Facebook Attribution vs. Google Attribution: Which is Better for Your Business?

In today’s digital landscape, attribution is critical for marketers aiming to optimize their advertising campaigns. With platforms like Facebook and Google leading the online ad space, understanding the differences between their attribution models is key to determining which is more effective for your business.

This article explores the differences between Facebook Attribution and Google Attribution, focusing on their default settings, time frames, device tracking capabilities, and how they impact marketing performance.

What Is Marketing Attribution?

Marketing attribution refers to the process of identifying which touchpoints in a customer’s journey contribute to a final conversion (e.g., a purchase or lead generation). By analyzing these touchpoints, marketers can understand the effectiveness of different channels—whether it’s social media, email marketing, or direct ads—and make informed decisions to improve Return on Ad Spend (ROAS).

Attribution models provide clarity on how to assign credit for conversions and allow businesses to focus resources on the most effective channels.

Key Differences Between Facebook Attribution and Google Attribution

1. Default Attribution Model

Facebook and Google differ significantly in their default attribution models:

• Google Attribution: By default, Google uses the Last Non-Direct Click model. This means that 100% of the conversion credit goes to the last channel the user clicked on—excluding direct traffic.
• Facebook Attribution: Facebook uses a last interaction model that focuses on the user who interacted with the ad, regardless of whether they clicked on it. This model includes view-through conversions, meaning that anyone who saw the ad, but didn’t necessarily click, is still counted as part of the conversion path.

This fundamental difference in approach often leads to discrepancies between what advertisers see in Google Analytics versus Facebook Ads Manager. For instance, a sale might appear to be attributed to direct traffic in Google Analytics, while Facebook could attribute it to an ad view within its platform.

2. Attribution Time Frame

Facebook recently changed its attribution window from 28 days to 7 days for both click-through and view-through conversions. Google’s attribution window, on the other hand, is customizable and defaults to 30 days.

This difference in time frames can lead to variances in reporting. For instance, Facebook’s 7-day attribution model counts conversions from users who viewed or clicked on an ad within the last 7 days. In contrast,?Google Analytics only counts conversions based on the last click within the designated window, typically 30 days.

Impact on Performance Metrics: Marketers who heavily rely on impressions (ad views without clicks) will see a significant difference in performance metrics between Facebook and Google. Google Analytics won’t account for view-through conversions, while Facebook includes them, often resulting in higher conversion numbers.

3. Cross-Device Tracking

One of Facebook’s standout features is its ability to track users across multiple devices. Facebook Attribution links user activities across different devices as long as the user is logged into Facebook. This gives advertisers a more comprehensive understanding of how users interact with ads on desktop, mobile, and tablet devices.

Google Attribution, however, relies on cookies to track user interactions. Since cookies are browser-specific, Google Analytics often struggles to track users across multiple devices. For instance, if a user engages with an ad on their mobile phone and later makes a purchase on their desktop, Google Analytics may not attribute the sale to the mobile ad.

Cross-device tracking makes Facebook a more powerful tool for understanding multi-platform user behavior, especially as more consumers switch between devices before making a purchase.

4. View-Through Conversions

Another key distinction is how the two platforms handle view-through conversions:

• Facebook Attribution: Includes conversions from users who only viewed an ad but didn’t click it. This means that even if a user saw your ad and made a purchase days later through a different medium (e.g., organic search), Facebook will count the conversion as part of the ad’s success.
• Google Attribution: This does not track view-through conversions unless specific models or settings are applied. Google primarily focuses on click-based actions. As a result, campaigns that rely heavily on impressions may not show full impact in Google Analytics.

Types of Attribution Models

Both Facebook and Google offer various attribution models that allow businesses to understand different aspects of customer behavior. These models distribute credit across the customer journey in various ways:

1. Last Click Attribution

Google Analytics traditionally defaults to Last Click Attribution, which gives 100% credit to the last click before the conversion. This model often fails to account for earlier interactions that might have influenced the customer’s decision.

Facebook also supports last-click attribution but places higher importance on view-through conversions, which means the model is more holistic on the platform.

2. Linear Attribution

This model assigns equal credit to each touchpoint along the customer journey. It helps marketers understand the full scope of interactions leading up to a conversion.

Facebook and Google both offer linear attribution, but keep in mind that Google Analytics may still underreport if touchpoints occur on different devices.

3. Time Decay Attribution

The time decay model assigns more credit to touchpoints that are closer to the conversion event. This is particularly useful for businesses with long sales cycles, where early touchpoints might play a smaller role than interactions closer to the purchase.

4. Data-Driven Attribution

One of the most advanced models, data-driven attribution uses machine learning to assign credit based on the actual impact of each touchpoint. It relies on historical data from your campaigns to evaluate what contributed most to conversions.

Both Google and Facebook offer data-driven attribution, but their methodologies differ. Google’s machine learning algorithms are based on user interaction within Google’s ecosystem (e.g., Google Ads, Search, Display Network), while Facebook’s data-driven models focus primarily on engagement within Facebook’s platform.

Cross-Channel Advertising Optimization Software

As businesses increasingly adopt cross-platform advertising strategies, it becomes essential to streamline the process of managing campaigns on both Facebook and Google. Cross-channel advertising optimization software bridges the gap between these two giants, allowing for the simple implementation and management of ads across multiple platforms.

This type of software creates a data bridge between Facebook Ads and the Google Marketing Platform, enabling real-time optimization across both channels. With integrated tracking, advertisers can use the unique strengths of each platform—such as Facebook's cross-device tracking and Google's click-based attribution—to achieve the best possible performance.

By leveraging cross-channel advertising software, businesses can easily manage their campaigns, improve ad performance, and make their conversions seamless across the two most powerful ad platforms. We make cross-platform advertising easy and efficient, ensuring that your marketing efforts across Facebook and Google work in harmony to maximize your conversions.

Think of the power of Facebook and Google attribution models working together! With the right optimization software, you can achieve consistent results and higher ROI without the complexities of managing each platform individually.

The Verdict

All marketers need to understand attribution models and the differences between Facebook vs. Google analytics data. Marketers need this knowledge to successfully attribute creativity, set audience targeting, and ultimately drive conversions.

The platforms both collect attribution data differently, but that doesn’t make either method wrong or right. I recommend trying both Facebook and Google attribution models to determine which works best for your business.