IAB 2025: 78% of Marketers Can’t Attribute ROI

A staggering 78% of marketers struggle with accurate attribution across all channels, according to a recent report by IAB. This isn’t just a number; it’s a glaring indictment of how many businesses are still flying blind, throwing budgets at campaigns without truly understanding their impact. How much revenue are you leaving on the table because you can’t connect the dots?

Only 22% of Marketers Confidently Attribute ROI Across All Channels

This statistic, again from the IAB’s 2025 State of Data and Attribution Report, reveals a profound chasm between aspiration and reality in our industry. Think about that: nearly four out of five marketing professionals cannot definitively say which of their efforts are truly driving revenue. It’s not just a technical problem; it’s a strategic one. If you don’t know what’s working, how can you double down on success? How can you cut waste? This low confidence score tells me that many organizations are still stuck in a cycle of trial and error, rather than informed, data-driven decision-making. We’re past the point where gut feelings cut it. Modern marketing demands precision, and precision starts with knowing where your credit belongs.

I saw this firsthand with a client last year, a mid-sized e-commerce brand selling artisanal chocolates. They were running campaigns across Google Ads, Meta, email, and even some influencer partnerships. Their internal reporting, however, was a mess of last-click data that gave all the credit to the final touchpoint, usually a paid search ad. When we implemented a more sophisticated, custom-weighted attribution model using their Salesforce Marketing Cloud data, we discovered that their email nurturing sequences, which had received almost no credit before, were actually playing a significant role in softening leads before they even searched. They were about to cut their email budget, but this new insight saved it – and ultimately, improved their overall campaign efficiency by 18% in three months. That’s the power of proper attribution.

The Average Customer Journey Involves 6-8 Touchpoints Before Conversion

This insight, consistently supported by research from firms like Nielsen, should be tattooed on the forehead of every marketing manager. The idea that a customer sees one ad, clicks, and buys is a relic of a bygone era. Today’s buyer’s journey is a winding, convoluted path involving multiple devices, channels, and interactions. They might see a display ad on their phone, then a social media post on their desktop, read a blog post, open an email, compare prices, and then, perhaps days later, click a branded search ad to make a purchase. Ignoring these intermediate steps is like crediting only the final sprint in a marathon – it misses the entire race.

This data point is why I vehemently disagree with any marketing team still relying solely on last-click attribution. It’s simplistic, misleading, and frankly, lazy. It overvalues direct-response channels and completely undervalues the crucial role of brand building, content marketing, and early-stage awareness campaigns. Imagine telling your content team that their painstakingly crafted articles and videos contribute nothing to revenue because a Google Ad got the final click. It’s demoralizing and fundamentally incorrect. We need to acknowledge the entire journey, not just the finish line. Otherwise, you’re systematically defunding critical parts of your marketing funnel.

Companies Using Advanced, Multi-Touch Attribution Models See a 15-30% Improvement in Marketing ROI

This is where the rubber meets the road. A recent eMarketer study highlighted this significant ROI uplift, and it’s not surprising. When you accurately understand which touchpoints contribute to a conversion, you can reallocate budget more effectively. You can identify underperforming channels and re-invest in those that are truly driving impact, even if they aren’t the “closer.” This isn’t about guesswork; it’s about surgical precision in your marketing spend.

For example, if your multi-touch model reveals that your early-stage YouTube video campaigns, while not directly converting, are significantly increasing the likelihood of a later conversion via email, you can then justify increasing your YouTube budget. Without this insight, those YouTube campaigns might look like a cost center. This is the difference between throwing darts in the dark and using a laser-guided system. The 15-30% ROI improvement isn’t just a number; it represents millions of dollars for larger organizations and significant growth for smaller ones. It’s the tangible benefit of moving past rudimentary reporting to true strategic insight.

45% of Attribution Failures Stem from Poor Data Quality or Siloed Systems

This statistic, often cited in reports on marketing data challenges, is an editorial aside I feel strongly about: no matter how sophisticated your attribution model, it’s garbage in, garbage out. You can buy the most expensive Mobile Measurement Partner (MMP) or integrate with every API under the sun, but if your underlying data is messy, incomplete, or disconnected, your attribution efforts will fail. This means inconsistent naming conventions, missing UTM parameters, tracking discrepancies between platforms, and customer data fragmented across CRM, email, and advertising systems.

I’ve seen this derail countless projects. We once worked with a regional health clinic, Piedmont Healthcare, looking to understand their patient acquisition channels. They had data in their EHR system, their website analytics (Google Analytics 4), and their patient portal. The problem? Patient IDs didn’t consistently carry across all systems, and their ad tracking wasn’t fully integrated with their appointment booking system. Before we could even talk about attribution models, we had to spend weeks cleaning, normalizing, and stitching together their patient data. It was tedious, unglamorous work, but absolutely essential. Ignoring data quality is like trying to build a skyscraper on a foundation of sand; it will inevitably crumble. Prioritize data hygiene, or your attribution efforts are dead on arrival.

Conventional Wisdom: Last-Click Attribution is “Good Enough” for Small Businesses

Here’s where I disagree with a common, yet damaging, piece of advice. Many consultants and even some platforms suggest that for small businesses with limited resources, sticking to last-click attribution is “good enough.” They argue it’s simpler to implement, easier to understand, and provides a quick-and-dirty view of what’s driving immediate conversions. I call this a false economy. While it might seem simpler on the surface, it leads to fundamentally flawed decision-making that can stifle growth and waste precious budget.

Imagine a small, local bakery in Decatur, Georgia, that runs ads on Meta Business Suite, a local radio spot on 99X Atlanta, and has a strong presence on Yelp. If they only look at last-click, they might conclude that their Yelp page is their only effective channel because that’s often the last touchpoint before someone walks in or calls. But what about the Meta ad that first introduced them to the bakery’s new croissant flavor? Or the radio spot that built brand awareness? Last-click would give zero credit to these crucial early touchpoints, leading the bakery to potentially cut their Meta or radio budget, unaware they were severing the very channels that initiated the customer journey. This isn’t “good enough”; it’s actively harmful. Small businesses, perhaps more than anyone, need to be hyper-efficient with their marketing spend, and that demands a more nuanced understanding of their customer journey. Invest in even a basic linear or time-decay model – the insights gained will far outweigh the perceived complexity.

The journey to sophisticated attribution is not a sprint; it’s a marathon requiring commitment to data quality, technological investment, and a willingness to challenge outdated assumptions. By embracing multi-touch models and prioritizing data integrity, marketing professionals can transform their strategies from educated guesswork into a precision-guided operation, ensuring every dollar spent works harder and smarter for their organization. This is crucial for marketing growth and avoiding common pitfalls.

Dana Carr

Principal Data Strategist MBA, Marketing Analytics (Wharton School); Google Analytics Certified

Dana Carr is a leading Principal Data Strategist at Aurora Marketing Solutions with 15 years of experience specializing in predictive analytics for customer lifetime value. He helps global brands transform raw data into actionable marketing intelligence, driving measurable ROI. Dana previously spearheaded the data science division at Zenith Global, where his team developed a groundbreaking attribution model cited in the 'Journal of Marketing Analytics'. His expertise lies in leveraging machine learning to optimize campaign performance and personalize customer journeys

Credentials 15+ years experience