Today’s consumers take complex journeys across multiple channels, with limited exposure to any one particular ad. For marketers, that means that the conversion path is fragmented, and it can be hard to connect the dots. Since users engage through various offline and untrackable online touchpoints (like billboards, word-of-mouth recommendations, or shared links), marketers cannot get a full view of the journey. Without that data, it’s impossible to accurately measure campaign impact or assign a reliable score for their contribution to the final purchase.
Performance marketers and advertisers are navigating these shifts and looking for new ways to capture insights into attribution to understand which tactics and strategies are working. Open web advertising offers lots of new possibilities, but requires a novel way of approaching attribution measurement.
Here, we’ll take a deeper look at the trends affecting performance marketing attribution, and how modern performance advertisers can adapt and succeed.
Attribution Challenges for Performance Advertisers
Attribution isn’t just a technical challenge — it’s a critical business necessity. Marketers need accurate attribution models to know which campaigns are actually working and to effectively allocate their budget toward the most promising target audiences. Without a clear view of outcomes, or at least a serious effort to create a clear view, you risk wasting money on ineffective campaigns or, worse, misinterpreting data and funneling funds into activities that appear successful, but are ultimately meaningless.
Here are the key challenges marketers are facing today:
1. Fragmented Customer Journeys
Customer journeys are no longer linear, and they vary widely across touchpoints and devices. Consumers have more options than ever for researching and purchasing products, which leads to complex paths that can be very challenging to track. Without a full view of the journey, attribution can be incorrect, which can hurt the bottom line.
2. Privacy and Data Restrictions
With the adoption of GDPR and other new privacy standards, performance marketers must pay close attention to regulations when capturing and using customer data. While first-party data — information collected directly from your own users — is generally considered the most future-proof foundation for high-performance targeting, it isn’t the sole path forward. Marketers can also still leverage broader data ecosystems for personalization by ensuring they have a valid lawful basis, e.g., consent, under frameworks like GDPR. As major players like Google continue to maintain support for third-party cookies (for now, at least), balancing owned data with privacy-compliant third-party signals is still a viable route for reaching new audiences on the open web.
3. Cross-Device and Cross-Platform Measurement
In addition to regulatory changes, the future of third-party cookies continues to flip-flop, so it’s become much more challenging to plan effective tracking of user interactions across multiple devices and platforms. It’s common to have gaps in conversion tracking, making it harder for marketers to analyze data and, ultimately, to prove ROI.
Attribution on Open Web vs. Walled Gardens
The “walled gardens” of Google, Meta, and others are digital ecosystems run by a single company, which controls data measurement and access. Walled gardens offer precision within their own ecosystem due to deep first-party data, but they create silos and attribution conflicts. In addition, walled garden attribution models tend to over-attribute and may skew the credit toward a single platform.
These platforms differ quite a bit from open web options for marketers, so their attribution models also differ dramatically. Open web attribution brings more opportunity to unify data points across various digital touchpoints, which is essential as customer journeys become more complex and user fatigue grows.
Here’s an overview of the differences between open web and walled-garden approaches:
| Characteristic | Open Web | Walled Gardens (Google/Meta) |
| Ecosystem | Diverse, open. | Closed loop. |
| Data | Third-party cookies. | First-party data reliance. |
| Transparency and flexibility | Using various tools and platforms is possible. | Limited visibility into raw data. |
Characteristics of Open Web Attribution Models
Diverse Ecosystem
The open web consists of countless publishers and ad tech partners, making it a fragmented environment for tracking.
Reliance on Third-Party Data
Historically, the open web has relied on third-party cookies for cross-site tracking, but there remains a lot of indecisiveness about their future, making them tough to build future plans around.
Transparency and Flexibility
Advertisers can choose the attribution tools and platforms they prefer on the open web, instead of relying on the proprietary tools from closed systems. That allows for more flexibility and transparency in how data is collected and analyzed.
Characteristics of Walled Garden Attribution Models
Closed-Loop Systems
These platforms have their own logged-in user bases, allowing them to track user behavior and conversions within their ecosystem with high accuracy.
First-Party Data Reliance
Walled garden platforms rely heavily on their extensive first-party data to attribute conversions, which is less affected by third-party cookie restrictions.
Limited Visibility
Advertisers using these platforms have limited visibility into the raw data and must rely on the platform’s reported metrics, which can make it difficult to compare performance across different channels.
What to Prioritize to Ensure Robust Attribution on the Open Web
Like any other digital channel, the success of open web projects ultimately hinges on performance. Every business should define its own key performance indicators (KPIs), but the top priority is always the tangible business outcome, such as generating leads, sign-ups, or actual revenue.
The most frequent error marketers make is over-relying on a single attribution model, which risks skewing results and leading to flawed conclusions. When you’re building an attribution model for the open web, consider combining that with marketing mix modeling (MMM) and incrementality testing for best results. These three methodologies — advertiser-owned model; MMM; and incrementality testing — are complementary, and when you combine them in a unified framework, they provide the most comprehensive, accurate, and actionable view of marketing performance. Each methodology answers different questions and compensates for the others’ limitations.
The open web offers a ton of opportunity, but you’ll need a solid strategy and the right technology to quickly test, learn, and optimize. As you’re planning for this new paradigm, both in strategy and choosing a platform provider, make sure to consider these key areas and what’s needed for your business:
Flexible Conversion Tracking Mechanisms
Without third-party cookies, there are a few ways to track user movement and behavior to understand where they’re converting. First-party pixel solutions put a small snippet of code (the pixel) onto a website to directly capture information on what pages a user visited, time spent on page, purchases made, and more.
Server-to-server (S2S) capabilities offer another option to track and gather data in lieu of third-party cookies. These tools share data about app or web activity between two servers, eliminating the need for cookies or other embedded measurement tools.
Comprehensive Attribution Models
Open-web attribution requires the full picture of user behavior, so consider your attribution model options carefully. Ideally, your campaigns can support various models, such as click-through and view-through conversions, depending on your goals. Timing data will also be important; use customizable attribution windows, such as 30-day click-through or 24-hour view-through. These metrics are often much richer and more useful to performance marketers than what legacy systems can offer.
Seamless Third-Party Integration
With the wealth of options on the open web, it’s possible to capture data from many sources. Make sure the platform you choose can integrate with a wide variety of partners, particularly if you plan to use multiple tools. Data transparency will make a big difference in quickly capturing and acting on data.
Segmentation and Targeting
With open web attribution becoming more common due to privacy concerns and complex customer journeys, advertising platforms have developed new features for efficiency and better results. Look for automated audience generation, which automatically creates audiences for remarketing and lookalike targeting. Also explore the option of exclusion capabilities, which give marketers the ability to use conversion data to exclude existing customers from campaigns. This is a key feature for efficiency and budget management.
Getting Started With Open-Web Attribution
The open web may seem like a wild world to explore, but it can provide greater control and more effective ad campaigns for marketers, plus more opportunities to capture first-party data and use it wisely.
