Google Attribution Models Explained (Part 1)

By George Karapalidis

377053 / Pixabay

Knowing how different marketing channels work together to drive conversions and sales is key for marketers, and the various Google attribution models available can be useful tools for examining your data from one angle or another.

But that array of options often creates more confusion, rather than insights. Which attribution model gives marketers the best picture? That’s the question we’ll tackle in this post, by analysing the pros and cons of the 6 main Google attribution models.

(Look out for part 2 later this week where we’ll show you a model that overcomes all the weakness of these models below.)

What is a Google attribution model?

An attribution model is a set of rules Google Analytics/AdWords uses to map conversions and sales to respective touchpoints in a customer’s journey. People come to your website through different channels:

  • Paid and organic search
  • Referral links
  • Affiliate links
  • Social media networks
  • Emails
  • Direct URLs and custom campaigns you’ve set up.

Attribution modelling shows you which ones bring in the most sales and which ones assist conversions – the marketing actions/channels that contributed to sealing the deal. But being a descriptive analytics tool, GA can only tell you how users interact with your website and other properties before converting.

It prescribes the right actions or predicts how conversions will change if you optimise a certain channel – it’s your job to properly capture and interpret all the available data. Arguably, that’s the hardest part of any marketer’s job. But that’s where data science can help.

There are several Google attribution models you can consider in Google Analytics:

6 Google attribution models

1. The last interaction attribution model

The credit for sale (conversion) is assigned to the last platform or channel that a user came from before converting.

Example: you are hosting a webinar and place a link to your product in the description box. Out of 100 attendants, 10 clicked that link and signed up for your tool. According to the last interaction attribution model, 10 sales will be credited straight to the webinar platform (referral traffic).

Sensing a fallacy here? This model does not account for all the other marketing activities you’ve used to generate the buzz around your webinar – that aggressive email campaign you did; the paid social media promotion and all the blog posts you’ve published to gather a warmed up, relevant audience for your event. The last attribution model does not account for all the other touchpoints a user probably had before converting.

Pros

  • Relatively easy-to-setup. Most analytics tools (except for Google Analytics) use this attribution model as default.
  • Delivers straightforward insights into cost-per-lead metrics.
  • Provides data into what’s driving the bottom of the funnel, one step away from conversion.

Cons

  • Tracks only the last steps in the buyer’s journey.
  • Gives you limited visibility into assisted conversions; diminishes the role of other mediums in your campaign.
  • Can leave you with a strong impression that only a few (or one) of your marketing channels work, while others show zero conversions (even if that’s not the case).

2. The first interaction attribution model

All the credit …read more

Read more here:: B2CMarketingInsider

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