The Challenges of Cross-Device Attribution in Performance Marketing
Performance marketing begins with a clear set of campaign objectives. It involves launching marketing campaigns on digital channels to drive desired actions from customers.


To understand how their ads are performing, marketers use cross-device attribution. This allows them to see the full customer journey, including their interactions with different devices.

1. Inaccuracy
The ubiquity of smart devices is expanding the possibilities for how people connect with brands. But, with the multitude of new touchpoints comes complexity.

It is difficult to understand the full path that leads to a conversion, particularly when users are not always logged in on each device or take large breaks between sessions. This is why cross-device attribution models are so important.

These models allow marketers to measure the impact of a campaign across devices and platforms. It’s also an opportunity to improve ad spend by understanding which ads and campaigns drive the most value and where to allocate budgets. These models are not perfect, but they help to provide actionable insights into marketing performance.

2. Complexity
Developing robust tracking systems that can establish unified user profiles across devices is a major challenge. Consumers often start a journey on one device, then switch to another to complete it, resulting in fragmented profiles and inaccurate data.

Deterministic cross-device attribution models can overcome this problem by stitching users together using known, definitive identifiers like an email address or cookie ID. However, this method isn’t foolproof and relies on users being logged in on every device. Furthermore, data privacy regulations such as GDPR and CCPA make it difficult to track users without their consent. This makes relying on probabilistic tracking methods more complex. Fortunately, methodologies such as incrementality testing can help marketers overcome these challenges. They allow them to gain a more accurate picture of the customer journey, enabling them to maximize ROI on their paid marketing campaigns.

3. Time Decay
When marketers have accurate cross-device data, they can create better campaigns with clear visibility into the value of their advertising traffic sources. This enables them to optimize budget allocation and gain higher ROI on marketing investments.

Time decay attribution models take a more dynamic approach to attribution by acknowledging that recent interactions have a stronger impact than earlier ones. It’s an excellent tool for businesses with longer sales cycles that rely on nurturing consumers over the course of several weeks or months before closing the sale.

However, it can often undervalue initial top-funnel marketing efforts that help build brand awareness and consideration. This is due to the difficulty of identifying users across devices, particularly when they aren’t logged in to their accounts. Fortunately, alternative methods like signal matching can provide accurate cross-device identification, which is necessary to get a more complete picture of conversion paths.

4. Scalability
Unlike single-device attribution, which relies on web cookies, cross-device attribution requires unified user IDs to track touchpoints and conversions. Without this, users’ data is fragmented, and marketers cannot accurately assess marketing performance.

Identity resolution tools like deterministic tracking or probabilistic matching help marketers connect device-level data to unique user profiles. However, these methods require that users be logged in to all devices and platforms, which is often impractical for mobile consumers. Furthermore, privacy compliance regulations such as GDPR and CCPA restrict these tracking capabilities.

The good news is that alternative methods are addressing this challenge. AI-powered attribution models, for example, leverage vast datasets affiliate tracking software to uncover nuanced patterns and reveal hidden insights within complex multi-device journeys. By using these technologies, marketers can build more scalable and accurate cross-device attribution solutions.

5. Transparency
When it comes to cross-device attribution, marketers need to be able to trace individual users’ journeys and give credit to each touchpoint that contributed to conversion. But that’s easier said than done. Cookies aren’t always consistent across devices, and many consumers don’t consistently log in or take long breaks between sessions. Privacy regulations like GDPR and CCPA limit data collection, further blurring the picture for marketers.

The good news is that technology exists to overcome these challenges. Using probabilistic matching to establish unified IDs, marketers can track and identify user data, even when cookies aren’t available or aren’t working properly. By relying on this method, you can still gain a clear understanding of your audience’s multi-device journey and how each marketing touchpoint contributes to conversion.