Attribution Model – Einstein Shocks Online Advertising

“Information is not knowledge.”
-Albert Einstein [and C3 Metrics]

Every year marketers approve Internet advertising budgets, spending a collective $71 billion dollars worldwide.

Huge amounts of time are spent tracking results, and gathering “information.” Webster defines “information” as the knowledge obtained from investigation, study, or instruction. But Albert Einstein disagreed.

Einstein insisted that “information is not knowledge” because of his intrinsic understanding that facts, when presented in the wrong order, or seen in the wrong light, can only lead to disinformation.

An attribution model with the wrong order, in the wrong light, makes what you thought was good information…wrong.

Decisions are only as good as your information. Today, the industry’s outdated online ad tracking systems erroneously give 100% credit to the very last clicked or last viewed ad before a transaction.

Example: if four Internet ads contribute to a transaction; today’s outdated systems allocate entire credit to the very last ad, completely ignoring the first three ads which actually drove the revenue.

Zero credit to revenue drivers, and 100% credit to the last ad placed. Nervous?

Now enter a robust attribution model: at C3 Metrics (disclosure, I’m the CEO), attribution modeling takes an enormous amount of ingredients, and reduces complexity into simplicity.

At a basic level, C3 assigns credit to Originators, Assists, and Converters within a transaction. An attribution model should capture every online media source from the top of the funnel where sales originate…down to the very bottom of the funnel. So in a $100 transaction, an Originator would receive a fraction of $100 attributed to them—and the Assist and Converter would also receive fractional credit of the $100 attributed respectively.

100% of revenue credit is attributed and split among Originators, Assists, and Converters–accounting for the actual drivers of revenue. Then revenue and respective costs from paid media sources converge in a single, elegant number in the attribution model: Attributed Revenue-to-Spend Ratio (ARSR™).

It’s a simple ratio any marketer can grasp: attributed revenue divided by corresponding spend. If you have a 4.0 ratio for a specific keyword, or specific Display campaign–you’re getting $4.00 in revenue for every dollar spent on that particular media source. Conversely, if you have an ARSR of 1.25 for a particular media buy—you’re getting $1.25 in revenue for every dollar spent there.

For brands that don’t transact dollars on their site, they simply assign a revenue value for: a dealer zip code lookup, building a vehicle online, or scheduling an appointment online.

ARSR delivers knowledge ready to act on, versus information barely ready to analyze. The special sauce of the attribution model is the numerator of the ratio (attributed revenue). Media buyers easily identify media sources with high numbers to scale, and low numbers to cut or improve. Instead of taking weeks, it’s about an hour.

But Einstein’s hairdo gets electric with results. In the longest running attribution study of its kind (2 yrs) the results are electrifying:

a) Seven-figures in profit from the advertiser’s higher ROI online ad spend
b) Display ROI improvement of 160%
c) Search ROI improvement of 98%
d) Accurate economic model to measure affiliate performance

Bottom line: millions of dollars in profit.

Less time performing attribution analysis: check.
Millions of dollars in profit using actionable knowledge: check.

You don’t have to be Einstein to figure this out…attribution done right saves you time and makes you a hero.

Are you ready to solve your own equation?