Ad attribution helps you understand which ads or channels drive customer actions like purchases or leads. But it’s not always straightforward. Common issues include short attribution windows, challenges with tracking Connected TV (CTV) ads, cross-device and cross-channel tracking gaps, outdated last-click models, and privacy restrictions limiting data collection. These problems can lead to wasted ad spend and inaccurate performance insights.

Solutions to fix these problems:

• Extend attribution windows to capture delayed conversions.

• Use view-through attribution for non-clickable CTV ads.

• Adopt multi-touch models to credit all touchpoints in the customer journey.

• Set up cross-channel retargeting to connect awareness campaigns with conversions.

• Test for incremental results using geo-lift studies or Marketing Mix Modeling (MMM).

Platforms like OTHERSIDE simplify attribution by integrating cross-channel tracking, offering real-time performance updates, and enabling fast campaign launches. Accurate attribution ensures you can allocate budgets wisely and focus on what works.

Digital Marketing Attribution in 2025: Challenges and Solutions

Common Ad Attribution Problems

Marketers across industries face ongoing challenges with ad attribution, largely due to outdated measurement methods that fail to capture the way consumers interact with brands today. Below, we break down some of the most pressing issues that complicate accurate attribution. Recognizing these problems is a crucial step toward developing better strategies.

Short Attribution Windows

Many advertising platforms rely on 1-day click attribution, which only captures a small portion of the customer journey. This method assumes that customers see an ad and immediately take action, but in reality, most conversions take much longer.

Take the automotive industry, for example. Buying a car is a decision that typically unfolds over weeks or months. A potential buyer might see a Connected TV (CTV) ad for a new SUV, research it online, visit a dealership, and finally make a purchase 30 days later. If the attribution window is just one day, the initial CTV ad gets no credit at all.

Similarly, B2B companies often deal with sales cycles that exceed 90 days. For instance, a software company running LinkedIn ads may generate leads that convert to paying customers months later. In such cases, 1-day attribution windows make these campaigns look ineffective, which can lead to budget cuts for channels that actually drive long-term value.

E-commerce brands face their own set of challenges, especially during seasonal campaigns. Imagine a shopper sees a Black Friday ad in October, adds items to their wishlist, and completes the purchase in December. A 1-day attribution window misses this connection entirely, undervaluing the role of early-funnel advertising in driving holiday sales.

Connected TV Attribution Issues

Connected TV (CTV) presents unique hurdles because viewers can’t click on TV ads. Traditional click-based models simply don’t work in this environment, leaving marketers unable to measure CTV's impact on conversions.

CTV ads are often powerful awareness tools that prompt customers to search for products later. For example, someone might see a food delivery app commercial while streaming their favorite show, then open the app 20 minutes later to place an order.

The problem is compounded by fragmented measurement. A viewer might see a CTV ad, search the brand on Google, click a paid search ad, and complete the purchase on the website. Without proper view-through attribution, the CTV campaign appears to have had no effect, while the search ad gets all the credit.

This creates a misleading picture of performance. Marketers may shift budgets away from effective upper-funnel CTV campaigns to channels that appear more successful in traditional models, ultimately hurting overall performance by neglecting the awareness-driving role of CTV.

Cross-Channel and Cross-Device Tracking Problems

Today’s consumers interact with brands across a maze of devices and channels, making it difficult for traditional attribution models to piece together the full customer journey. For instance, a shopper might see a display ad on their laptop at work, research the product on their phone during lunch, and complete the purchase on their tablet at home.

Device fragmentation is a major issue. Most attribution systems treat each device as a separate user, leading to inflated audience metrics and an incomplete view of conversion paths. This distortion makes it hard to understand how different touchpoints work together.

Cross-channel tracking adds another layer of complexity. A customer might first see a CTV ad, later click on a social media ad, and finally convert through a direct visit to the website. Without proper cross-channel attribution, these touchpoints appear disconnected, even though they’re part of a cohesive journey.

Data silos within organizations make matters worse. CTV campaigns might be managed on one platform, social media on another, and website analytics on a third. Each platform uses different tracking methods and definitions, making it nearly impossible to reconcile data across channels. This lack of integration directly impacts how campaigns are measured and optimized.

Last-Click Attribution Limitations

Last-click attribution assigns 100% credit to the final touchpoint before conversion, ignoring all the prior marketing efforts that guided the customer along their journey. This approach overlooks the role of upper-funnel activities like brand awareness campaigns, CTV ads, and display advertising.

The result is a bias toward lower-funnel channels. For instance, search ads and retargeting campaigns often appear highly effective because they capture customers who are already ready to convert. Meanwhile, awareness campaigns that created that intent in the first place receive no recognition.

This bias can harm brand-building efforts. Imagine a company runs a months-long awareness campaign across CTV, display, and social media, creating brand recognition and purchase intent. When customers finally convert through a search ad or direct visit, all the earlier work goes unmeasured in last-click reporting.

Additionally, last-click models ignore the complex journeys that lead to conversions. Customers might see multiple ads, talk to friends, read reviews, and conduct research before making a purchase. Last-click attribution treats all these interactions as if they didn’t happen.

