Attribution’s Value to the Customer Intelligence Function By Bill Muller, Editor
With the emergence of the Customer Intelligence (CI) function within many enterprise-sized marketing organizations has arisen the desire to look at customer behavior across the entire marketing ecosystem. Inherent in attribution modeling’s functionality is the ability to do just that – to not only scientifically assign credit to the channel, campaign and campaign traits that helped marketers achieve success by whichever key performance indicators they choose, but also to associate that media performance success with the demographic and behavioral traits of given audience segments.
Let’s look at just three examples of CI value that can be drawn from the attribution process:
As transactional data that’s associated with customers is fed back into the marketing attribution process, it can be married with media performance data and customer demographic information (that’s collected through the transaction process, surveys, or via overlay by any number of third-party data providers). As a result, algorithmically attributed media performance can be identified for an organization’s highest value customers, or by those with the highest propensity to convert, or by those with the highest propensity to be repeat buyers – as defined by the demographic and behavior traits of a particular customer segment. Armed with this information, CI professionals can advise their online and offline media buying colleagues to adjust their tactics by customer segment to increase LTV, conversion rates and yield.
Mapping the Funnel
By analyzing the demographic characteristics of customers whose marketing performance data has been fed through the attribution process, CI professionals can also identify the tactics that produce the best results at each stage of the conversion funnel – by audience segment. Which channel, publisher and offer serves at the first touch (“introducer”) for the customer segment with the highest LTV? Which combination of tactics serves as the last touch for the segment with the highest propensity to be repeat buyers? For the highest value customer segments based on several different key performance indicators, what do the ideal conversion funnels look like? With answers to questions like these, the CI function can not only advise the rest of the marketing organization on which tactics produce the highest results by customer segment, but can also prescribe at which funnel stage and in which sequence those tactics should be executed.
Assessing Lag Time
There are numerous “lag time” metrics associated with every customer’s stack of touchpoints on the path to a conversion. The time between every milestone – first impression, first click, first website visit, last impression, last click, last website visit, conversion, etc.-can be calculated, and as with the examples above, can be associated to the demographic traits and media performance of the highest value audience segments. With the intelligence gleaned from this analysis, CI professionals can advise media professionals on which audience segments have the longest and shortest lag times between critical milestones in the conversion funnel, the lag times for the highest value segments, and which media tactics should be employed to produce faster conversions, higher value customers, and the greatest return across the entire marketing ecosystem.
Just Scratching the Surface
Though attribution is rapidly on the rise within the media buying function at many organizations, the Customer Intelligence function is rarely taking advantage of the cross channel touchpoint intelligence that only the attribution management process can provide. But as these professionals begin to experiment with attribution and incorporate it in the value-add they provide to their media buying colleagues, it will undoubtedly become their default methodology, never again choosing to look at audience characteristics in isolated, non-attributed silos.
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Articles From Industry Publications
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By Anto Chittilappilly, Co-Founder, President & CTO, Visual IQ
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Note to The Editor
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