How to calculate Attribution’s ROI: The Formula. [INSIGHT]

A question that frequently arises when brands or agencies consider an investment in a marketing attribution solution is how to calculate the return on that investment.  Of course, advertisers also tend to realize many incalculable benefits once they implement attribution, including (but not limited to) a stronger faith in the accuracy of their overall measurement practice,  a third party accountability layer to evaluate all media partners, and installing the cornerstone of a fully data-driven marketing practice, but fiscal decisions do often require fiscal answers.

Understandably, marketers want to be able to estimate their actual dollar return in advance to ensure that the solution will pay for itself via potent optimization that generates meaningful media efficiencies.  They also need to ensure that once the engagement starts, they have an ongoing methodology for holding their attribution provider accountable for producing the results they expect.

Collect These Values

So what follows is a straightforward methodology for either predicting the ROI of your attribution solution in advance, or calculating its actual ROI post-implementation.  A visual aid is available to help walk you through the math of the example that is described below. The values you’ll need to gather in order to calculate the ROI of attribution are your historical annual figures for:

– Media spend for channels on which attribution will be performed (M)
– Quantity of conversions currently attributed to those channels (C)
-The total value of sales/revenue currently attributed to those channels (TV)

Calculate These Values

Once you’re armed with these values, you can then calculate two other annual values that will be needed:

– The average value of a conversion (CV) which will be TV/C (or you may already have a working value for each conversion to be used in place of this calculation)
– The gain in revenue recognized over your costs (G) which will be TV-M

So as a prediction example,  assume that your media spend is $10 million (M), you produced 50,000 conversions (C) that generated $35 million in total sales/revenue value (TV), then your average conversion value (CV) is $700, and your gain (G) is $25 million. These figures provide an accurate picture of your current marketing environment without attribution implemented.

The Post Implementation Side

Next, in order to predict what your environment will look like with attribution implemented, one additional value is needed that takes into account the implementation of your attribution solution.  This is your attribution project expense (APE).  This value is derived from the sum of these three costs:

-Incremental internal human resource costs required to launch the attribution solution and enable it to become a self-sustaining component of your marketing ecosystem – assume half of a full-time employee for three months.  Thereafter, any human resource costs associated with utilizing your attribution solution will typically be covered by the time savings that attribution has enabled you to achieve via reporting and analysis efficiencies. 
-Data integration costs, including incremental ad-serving costs required to obtain cookie data (rule of thumb = $1,000 per month), plus the incremental ongoing human resource cost associated with placing tags on all your digital assets (rule of thumb = $1,000 per month).
-Finally, the complete annual costs paid to the attribution provider, for licenses, service and support, set-up, rev-share (if applicable), etc.  

Once your attribution project expense (APE) has been calculated you have everything you need to predict (or calculate the actual) ROI.  To walk through the example, start by assuming a lift in conversions of just 10% as a result of implementing your attribution management solution. Projected figures for this lift value vary depending on which attribution provider you talk with, but most projections fall within the 15%-35% range.  In our example the number of conversions (C) was 50,000, so in our post-implementation scenario it will be 55,000 (AC) at the same $10 million media cost (AM).  Assuming our same historical average conversion value of $700 (ACV), these 55,000 conversions will produce $38.5 million in total sales/revenue value after the implementation of attribution (ATV). 

Then by adding the $10 million media costs to an attribution project expense (APE) of $250,000 (in this case, 2% of media spend plus incremental human resource costs plus data integration costs) you derive your total cost (ATC) – or $10.25 million.  By subtracting the $10.25 million cost from the $38.5 million in total sales/revenue value you derive a gain after the implementation of attribution (AG) of $28.25 million.

The final step is to subtract pre-attribution gain (G) from post-attribution gain (AG) and divide the remainder by the attribution project expense and express as a percentage.  So in our example:  $28.25 million minus $25 million = $3.25 million, divided by $250,000 = 1300% ROI for the first year of implementation (with higher ROI for subsequent years when start-up costs are not incurred).  

Clearly, the conservative 10% lift in conversions that was selected as the basis for this prediction can realistically be adjusted up to 35% and beyond, and the 2% of media costs used to formulate the cost of attribution services could be adjusted to a lower figure.  Both would produce even more impressive ROI results.  But regardless of the values you plug into this methodology, it’s clear that implementation of an attribution solution can deliver significant ROI.

by Anto Chittilappilly
Anto Chittilappilly is Co-Founder, President & CTO of Visual IQ, a cross-channel marketing intelligence software company that provides attribution management insights and recommendations needed to successfully optimize campaigns and deliver maximum ROI for organizations’ entire marketing mix.
Courtesy of MediaPost

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