impact of post-view sales, leading to a significant underestimation of their SMA campaign performance on Facebook. In collaboration with TrackAd, three exploratory approaches were implemented to better understand and integrate post-view conversions into their analyses: Facebook’s Meta Conversion Lift, post-view order matching via Adstrack, a tool from the agency Adsteroid, and algorithmic distribution through TrackAd.
The results revealed that total sales generated by Facebook were underestimated by 58% when focusing solely on post-click conversions. By including post-view conversions, Atlas for Men was able to reassess the true impact of their SMA campaigns and adjust their strategies accordingly, increasing investments in this channel.
What are the solutions to overcome the challenges of walled gardens?
1. Adopting a multi-touch attribution approach
To address the limitations of walled gardens, adopting multi-touch attribution models is essential. These models consider all interactions with a potential customer before conversion, allowing for a more balanced distribution of credit for conversions across the various SMA channels used, even if some of their data is siloed. At TrackAd, we provide solutions that incorporate these approaches, enabling you to better understand the true impact of each touchpoint on the customer journey.
The multi-touch approach is crucial for reconciling data from different platforms and gaining a more holistic view of campaign performance. For instance, by combining Facebook’s post-view sales data with the post-click conversions recorded by your analytics solutions, you can obtain a more accurate picture of the contribution of each interaction to the final conversion. Consequently, this enables you to finally understand the true ROI of your digital efforts.
2. Centralizing and reconciling disparate data
To overcome the challenges of data fragmentation, it is essential to use data reconciliation tools that centralize information from various walled gardens and distinguish the impact of post-click and post-view conversions. Advanced solutions should be employed to consolidate and unify data from different SMA platforms, providing a global and coherent view of the impact of digital campaigns.
The objective measurement performed by AI-powered algorithms and Marketing Mix Modeling (MMM) enables advertisers to identify the true performance of their digital acquisition efforts in SMA. By centralizing data, advertisers can break down silos and make informed decisions based on a comprehensive understanding of campaign effectiveness.
3. Testing and Adjusting Your SMA Strategies
Once an objective analytics environment is established, it’s crucial to continuously test your SMA strategies to navigate the constraints imposed by walled gardens. This involves experimenting with different ad formats, creatives, and targeting options to determine what performs best in each ecosystem. Tools like those offered by TrackAd enable advertisers to monitor the performance of various strategies in real time, providing the flexibility needed to adjust campaigns quickly and effectively.
Testing new approaches also allows you to remain agile in the face of constant algorithm changes on SMA platforms and new restrictions on user tracking. By continuously adapting your strategies with extensive A/B testing, you can maximize the efficiency of your campaigns while minimizing the impact of the limitations set by walled gardens.
4. Reassessing success metrics
Advertisers must also reassess the metrics used to measure the success of their SMA campaigns. Walled gardens often promote metrics that don’t necessarily align with real business objectives, such as sales or qualified leads. By focusing on more relevant key performance indicators (KPIs), like cost per acquisition (CPA) or return on investment (ROI), adjusted for attribution models that meaningfully integrate post-click and post-view conversions, you can better align your advertising efforts with overall business goals.
It is equally important to regularly compare the data provided by SMA platforms with that from your analytics solutions to identify discrepancies and make necessary adjustments, such as correcting SMA tag integrations or configuring conversion events. This will enable you to make more informed decisions and maximize the effectiveness of your advertising investments.
Conclusion
Walled gardens present significant challenges for performance analysis and campaign attribution in Social Media Advertising. The persistent difficulty in linking post-view conversions generated by SMA to complete user journeys remains a major issue for advertisers. However, by adopting multi-touch attribution strategies and centralizing disparate data, you can achieve a clearer understanding of your campaign performance. With these approaches, advertisers can navigate the limitations of walled gardens and optimize their strategies for greater impact.
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