Walled Garden Attribution is Making Things Worse, Not Better

Share:

As campaign performance and audience data become increasingly disjointed behind higher walls, advertisers are left scratching their heads.

How do we maintain control while simultaneously handing over the keys to major advertising platforms? Because let’s face it – many more walled gardens are popping up on the horizon with no end in sight. 

But before we get to the nitty-gritty, let’s take it from the top. 

What is a Walled Garden?

A walled garden is any platform or experience where consumers provide their data and personal information, which is then used for targeted advertising. 

What makes an experience a walled garden, more specifically, is that the information is not shared between different platforms. 

This contrasts with the previous industry standard of third-party cookies or data-sharing agreements. 

Privacy laws are increasing pressure on these platforms to prevent data from being shared outside their ecosystems.

Classic examples of walled gardens include Google, Meta, and Amazon, where consumer activity is tracked and used for advertising, but advertisers can’t access all that information, nor is it shared between platforms.

Why Walled Gardens Are Problematic for Attribution

As the walls between platforms grow higher and data sharing becomes more limited, advertisers are left with two choices: blindly trust walled gardens or find a better way around these black-box systems.

For advertisers locked into several walled garden advertising platforms, strategizing cross-channel campaigns becomes increasingly challenging as audience data and attribution stay platform-side. 

These platforms only have visibility into their own data, and even when advertisers clearly see audience impact, it is even more difficult to attribute accurately given the lack of transparency and information sharing.

The digital advertising industry can no longer reliably outsource attribution to these walled gardens because the information provided is increasingly limited.

Inflation and Its Impact on Media Buying and Attribution

Current economic pressures, including inflation, are pushing advertisers to do more with less; for example, in our media portfolio, we are seeing year-over-year (YoY) cost per clicks (CPCs) at least 20% higher. Rising costs create a real constraint for advertisers’ ability to drive incremental growth at the same level of YoY media spend. A task many of us are all too familiar with. Needless to say, it is easier said than done.

These macroeconomic pressures add additional stress to optimize media spend and create more effective attribution models. 

With high expectations, combined with higher walled gardens, advertisers are looking for independent alternatives—ones with better attribution and transparent systems.

Challenges in Managing Attribution Across Platforms

It’s fair to say that advertisers face their share of significant challenges when trying to manage attribution across different platforms like Meta, Google, and CTV. 

Each of these walled gardens has a vested interest in keeping media spend within their ecosystems. 

This often leads to self-serving and biased attribution reports. Even if a platform wants to provide unbiased measurement, it can’t because it lacks access to data from other platforms. 

For example, Meta will want to take more credit for any clicks or impressions within its platform to drive an increase in ad spend. A true catch-22 situation.

This is compounded by the fact that these platforms automate campaigns, bids, and budget strategies based on their own attribution models. 

So, what is the solution? Advertisers need to solve for attribution independently and control the bidding algorithms based on independent attribution models.

A Triangulated Approach to Attribution

To address attribution effectively, it’s crucial for advertisers to understand the questions they aim to answer with attribution. Often, we seek to determine the optimal paid media spend for a particular tactic or channel. 

A triangulated approach between three inputs—business KPIs (key performance indicators), incrementality testing, and media mix models (MMM)—can help.

1. Business KPIs Business KPIs, such as YoY (year-over-year) Revenue, should be one of the key factors in determining if a particular tactic or channel is driving the expected outcomes and whether investment should be altered. Over-reliance on click-based MTA (multi-touch attribution)  models can lead to business contraction.
2. Incrementality Testing Incrementality testing involves running A/B experiments or test and control setups among statistically significant sample sizes. This approach provides precise elasticity of what a particular channel or tactic offers (e.g., 10% incremental new customers). However, incrementality tests can only account for the inputs they have and can take time to provide results.
3. Media Mix Models (MMM) MMMs are models trained on historical channel spend and impact, such as daily store revenue. They are great for providing correlation, indicating expected results based on spend. However, MMMs are limited by causation, which is why continuous training with the results of incrementality tests is crucial.

Advertisers can take a more balanced and effective approach to attribution by not chasing any single signal and observing business KPIs alongside MMM and incrementality testing. 

The challenge is then to feed this information back to the walled gardens.

Technical Solutions for Attribution

Marketers need to step into a more technical understanding by leveraging APIs and connection points provided by walled gardens to feed attribution models back into these platforms. 

At Adlucent, we handle this for multiple advertisers through our Adlucent Index™ technology, building custom integrations with platforms like Google and Meta to train their automated campaigns on external attribution models.

Now what?

To improve attribution strategies, advertisers need to adopt a triangulated approach, combining business KPIs, incrementality testing, and MMMs. 

By doing so, they can achieve a more holistic view of their advertising efforts and drive more effective outcomes.

The industry should continue to move towards more transparent and collaborative practices to enhance attribution accuracy and effectiveness.

Are you looking for a partner to navigate the complexities of a data privacy world? Let’s prove outperformance has no limit.

Matt Zeiger