Data Privacy and Tracking Restrictions

The rise of privacy regulations and changes in tracking technology have upended traditional attribution methods. For example, Apple’s iOS 14.5 update significantly reduced the tracking capabilities of platforms like Facebook and Google, while laws like GDPR and CCPA limit data collection across channels.

Third-party cookie deprecation has made cross-site tracking nearly impossible. A customer might see a display ad on a news site and later convert on the advertiser’s website, but without cookies to link these interactions, the display ad gets no credit.

High opt-out rates further complicate matters. Apple reports that fewer than 25% of iOS users opt into app tracking, leaving a large gap in mobile attribution data. This is especially problematic for brands that rely heavily on mobile campaigns.

Meanwhile, walled garden platforms like Google and Facebook still have access to attribution data within their ecosystems but don’t share detailed user-level information with advertisers. This forces marketers to rely on platform-reported data, which often conflicts with other measurement systems and makes cross-platform optimization nearly impossible.

As a result, traditional attribution methods are becoming increasingly unreliable. Marketers need to explore new approaches that don’t depend on user-level tracking but still provide actionable insights for campaign planning and budget allocation.

Solutions for Ad Attribution Problems

Addressing ad attribution challenges effectively can pave the way for smarter budget decisions and better campaign performance. Below are strategies to tackle these issues head-on, offering insights that can refine your marketing efforts.

Extend Attribution Windows

Extending attribution windows lets you capture delayed conversions, especially for products or services with longer sales cycles. This approach helps ensure that paid-media conversions aren’t mistakenly labeled as organic, giving every touchpoint the credit it deserves. By doing so, you can more accurately measure metrics like Return on Ad Spend (ROAS), Cost Per Install (CPI), and Customer Lifetime Value (LTV), providing a clearer picture of your campaign's true impact[1][2][3].

Use View-Through Attribution for CTV

Since Connected TV (CTV) ads are non-clickable, traditional click-based models fall short in measuring their effectiveness. Enter view-through attribution: this method credits conversions to users who saw a CTV ad within a specific timeframe, even if they converted later through another channel. For example, someone might see a CTV ad and later purchase via your website or app. Pairing this model with cross-channel retargeting strengthens its effectiveness by creating measurable touchpoints after the initial exposure.

Use Multi-Touch Attribution Models

Last-click attribution often oversimplifies the customer journey, ignoring the influence of earlier interactions. Multi-touch attribution solves this by distributing credit across multiple touchpoints. For instance:

• Linear models: Assign equal credit to every interaction.

• Time decay models: Give more weight to touchpoints closer to the conversion.

• Position-based models: Emphasize the first and last interactions.

The right model depends on your business goals and how your customers engage with your brand.

Set Up Cross-Channel Retargeting

Connect the dots between upper-funnel awareness and lower-funnel conversions by leveraging audience segmentation for retargeting. For example, you can create audience segments of users exposed to your CTV ads - many programmatic platforms allow this based on ad impressions alone. These segments can then be retargeted on channels like social media and display ads, creating a clear and trackable path from initial exposure to final conversion.

Test for Incremental Results

Attribution models alone can’t always confirm whether your campaigns are driving new sales or simply capturing customers who would have converted anyway. That’s where additional testing comes in. For example:

• Geo-lift studies: Compare performance in markets exposed to your campaign against control markets to measure incremental lift.

• Marketing Mix Modeling (MMM): Use statistical analysis to account for factors like seasonality and competition, helping you determine whether your ads are delivering results beyond what traditional attribution methods reveal.

These tests provide a clearer understanding of your campaigns' true impact, ensuring your advertising dollars are well spent.

Choosing the Right Attribution Model

Once you've tackled common attribution challenges and their solutions, the next step is selecting the attribution model that aligns with your goals and campaign structure. The right model refines your insights and ensures your measurements truly reflect your marketing efforts. Each model credits touchpoints differently, so understanding their strengths and limitations is crucial for making informed decisions.

Attribution Model Comparison

Using the wrong attribution model can lead to skewed performance insights and misallocated budgets. Here's a breakdown of the main attribution models to help you decide:

The choice boils down to your campaign objectives. For instance, if you're focused on brand awareness, a first-click model can reveal which channels are introducing new customers. On the other hand, campaigns aimed at driving conversions might benefit from a last-click approach. However, for many modern marketing strategies, more nuanced models - like position-based or data-driven - can offer better insights.

Why Data-Driven Attribution Works Best

Data-driven attribution takes measurement to the next level by using machine learning to analyze actual customer behavior. Instead of following rigid rules, it examines multiple conversion paths to determine which touchpoints truly influence decisions. This approach provides a more accurate picture of your marketing impact.

One of its biggest advantages is flexibility. Unlike rule-based models, data-driven attribution adjusts credit dynamically. For example, it might identify social media ads as key drivers for first-time buyers but less impactful for returning customers, tailoring the credit accordingly.

