Master Marketing Attribution

Attribution tells the story of your customer’s journey from brand discovery to final sale. As such, the right attribution model is crucial to efficient digital ad spending. Fine-tuning your online attribution methodology unveils where customers find the most value in your marketing materials, unlocks more efficient ad performance, and allows your business to make data-driven decisions when prioritizing different platforms and campaign types.

Of course, not all businesses or platforms agree on which events cause online shoppers to ultimately convert. Read on for some of the most common challenges advertisers experience when sorting through digital attribution, including an overview of various models and why a business might elect to use each of them in different circumstances.

Common Attribution Challenges

Your marketing channels have access to tons of useful information but require attribution models to properly interpret sales data and report how well each channel does its job. This is what marketers refer to as attribution — essentially, giving credit where it’s due.

Every attribution model has its potential blind spots, disguising the reasons one campaign might succeed where another fails. As useful as they are, digital platforms themselves aren’t unbiased in this regard. Major advertising platforms like Google and Facebook (and all the rest) are happy to give themselves maximum credit for your advertising success to incentivize greater spending, complicating matters for marketers searching for the most reliable image of their customers’ experience.

Conflicting data (ie. multiple platforms laying claim to the same sales) often leads to these core marketing challenges for digital advertisers:

-Ad platforms don’t compare notes, operating independently from one another.

-When measuring online activity from digital campaigns, Google Analytics will show last-click sources for conversions but ignore the influence of impressions.

-Most online-to-offline conversion attribution solutions exist within each specific platform, which presents the potential for duplication of credit.

Fortunately, there are expert solutions for each of these problems when working with an advertising partner capable of connecting these platforms, identifying the correct attribution model for each, and assigning proper credit with respect to impressions and other touchpoints.

Common Digital Attribution Models

Which entices more people to see a film on the big screen: the movie trailer or the ticket office? In the digital ad-sphere, every popular attribution model looks to weigh the exact value of that initial customer interaction with a product against the event immediately preceding the point of sale.

As always, the most accurate answer is usually a blend of the two, but we’ll get to that in a moment. First, here are the most common default attribution models to be aware of:

Last-touch

Last-touch has been the default setting for Google Analytics and most other prominent platforms (though GA will soon be a data-driven model). It ties 100% of an online conversion to a customer’s final interaction, regardless of any previous touchpoints the user may have experienced with your brand. Last-touch models are widely used to clarify where a point of sale occurs and how that action might be replicated, but be warned: sticking entirely to last-touch models without an eye toward upper- and mid-funnel efforts can hamstring a campaign.

First-touch

On the other end of the attribution spectrum is first-touch, crediting conversions to ads that spark a chain of events leading to the point of sale. This model is often used by businesses with shorter buying cycles, or for awareness campaigns designed to pull in new audiences. For more expensive products, brand awareness campaigns can find success with the first-touch model on platforms like Instagram or Pinterest where users are in the habit of discovering new products.

Linear

Linear attribution is an attempt to balance each touchpoint between top-of-funnel discovery and final conversion by giving each interaction with a user equal weight. Though linear attribution is a slightly more nuanced approach than either of the models above, it doesn’t highlight where a campaign is most effective (or which touchpoints are relatively unimportant), making it difficult to optimize or glean insights from.

Position-based

The position-based attribution model respects the importance of first and last touches without ignoring the interactions in between. This model gives a percentage of the conversion credit to every interaction, but offers preferential treatment to the two most important touches — the first time a customer found you, and the interaction that prompted a conversion.

Position-based attribution can benefit businesses that tend to see multiple touchpoints between their brand and a new shopper prior to a conversion. It also allows flexibility to test which interactions gain greatest favor with consumers, and can be optimized to your business’ specific strengths.

Time decay

This model minimizes the impact of top-funnel marketing techniques, caring little for brand awareness and placing an emphasis on longer-term relationship building. It can be helpful when dealing with expensive B2B purchases that often require more planning than the average sale.

A Time and a Place for Every Model

A good attribution model tells the story of how a user discovered your brand, followed by each impactful step they took toward becoming a loyal paying customer. Identifying and replicating these steps can only be done when both your model and lookback windows are appropriately dialed in for your specific product, service or industry.

Longer lookback windows might make sense for certain industries and represent useless “fluff” data to others. A car dealership or law firm is likely to be more interested in users who clicked a link to visit their branded site over the previous 90 days than a business centered around products with miniscule sales cycles.

The best way to determine which model best represents your average journey is through experimentation. While a multi-touch, full-funnel approach might aid in capturing the most complete picture of user activity for most ecommerce brands, there are plenty of additional circumstances which may call for alternative attribution models. Knowing your brand, products, and customers better through insightful attribution practices can aid in optimizing any campaign.

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