1,000% Uplift in Out Of Home!?

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Calculating ROI in Out Of Home advertising is hard. That is why you see crazy metrics like a 1000% uplift. We walk through why that happens and how we give you better, more actionable intelligence.

NEW YORK - eTradeWire -- Calculating ROI and attributing value to an Out Of Home (OOH) advertising campaign, such as billboards or car wraps, requires billions of data points from mobile location data. One of the most challenging problems to overcome when working with mobile location data is developing accurate exposed and unexposed groups. Those challenges mean that it is not always possible to determine causality from the information that we have.

It also means that without proper care, you often end up with uplift well over 200%.

We're not kidding - we have actually seen uplift studies with numbers as high as 1000% from some of the largest attribution companies out there.

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Companies have actually proposed that their campaign was so effective it increased visitation rates in the exposed group by 1000%.

Intuitively, this can not be correct. That would be the most effective campaign in the history of advertising. If the propensity to purchase is similar between exposed and unexposed groups, then there should be an eye-watering boost to sales. Imagine the case where you did a massive campaign of 200 cars and 200 billboards. You would "expose" the majority of a population, even in a big city like New York. Revenue would subsequently grow by hundreds of percent. It doesn't, so there is an obvious catch here.

How do I find an equivalent unexposed person to myself that has not seen the ad? The answer is that if the campaign is massive - few people have an unexposed equivalent.

Why This Happens

At mobilads, we have always made the decision to stay honest.

That means we don't exaggerate and we give brands honest feedback on the success of the campaign. We do this because we think that:

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- Our campaigns are effective without exaggerating numbers
- We believe that by delivering an honest and reliable analysis, we can work with brands to optimize where and how we are advertising with them - adding even more value

We do not do ourselves or the brands we partner with any favors in providing flawed analysis, and it prevents the valuable step of optimization.

How do these numbers get so skewed? Our competitors are not lying, they have run the numbers without proper respect for the underlying data they work with. The problem has its roots in selection bias, and this is broken into two essential topics. Selection bias due to methodology and selection bias due to the data.

Visit us at https://www.mobilads.co/

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Source: mobilads
Filed Under: Advertising

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