The Analytics Wars - Rise of Channel Attribution Models

The Analytics Wars - Rise of Channel Attribution Models

Understanding the unique ways in which various marketing campaigns contribute to your bottom line can shed insight into how your campaigns are performing. While there is no single best method for understanding the overall customer buying cycle, moving beyond last-click attribution can help shed insight into better analyzing your overall marketing spend and budget.

By default, Google Analytics utilizes last touch point attribution in determining the traffic sources that lead to a conversion. According to this model you may end up with a consumer buying path that looks like this but only attributes the sale based upon the last click:

Organic Search Listing - > Affiliate Banner -> Paid Search Ad -> Facebook Link

With a last-click model you only see Facebook as the winning traffic (referral) source and you may attribute this sale accordingly. Moving beyond last-click attribution can vastly help improve your ability to understand how the various aspects of your campaigns contribute to the overall return on ad investment. In order to do this you need to utilize a custom setting in your Analytics JavaScript by calling the setCustomVar method, which can track a visitor (as long as he or she has an active cookie) across multiple sessions and paths.

A partial solution to the last-click challenge is Google's introduction of the paid search funnel, which allows you to track the path to conversion. Many analytics packages such as Omniture focus on detailed level attribution, allowing you to see the exact path toward conversion and figure a multi-level return on ad spend model accordingly. If you are using Google Analytics, you can begin moving down this path with AdWords Search Funnels, which allow you to see Assists (pre-conversion visits), time lag to conversion, and the length of the path until completed conversion. For companies with longer lead or buying cycles, these reports are particularly useful in helping to move toward a more accurate attribution model.

Traditionally, the keyword-level Return On Advertising Spending (ROAS) has been calculated simply as:

Clicks * Revenue-per-Click / Ad-Spend

The trick is to avoid attributing the entire revenue to a single keyword, and instead, consider potential return from other keywords that converted later on in the funnel. In the context of search marketing, you can see which keywords may have contributed to conversion since the interactions between generic keywords, which foster brand awareness, and brand keywords, with a higher conversion rates, rate can help you determine an overall Return on Investment (ROI). While attributing a high conversion rate and return on brand keywords is a standard practice, many conversion paths feature more than one click, requiring you to drill deeper to gain further insights into consumer behavior. Understanding how the majority of conversions emerge can help you prioritize your placement, bids, and investment in various marketing channels.

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