5 Common Challenges in Attribution Reporting (And How to Solve Them)

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Attribution reporting is key in helping you understand which marketing efforts are working and which are falling flat. But it’s getting harder to do well. 

Customers move across channels, devices, and platforms, and new privacy rules make it harder to track their full journey.

In this article, we’ll break down five common attribution struggles and offer practical ways to handle each one.

5 Attribution Reporting Struggles + Ways to Overcome Them

1. Balancing accuracy and insight

Marketers often shift between two extremes: spending too much effort perfecting data collection methods and leaning too heavily on intuition or a false sense of assurance that “what has worked before will surely work again.” 

Neither approach offers a full picture, and both can lead to flawed decisions. 

The goal is to strike a balance between accuracy and practical application: Get the best data you can, but don’t get stuck chasing perfection. Acknowledge and accept the limitations of your work, and focus your resources and energy on testing, learning, and improving over time.

Here’s how to move forward:

• Identify your must-have data (e.g. leads, purchases, key engagement signals).
• Use that to inform lightweight tests, like changing calls to action (CTAs) or timing.
• Build in regular reviews so you’re always learning—even if your tracking isn’t perfect.

2. Fragmentation

In data science, fragmentation occurs when data is spread across different systems and locations, making it more challenging to work with. In marketing, fragmentation reflects how user behaviour spans across channels and devices.

To understand this, think about today’s customer journey: Someone might read a blog post, see a LinkedIn update later, click a Google Ad days after that, and finally convert weeks later on your website. Indeed, Salesforce estimates that it takes 6–8 touchpoints to generate a lead. Other studies suggest it could take 50 or more.

This kind of audience behaviour leads to fragmented data. That’s why unifying your data across platforms and teams is essential to understanding what drives results.

To do this:

• Use tools like Google Tag Manager, Google Analytics 4, and BigQuery to centralise your analytics.

• Get clear on shared tracking methods, such as event naming or consistent Urchin Tracking Module (UTM) parameters. 

• Use a single platform, such as Google Tag Manager, to manage tracking scripts. 

• Collect everything into a shared dashboard, such as through Looker Studio, and give appropriate team members access for better visibility.

3. Direct and indirect contribution

Content influences conversions in both direct and indirect ways:

• Direct contributions come from content that directly leads to a conversion, such as a like when a blog post results in a purchase via a tracked link. Attribution is more straightforward, as there’s an implied cause-and-effect relationship.
  
  
• Indirect contributions come from content that builds trust, educates, or keeps your brand top of mind but doesn’t directly lead to a conversion—like a social media post that builds trust or sparks interest over time. These are harder to measure but are just as important.

Because direct contributions are easier to track, they often get more credit in attribution. This is one reason companies overinvest in paid media and underinvest in organic content. 

This is a classic case of availability bias: favouring what’s easiest to measure. A strong attribution model can help reduce this bias and provide a more complete view of content performance.

The right attribution model for you depends on:

• How long your sales cycle is
• How many channels you use
• Whether you care more about conversion moments or the full journey

Popular options include:

• Single-touch: Credits only one touchpoint (usually first or last).‍
• Multi-touch: Distributes credit across several touchpoints.‍
• Next-generation: Uses machine learning to weigh the influence of each touchpoint.

4. Privacy, tracking, and third-party cookies

Recent years have brought major changes to privacy policies and practices, which make attribution more complex. Marketers can no longer track consumer behaviour as accurately, as frequently, or over as long a period of time as they used to. 

Several key industry shifts are affecting attribution in content marketing. These include changes to:

Third-party cookies

Major browsers like Chrome, Safari, and Firefox are increasingly restricting or eliminating third-party cookies, which reduces marketers’ ability to track users across multiple websites. Data is aggregated and anonymised to a greater degree, which protects user privacy but reduces accuracy and granularity. 

Privacy laws

Laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) limit the scope of data collection and require explicit user consent for tracking. 

Non-compliance can lead to fines and reputational damage, so marketers must ensure their tools respect privacy requirements. In response to these privacy laws, many platforms have had to reduce their data retention windows, making it more difficult to obtain and analyse long-term behavioural data. 

First-party data

With third-party cookies declining, marketers must rely more on first-party data—information collected directly from users through their own channels.

First-party data solutions include:

• Server-side tagging
• Cross-device tracking using first-party identifiers like user IDs or device IDs
• Consent-based data modelling in tools like Google Analytics
• Data aggregation in tools like BigQuery

Consent modes

Platforms like Google Analytics now offer consent modes that adjust what data is collected based on user consent. When data is missing, machine learning fills the gaps by estimating real-world behaviour.

Even as tracking becomes less exact, data modelling is getting smarter. As a result, you’ll still be able to draw important, high-level conclusions. Experimentation (such as incrementality testing) will enable you to make conclusions about customer behaviour and adjust your strategies accordingly.

What to do

There are a few things you can do to adapt to these changes:

• Stay up to date on user consent requirements and privacy laws to ensure your tracking methods and tools remain compliant. 

• Focus on collecting first-party data through form submissions, newsletter sign-ups, account logins, and other direct interactions on your owned channels.

• Use Google Tag Manager to link first-party tracking tools—such as BlueConic, Segment, or your customer relationship management (CRM) system—to key areas of your site.

• Try server-side tagging, which sends tracking data through your own server instead of relying only on a user’s browser.

• Use Google Analytics 4 to model data where user consent isn’t given.

5. Zero-click platforms and practices

Zero-click refers to both platforms and marketing practices that prioritise keeping users engaged without sending them to external websites. 

For example, on Instagram, links in post descriptions and comments aren’t clickable—users can’t just tap and leave the app. Clickable links are limited to bios, Stories, and ads. As a result, creators often focus on delivering value right on the platform. Users can even complete purchases without ever leaving the Instagram app or website. 

Zero-click marketing can be highly effective, but it makes attribution more challenging since tools like Google Analytics cannot track what happens inside apps like Facebook or LinkedIn.

Luckily, there are some ways around this:

• Use platform-specific tracking tools, such as Meta Pixel or LinkedIn’s Insight Tag, via Google Tag Manager.

• Monitor native engagement metrics (e.g., saves, shares, form completions).

• Aggregate cross-platform data in a tool like BigQuery to get a broader view of user behaviour.

Turn Insights Into Action with Eleven

Attribution reporting has its challenges, but it isn’t impossible. By understanding where the roadblocks are and using the right tools and strategies, you can get a clear idea of what’s working and make more confident, data-informed decisions.

If you’re ready to get more from your content and your data, download Eleven Writing’s free eBook, Introduction to Multivariate Attribution for Content Marketing, or contact us to see how we can help.