Why Different Tracking Systems Don't Always Match Up and How to Account for Attribution Errors

If you’re currently running a business, chances are that your marketing is on multiple digital channels. And smart marketers (and business leaders) want to know where their efforts are having the most impact on leads, sales or general engagement.

According to Content Marketing Institute, marketers use an average of 13 tactics—7 different social media platforms, and 3 paid advertising channels within their efforts. With so many places from which to attribute your desired outcome, it’s crucial you limit attribution errors.

*What it feels like to have no attribution model in place.*

Unfortunately, the more channels you’re on, the more complicated it can become.

Why does Facebook claim 50 sales when Google Analytics says it only drove 40?
How come my Google Ads leads and Facebook leads combine for more than my total?
Which of my campaigns actually drove the final sign up for my app?

I’ll break it down step by step, and give you the tools to best account for different attribution systems and ensure accurate data from any future campaigns.

The Basics

What is attribution? In regards to marketing, attribution is the value assigned to a marketing activity based on the desired outcome.

Often, when running ads, there can be some confusion as to which platform the sale came from. With multiple traffic sources and default attribution methods from each individual platform, it can become very overwhelming.

In today’s digital space, it’s pretty safe to say that no single event caused a conversion. Instead, we often see multiple touchpoints within the buyer’s journey. More often than not, each platform enhances the user-experience and assists the conversion in some way.

It’s important to understand each platform’s default reporting style, as they do tend to differ depending on what marketing efforts you’re utilizing. Instead of using each system as a separate entity, using them in combination will help to achieve the most complete (and accurate) picture.

Facebook Ads vs. Google Ads

At the most basic level, tracking within Facebook is pixel-based (or people-based), whereas Google is session-based (or cookie-based 🍪).

*Sadly, there are no chocolate-chip cookies involved.*

To ensure each of these systems is actually tracking, the Google Analytics code tracks users who have Javascript, images and cookies enabled. Whereas Facebook relies on the user being signed in either to their Facebook or Instagram profile on a given device.

Since these systems track differently by default, we start to see tracking information that doesn't quite match up.

Facebook Attribution

The two main types of Facebook attribution windows are views and clicks.

When a user clicks on the ad and takes an action, this is called click-through attribution. However, if the user sees the ad (tracked as an impression in Facebook), didn't click, but took an action within the set attribution window, this is instead called a view-through attribution.

Facebook, by default, uses a last-touch attribution model. As long as a Facebook ad was clicked or interacted with by that user, Facebook will take the credit. This is why without additional tracking systems set up, Facebook tends to attribute for conversions in some cases where another analytics platform may not have given Facebook the credit.

Google Analytics

By default, Google Analytics attributes a conversion to the last traffic source that the user came from before making the conversion—the last-click (or last interaction) model.

Other attribution models within Analytics include:

Last Non-Direct Click model - Used for non-Multi-Channel Funnels reports.
Last Google Ads Click model - Used to identify and credit the Google Ads ads that closed the most conversions.
First Interaction model - Used when running ads or campaigns to create initial awareness.

Linear model - Used when campaign goal is to maintain contact and awareness with the customer throughout the entire sales cycle.
Time Decay model - Used when running short promotions and you want to give more credit to interactions during that period of time.
Position Based model - Used for determining touchpoints that introduced customers to your brand and final touchpoints that resulted in sales.

Native Website Tracking - Shopify

In addition to Facebook and Google default tracking, you also must consider how your website tracks conversions, as well. (For our example, we’ll stick to Shopify.)

In a similar tracking style to Analytics, most third-party reporting platforms use cookie-based measurement. Because of this, Shopify isn’t able to accurately measure cross-device conversions like Facebook does.

With the last-click attribution style, Shopify tends to mislabel conversions from paid traffic (specifically Facebook) as “direct”.

Tools for Tracking

With all these different systems and tracking styles, what are some ways to account for attribution errors and ensure accurate data?

UTM Parameters

Facebook

One of the best ways to ensure accurate data across multiple accounts it to implement Urchin Tracking Module (UTM) parameters within your Facebook campaigns. Once clicked, this URL sends data back to Google Analytics and other systems, like Shopify, allowing your ad campaign efforts to be more accurately tracked.

A good starting place for tags within Facebook Ad campaigns is: utm_source=facebook&utm_medium=cpc&utm_campaign=campaign_name

* Pro tip: If you’re looking for a quick UTM tag for any current and future Facebook campaigns, you can get away with just including the above 3 parameters. Be careful though, just having utm_campaign within the UTM parameters without utm_source will result in no tracking within Analytics.

Google Ads

When building campaigns Google gives you two options, auto-tagging, and manual tagging. Google recommends enabling auto-tagging to “get the most detailed Google Ads data.” Auto-tagging also saves you time, as manual tagging can be much more time-consuming and prone to more errors.

Although manual tagging takes more time and only allows a specific amount of data, there are special cases in which manual tagging might be better a fit.

If your website doesn’t allow arbitrary URL parameters
If you need to use UTM tagging for non-Google Analytics purposes

Disabling auto-tagging will allow you to add parameters to URLs to identify the campaigns that refer traffic. Custom campaigns will require parameters similar to Facebook.

* Pro tip: Separate the parameters from the URL with a question mark. List the parameters and values as pairs separated by an equal sign. Separate each parameter-value pair with an ampersand. https://www.example.com/?utm_source=google&utm_medium=cpc&utm_campaign=campaign_name

Attribution Windows

When consulting multiple platforms, check that your conversion attribution windows match. By default, the Facebook conversion reports are set to a 1-day after view or 28-day click window.

The attribution windows within Facebook are 1-day, 7-day, and 28-day view and click attribution. To ensure accurate analysis of data, make sure your Analytics windows are set to the corresponding time frame as well.

Attribution can get tricky for novice and experienced marketers alike, especially while measuring results from efforts across multiple platforms. With a better understanding of attribution and by taking the necessary steps to implement tagging options within your campaigns, it becomes easier to see which channels are most profitable for you.

Content originally published on EmberTribe.com