This model also uncovers valuable patterns, such as seasonal trends, cross-device interactions, and the most effective channel combinations. As customer journeys grow more complex - spanning multiple devices and platforms - this level of sophistication becomes increasingly important.

That said, data-driven attribution isn't without its challenges. It requires a substantial amount of conversion data to function effectively. Smaller businesses or niche markets may struggle to generate enough data for meaningful analysis, making simpler models a better fit in those cases.

While last-click attribution offers simplicity, data-driven models demand deeper analysis and specialized tools. Yet, companies with sufficient data often see improved campaign performance after adopting this approach. Its ability to adapt to changing customer behavior and market conditions makes it a powerful tool for long-term success and smarter budget decisions.

How OTHERSIDE Solves Attribution Problems

Understanding attribution models is one thing, but successfully implementing them requires the right partner. OTHERSIDE's programmatic advertising platform tackles key attribution challenges with integrated technology, clear reporting, and fast deployment.

Cross-Channel Campaign Management

One of the toughest challenges in attribution is tracking customers across multiple devices and touchpoints. OTHERSIDE solves this by bringing Connected TV, display, native, and mobile app advertising into a single system. This unified approach allows for cross-channel retargeting and shared data insights across all touchpoints [4].

Forget the frustration of fragmented platforms. With OTHERSIDE, you can track a customer’s journey seamlessly. For example, if someone watches your Connected TV ad but doesn’t convert right away, the platform can retarget them with display ads on their mobile device. It then tracks their entire journey - from first impression to purchase.

OTHERSIDE’s platform identifies when the same person interacts with your brand across different channels and devices, ensuring precise attribution data. No more inflated reach numbers or missed conversions.

To make this even more effective, the platform leverages over 400 premium data partners to refine audience targeting and enhance your first-party data. This means smarter lookalikes, better retargeting, and more precise segmentation [4]. With this level of data integration, you get a clearer understanding of your audience and their behavior, leading to more accurate campaign insights.

Clear Reporting and Performance Tracking

Transparency is key, and OTHERSIDE delivers it with pixel-based tracking that monitors every touchpoint, providing full-funnel attribution and daily performance updates [4].

The Nexus Engine™ optimizes campaigns in real time, reallocating spend to the best-performing placements to maximize ROAS [4]. This real-time optimization ensures your attribution data reflects current campaign performance, not outdated metrics from days-old results.

Speed matters too. The Nexus Engine™ reduces the typical 4–6 month ramp-up period to just 4–6 weeks, using real-time cross-channel optimization [4]. This accelerated timeline gives you actionable attribution insights much faster than traditional methods.

The results speak volumes. A recent MMM study with one of OTHERSIDE’s clients showed a 2.2x return on investment from top-of-funnel programmatic spend, verified by an independent third party [4]. This kind of third-party validation ensures you’re seeing the true impact of your campaigns.

Fast Campaign Launch

Speed is crucial when testing attribution strategies, and OTHERSIDE doesn’t disappoint. Campaigns can be launched within 7 days [4], allowing for quick testing and iteration of different attribution windows, channel mixes, and targeting strategies.

The platform provides fully managed programmatic advertising services, handling everything from strategy and execution to real-time optimization, custom tracking, and data-driven targeting across multiple channels [4]. This hands-on management eliminates the technical challenges that often hinder proper attribution setup.

Joe Cornfield from Transparent Labs shared his experience:

"OTHERSIDE gave us a one-stop solution to diversifying our media spend. They prepared a diverse, innovative multi-channel strategy for us, and ads went live within 2 weeks of onboarding. We are already exceeding our performance goals" [4].

This quick launch capability is critical for attribution testing. It lets you run experiments across different timeframes and market conditions without long delays. Instead of waiting months to see if your attribution strategy works, you can gather meaningful data in weeks and make informed adjustments.

Conclusion

Attribution challenges can seriously impact your marketing results. When measurement systems fail to capture the complete customer journey, it often leads to wasted ad spend and missed opportunities.

By extending attribution windows, using view-through attribution for CTV, and adopting multi-touch models, marketers can gain a clearer understanding of what drives conversions. These strategies also help validate incremental growth through cross-channel retargeting and geo-lift or MMM studies.

Among the various methods, data-driven attribution stands out because it uses actual conversion data to assign credit accurately, avoiding outdated assumptions. This approach is especially relevant in the U.S., where consumers frequently switch devices and take longer to make purchasing decisions. This makes it essential to have the right platform in place to execute these strategies effectively.

That’s where OTHERSIDE's integrated platform comes into play. It removes the technical roadblocks that often hinder proper attribution. By combining cross-channel tracking, rapid campaign launches, and real-time optimization with the Nexus Engine™, this platform transforms strategies into measurable results. With campaigns launching in as little as 7 days, you can start collecting accurate attribution data almost immediately - no long waits required.

Accurate attribution isn’t just about better metrics - it’s about smarter decision-making. When you know which touchpoints truly drive conversions, you can allocate your marketing budget more effectively and scale what works. For U.S. marketers dealing with increasingly complex customer journeys, precise attribution is the foundation for sustainable growth and better ROI.