Marketing Attribution in Shopify

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Marketing Attribution in Shopify

Marketing attribution has been around for a long time. The goal is to answer the question, “what journey did a customer take to buy from me?”

While this is likely simple for a business running some basic channels, it gets considerably harder to answer once you factor in lots of channels, especially since we live in the so-called “omnichannel” marketing world. Even a small business might market across several channels; without marketing attribution, it can be extremely difficult to tell where customers come from.

If you can find out where your customers come from, you can tune and optimize your channels accordingly. Such is the goal of marketing attribution. 

What is Marketing Attribution?

In short, marketing attribution involves analyzing various marketing touchpoints on the customer’s journey to purchasing or converting.

Attribution works out what channels had the most impact on a customer’s decision to convert.

For example, the customer might arrive from a social media ad, an organic post, or an email newsletter.

Understanding what touchpoints pull in the most conversions and how they interact to form a customer journey enables precision marketing. By analyzing marketing attribution, channel spend can be focussed on where it has the most impact. 

Marketing Attribution for Shopify

It’s possible to attribute marketing for Shopify shops in the same way as for any other website.

The Shopify website is the endpoint that you’re driving traffic to and converting from. Of course, it’s possible to convert from multiple endpoints (e.g., an eCommerce store might have an app), in which you’ll need to analyze multiple customer journeys.

Shopify marketing reports are semi-automated and track clickable actions across paid and unpaid channels. In addition, reports remove duplicate conversions automatically. However, you only have two options for how you allocate attribution weight and can only allocate it to the first or last touchpoint.

This can be problematic, as some customer journeys take place over several touchpoints, which combine to funnel the customer toward a sale. Some channels might be excellent at capturing initial interest, others for converting. If you only ever focus on the first or final touchpoint, you risk ignoring others. 

Combining Google Analytics with Shopify is best for measuring attribution and many other useful metrics.  To connect Google Analytics to Shopify, Shopify has a guide here. It’s simple and takes just minutes. 

Setting Up Attribution

Marketing attribution primarily revolves around UTM (Urchin Tracking Module) parameters.

These are URL strings found after URLs and contain data about the link’s position and purpose.

They look something like: 

www.yourshopifystore.com?utm_source=facebook&utm_medium=cpc

UTMs are a standardized tagging system purchased by Google and can be created in Google's Campaign URL Builder. There's no need for UTM parameters for Google Ads, as you can use auto-tagging instead.

Ad blockers, GDPR, and other national and international privacy initiatives are making user-tracking methods like UTM parameters less tractable, and marketing mix modeling (MMM) is probably the most future-proof method for measuring marketing ROI.

Once you’ve tagged URLs, you can set up an Attribution Project in Google Analytics.

Marketing Attribution Models

When UTM parameters collect tracking data, they parse it to a cookie which Google Analytics ingests. The cookie will contain data about their journey, e.g. they clicked on one link, then an ad, and then finally landed on a website to convert.

The problem is, while you can tell what touchpoints the customer clicked on to convert, it’s difficult to tell which touchpoint(s) is the most important. That’s where marketing attribution models come in.

There are six different types of marketing attribution models available in Google Analytics:

  1. Last click
  2. First click
  3. Linear
  4. Time decay
  5. Position-based
  6. Algorithmic (Custom)

1. Last click attribution 

Last-click attribution is probably the most common. It attributes 100% of conversion credit to the last click. Clicks down the funnel (e.g., a retargeting ad), are likely to receive more credit here, whereas top-of-the-funnel activity such as blog posts might receive none. 

2. First click attribution

This is the opposite of first-click attribution and credits 100% of the conversion to the first click.

In this situation, you’re giving the most credit to interactions that bring customers into the funnel and are useful for analyzing attribution when you’re spending more on building more traffic.

For example, you’ll see whether investing in your first clicks provides additional conversions and how traffic converts through the funnel. 

3. Linear attribution

Linear attribution involves all touchpoints and credits each equally. It doesn’t miss any touchpoints but doesn’t help analyze or prioritize those that had the most impact. 

4. Time decay attribution 

In essence, this is similar to the last click but gives some credit to preceding clicks. More weight is applied to clicks closer to the conversion. 

5. Position-based attribution

Also called U-shaped attribution, provides 40% of the credit to the first and last click while the remaining 20% is spread out across clicks. This assumes that the first and last clicks are the most important. 

6. Algorithmic attribution

Once you’ve collected sufficient data, you can let Google Analytics model the customer journey for you and assign weight to what it deems are the most important touch points.

Interpreting Attribution Models

You can view which journey produces the highest conversion rates by comparing attribution models. This provides valuable marketing intel that helps marketers decide how to optimize spending.

Use the Model Comparison Tool to compare the impact of different attribution models - the calculated Conversion Value (and the number of conversions) for each of your marketing channels will change depending on the attribution model used.

Limitations of Marketing Attribution

Firstly, attribution relies on cookies which more internet users are rejecting. In a cookieless world, marketing attribution is suddenly a lot more complex - though not impossible.

Marketers are perhaps best off investing in other forms of marketing analysis, like marketing mix modeling, which maps marketing inputs to sales and conversions outputs.

In contrast to marketing attribution that looks solely at touchpoints, MMM looks at other marketing factors, such as seasonality. Many major global enterprises and high-value startups use MMM already, but it’s an effective strategy for marketing optimization that almost any marketer can take advantage of.