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Media Attribution

The Double Counting Effect

Key Facts:

The use of multiple third party conversion tags (e.g., pixels that record conversion events in advertising analytics packages) results in revenue overstatement, as different channels claim credit for the same conversion event.

Based upon an analysis of Convertro ecommerce client data, a conversion, on average, involves 3.3 known contributing sources. This implies that clients using multiple conversion tags experience a high degree of double counting.

Tracking Method	Description
Single-Vehicle Tagging	Using multiple conversion tags for individual sources (e.g., concurrent use of the Yahoo!, Google and Bing Conversion tags) maximizes the double counting effect.
Multi-Vehicle Tagging	Some marketing companies provide a single conversion tag that records conversions generated by a range of vehicles (e.g., the three major search engines). This prevents double counting conversions from paid search traffic (e.g., ads purchased on Google, Yahoo!, and Bing). However, these conversion tags do not factor into account the traffic driven by other sources such as organic search, comparison shopping engines, display ads and other known referring sources.
Total-Vehicle Tagging	Having a single tag for tracking all sources is the only way to eliminate the double counting effect.

The "Last Known Source" Problem

The majority of analytics tools, bidding tools and third party tracking tags give 100% credit to their last known source - a.k.a. "The Closer".

Based upon an analysis of Convertro ecommerce client data, we see an average of 3.3 known contributing sources per conversion; this means that the majority of sources are ignored in models that only consider the last click.

Conversion tags, even when just a single vehicle is involved, can lead to problems if credit is given only to the last known source. In the case of Google, for example, Convertro ecommerce client data reveals on average two Google PPC ad keyword triggers for every conversion event. Under the last known source scenario, this means that half the conversion-generating keywords would get zero credit (and conversely, half would get full credit even though they were only partly responsible for the conversion).

The last known source model ignores the entire top of the funnel sources known as "introducers," and the middle of the funnel sources known as "influencers." These sources receive no conversion credit and are thus deemed to be ineffective, when in fact they represent an indispensible part of the conversion funnel. Instead, navigational traffic, such as "branded" terms that are searched right before the conversion event, receives disproportionate credit.

Multi-Attribution

Giving each and every source involved in a particular conversion event a pro-rata share of the conversion value is critical to evaluating the true effectiveness of any particular campaign.

Convertro solves the Double Counting Effect and Last Known Source Problem by allowing clients to use a single conversion tracking tag and applying multi-attribution logic to the data. In addition, marketers can toggle between Multi, First and Last known paid source filters to see how their data would look under each scenario.