AdWords Attribution for Paid Search - Which AdWords Attribution is Right for You?

Google has been speaking extensively about AdWords attribution all year. But which AdWords attribution model is right for your business...and is choosing the right model the most important piece of the puzzle? 

AdWords Attribution for Paid Search - Which AdWords Attribution is Right for You?

AdWords attribution may not necessarily be a big part of your day-to-day duties as a paid search professional. You’re probably a lot more focused on driving as much traffic and revenue, and as many clicks and conversions as possible. But attribution is becoming an increasingly important topic as customer journeys change and more and more business goes from online-to-offline (o2o), involving not simply website visits via paid search clicks, but also social, mobile and call-based interactions. We’ve previously touched on AdWords attribution at SMX West 2017, but we’ll be taking a deeper dive this time around.

The Six  Different Types of AdWords Attribution

This article will go a bit further than Google’s own AdWords attribution model explanations to go over the six different types of AdWords default attribution models that might appear in an AdWords attribution report near you.

These AdWords attribution models differ primarily based on how much weight they apply to different parts of your sales funnel - whether that be the very first clicks in a campaign, down-funnel clicks that get closer to conversion, or the very last click in the entire journey. 

Google clearly has a favorite AdWords attribution model (which we’ll get to in a bit), but in many cases, the publisher otherwise recommends using some of the other five models as comparison points against each other, rather than using each as a single, standalone source of truth.

1. Last-click AdWords attribution

First, we’ll discuss what many deep-funnel performance marketers consider to be the most important AdWords attribution model: last click. This attribution model attributes all credit for clicks to the final click before sale. Last click strongly emphasizes deep-funnel clicks, tying the final click to revenue, and therefore tends to have already seen considerable usage among deep-funnel marketers (including paid search professionals like yourself).

It should be noted, however, that last-click attribution may significantly overvalue branded keywords and the effects of remarketing campaigns. Google recommends using this model as a comparative metric against other attribution models to gauge the effectiveness of certain keywords at different stages in your customers’ journey.

Pros, Cons and Use cases

  • Pros: Full focus on final conversion before sale - a good fit for performance marketing.
  • Cons: De-emphasizes upper-funnel activity.
  • Use case: For a sales funnel in which conversions are highly emphasized.

2. First-click AdWords attribution

First-click attribution is an extremely aggressive AdWords attribution model that effectively attributes all clicks leading to a conversion to the first click. It might be useful for advertisers simply running brand campaigns to raise awareness, or possibly for extremely advanced testing purposes for mature campaigns (such as comparing top-performing first-click keywords against top-performing last-click keywords). However, AdWords attribution model ignores anything in the funnel below the very top, and its inherent bias toward highly competitive keywords significantly limits its usefulness overall.

Pros, Cons and Use cases

  • Pros: Useful only for absolute top-funnel click attribution.
  • Cons: Misses everything after the initial touchpoint.
  • Use case: Possibly for branding campaigns or extremely limited tests. 

3. Linear AdWords attribution

Linear attribution assigns equal credit to every touchpoint in your funnel. This AdWords attribution model seems a bit more balanced or “fair” than the previous AdWords attribution models at a glance, but clearly misses the nuances of certain touchpoints being over- or undervalued.It does approximate a full-funnel customer journey, and might make for a good start for paid search beginners, or for a very, very early stage of testing in which all funnel stages are considered controls to test against.

However, linear's inability to distinguish stronger touchpoints from weaker ones limits its usefulness overall. Google recommends using it for initial testing to compare against first-click and last-click data to see which interactions are most effective in moving customers down through your funnel.

Pros, Cons and Use cases

  • Pros: A relatively easy-to-understand introduction to factorial attribution
  • Cons: Unable to recognize outsize influence of any individual funnel stage
  • Use case: Possibly for branding campaigns or extremely limited tests. 

4. Position-based / U-Shaped AdWords attribution

The position-based AdWords attribution model assigns 40% of the “credit” to top-funnel and bottom-funnel touchpoints respectively and assigns the remaining “credit” evenly to the middle of the funnel. It assumes key bottom-funnel and top-funnel interactions to be the most significant, but largely ignores mid-funnel interactions.

It could, for instance, be useful in sales cycles for which initial touches and closing sales are the two most important touchpoints, and are comparable in significance. One such example might be commercial real estate - a field in which striking up an initial relationship with a realtor (creating an extremely high-value lead) is almost comparable to the importance of closing a sale on a six-figure or seven-figure property.

Pros, Cons and Use cases

  • Pros: Emphasizes top-funnel and bottom-funnel equally.
  • Cons: Largely ignores mid-funnel interactions.
  • Use case: Specialized businesses that prize top-funnel and bottom-funnel touchpoints equally.

5. Time decay AdWords attribution

The time decay AdWords attribution model, as the name implies, assigns more weight to more-recent touchpoints, while eroding the relevance of top-funnel touches that took place in the past, potentially revealing which touchpoints may be more influential in closing sales more quickly and which tend to precede longer sales cycles.

Because it emphasizes bottom-funnel touches, time decay may disproportionately “credit” brand and remarketing campaigns, but it’s a potentially useful model to consider using for B2B audiences with long sales cycles, where deal acceleration and a handful of lucrative closed-won deals may be more important to your business than scattered top-funnel leads.

Pros, Cons and Use cases

  • Pros: Strongly emphasizes bottom-funnel and conversions.
  • Cons: Largely ignores upper-funnel interactions.
  • Use case: Big-ticket B2B products and services, as well as potentially comparing which top-funnel touchpoints tend to drive shorter sales cycles.

6. Data-driven attribution (DDA)

The AdWords attribution model pushed most by Google, DDA has been accompanied by numerous case studies from the publisher explaining its efficacy. This attribution model is only for high-volume advertisers who have recorded a minimum of 15,000 clicks and 600 conversions within the past 30 days (and you must subsequently maintain a minimum of 10,000 clicks and 400 conversions going forward).

Google claims that its machine learning algorithms power DDA, making it significantly more accurate. However, this attribution model, in addition to its potentially high volume threshold, remains something of a black box with no transparency into exactly how its algorithms work. 

Pros, Cons and Use cases

  • Pros: Provides the most accurate type of attribution, according to Google.
  • Cons: Requires significantly high volume to qualify.
  • Cons: Algorithms are still a poorly-understood black box to be taken on faith
  • Use case: Advertisers with sufficient volume

What Happens After AdWords Attribution?

Clearly, it’s important to figure out what type of AdWords attribution might work best for you - for instance, whether a specific funnel stage might be more or less significant for you. But beyond choosing a specific attribution model, advertisers should ideally be able to harness the insights from every piece of data in their funnel. 

For those that are ready to take the next step, there are predictive advertising platforms that can provide deep, click-level analysis to capture every aspect of a single click’s data, from demographics to time-of-day to device to location, and convert this data into actionable insights that help you grow your business.

About the Author

Andrew Park

Andrew Park is a content marketing manager at QuanticMind. A UC Berkeley graduate and lifelong Bay Area resident, Andrew has done tours of duty in editorial, PR and marketing, and now works with the QuanticMind team to communicate the importance of data science and machine learning in digital advertising.

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