Making Sense of Digital Media Attribution

Why does Facebook say that your campaign raised $2,000, but your donation platform or customer relationship management (CRM) system only shows $1,000 associated with that specific appeal code?

It's a question executive directors, board members, and auditors ask constantly. The short answer: Both numbers are right. That's the attribution problem.

What Is Attribution?

Digital media attribution is the process of identifying which marketing touch points deserve credit for a conversion — whether that's a donation, email sign-up, or event registration. It’s the digital breadcrumbs that lead someone from first awareness to action.

Think about your own behavior online. You read an email and then Google more information, you see an Instagram ad and then seek out that organization on YouTube, or you see a Bing ad that directs to the website. Donors don’t act in a linear fashion either. This is why attribution is messy. 

Attribution matters because it drives budgets. Resources aren't unlimited, and today’s marketing should not operate on a feeling but instead on data. This is how programs, auditors, and businesses make decisions. Marketing and fundraising should be no different.

The Attribution Models That Matter

No single model is best. Each one illuminates a different part of the donor journey — here's what they each show, and where they fall short.

Last-Click Attribution

Last-click attribution is the simplest model — and gives 100% of the credit to the final touch point before conversion. It’s easy to understand, making it a common starting point for conversations. 

The problem: Donors are influenced by multiple channels and require multiple impressions on each. Last-click favors channels that make it easiest to convert, not the channels that convince people to convert. Search ads often dominate here because people who click search ads have already shown intent — they’re looking to convert, so the ad streamlines conversion, but doesn’t necessarily drive the decision.

First-Click Attribution

On the other hand, first-click attribution gives all credit to the initial touch point that introduced someone to your organization. It shows which channels expand your audience and grow your conversion funnel.

The limitation is that it ignores what drives people from awareness to action. Instead, it favors passive channels with broad reach, showing where your audiences are, but not what drives them to convert. Meta, TikTok, and other social channels often perform well here because these platforms are made for discovery — introducing audiences to things that they will like.

Linear Attribution

Linear attribution distributes credit equally across all touch points in the donor journey. If someone interacted with five different campaigns before donating, each gets 20% of the credit. At least it acknowledges that the donor journey is rarely linear and credits each channel equally.

In practice, though, linear attribution can be hard to measure and report on due to data privacy restrictions, pixel limitations, and overall user preferences. It requires data from multiple platforms to be synced, so it’s less actionable within a single platform and often is spotty at best. Passive channels — video, display — tend to appear more valuable through this lens. 

Time-Decay Attribution

Time-decay attribution gives more credit to touch points closer to the conversion, with the most recent interactions receiving the most weight. It recognizes that early touch points matter, but are less important than the interactions immediately before conversion.

Like linear, time-decay can be hard to measure across platforms, and weighting assumptions can be hard to standardize. Still it’s particularly useful for understanding which campaigns move people from consideration to action. For nonprofits running true multichannel campaigns, this approach is more robust than linear, with owned channels and intent-driven channels like search performing best because they will be given a higher value than more upper-funnel platforms. 

Data-Driven Attribution

Data-driven attribution, or algorithmic attribution, uses machine learning to analyze your actual conversion data and assign credit based on the statistical impact of each touch point. Rather than relying on predetermined rules, it learns from your specific audience behavior. Research from Google indicates that organizations using data-driven attribution see an average of 6% more conversions at the same cost.

The tradeoff is transparency. Data-driven attribution is the hardest to explain because the algorithms make most of the decisions, which makes conversations about what is and is not working challenging. You have to trust the output, and the model needs significant conversion volume to be reliable.

For nonprofits with enough conversions and data, it provides the most accurate attribution, but for smaller nonprofits, bottom-of-funnel, intent-based channels like search will have the most value, causing potential inconsistencies across campaigns, nonprofits, and spends. 

How Platform Attribution Works — And Why It Adds to the Confusion

Ad platforms report their own attribution data, which often tells a different story than other attribution models. Often called “platform attribution," or “campaign-attributed conversions,” it relies on data from a pixel — a small tracking code — that has gotten less accurate as more private browsing and JavaScript blockers have been used. 

Platform attribution captures both active (someone clicked on an ad) and passive (someone saw an ad) conversions: click-through (someone clicked your ad and converted within a set window — I typically set this to seven days) and view-through (someone saw your ad but didn't click, yet later converted — I typically set this to one day). 

Platform attribution is important because platforms need to know who to target, especially for acquisition campaigns, so these conversions are more directional and show that you are reaching a qualified audience. If someone sees a display ad (view-through) and then Googles and clicks a search ad (click-through), both ads will claim credit for the conversion.

Attribution Is Imperfect — and Getting Harder

Attribution isn’t getting harder because there is less reliable data, it’s getting more difficult because everyone wants a black-and-white answer, and donors simply don’t engage with digital media that way. 

The digital landscape is fragmented. Donors interact with organizations across multiple devices, browsers, and platforms. Privacy regulations like General Data Protection Regulation (GDPR) and iOS tracking changes have made cross-platform tracking increasingly difficult. The average nonprofit now uses multiple channels to reach donors, making the donor journey more complex than ever.

This is where understanding the difference between correlation and causation becomes critical. Just because two things happen together doesn't mean one caused the other. Someone might see your Instagram post and donate the next day — but perhaps they were already planning to give because of your email campaign last week.

No single attribution model tells the complete story. The most sophisticated nonprofit marketers use multiple models to triangulate truth — and larger organizations are now using Media Mix Modeling to get a more complete picture beyond what attribution alone can provide. 

Attribution is a tool for better decision-making, not an exact science. Let it inform your strategy without getting paralyzed by imperfection. Focus on continuous improvement, and you’ll make smarter decisions that ultimately drive more resources toward your mission. 

The preceding content was provided by a contributor unaffiliated with NonProfit PRO. The views expressed within may not directly reflect the thoughts or opinions of the staff of NonProfit PRO.