The underlying message that resonated throughout our course was that Digital Marketing offers a "measurable" ROI. Tools like Google Analytics help us to maximize this ROI. Things become a little complicated when your marketing dollars are being spent on multiple platforms e.g. Google, Bing, Facebook, Twitter etc. How do you collate the total ROI and is it even "measureable" in the first place.
A McKinsey article discusses about the ROI analytics for Digital Marketing. The article specifically dwells into the ROI from advertising on social media platforms. The main issue that the author tries to address is around the fact that "social-media-based marketing is driven more by faith than by evidence". The jist of the article is that there is huge data available to marketers, but its a challenging problem to analyze it and not surprisingly "McKinsey has developed three innovative analytical methods to help marketers better understand the impact".
But then I read another article on Mashable, and this one completely tilted the table around. As per the article, the Ad ROI attribution is impossible! If this doesn't sound true, you might want to look at the who came up with this conclusion. Randall A. Lewis (economic research scientist, Google) and Justin M. Rao (economic researcher, Microsoft) wrote a paper titled "On the Near Impossibility of Measuring the Returns to Advertising". The pair argued that the ROI data of digital marketing is not statistically significant. In their own words
"We find that even when ad delivery and consumer purchases can be measured at the individual level, linked across purchasing domains, and randomized to ensure exogenous exposure, forming reliable estimates on the returns to advertising is exceedingly difficult, even with millions of observations. As an advertiser, the data are stacked against you."
Even if I don't want to believe this conclusion, I can't help look at the fact that this paper was written by the scientists at Google and Microsoft! Probably this is not the whole story or my interpretation is wrong. This requires more research. More to follow!
A McKinsey article discusses about the ROI analytics for Digital Marketing. The article specifically dwells into the ROI from advertising on social media platforms. The main issue that the author tries to address is around the fact that "social-media-based marketing is driven more by faith than by evidence". The jist of the article is that there is huge data available to marketers, but its a challenging problem to analyze it and not surprisingly "McKinsey has developed three innovative analytical methods to help marketers better understand the impact".
But then I read another article on Mashable, and this one completely tilted the table around. As per the article, the Ad ROI attribution is impossible! If this doesn't sound true, you might want to look at the who came up with this conclusion. Randall A. Lewis (economic research scientist, Google) and Justin M. Rao (economic researcher, Microsoft) wrote a paper titled "On the Near Impossibility of Measuring the Returns to Advertising". The pair argued that the ROI data of digital marketing is not statistically significant. In their own words
"We find that even when ad delivery and consumer purchases can be measured at the individual level, linked across purchasing domains, and randomized to ensure exogenous exposure, forming reliable estimates on the returns to advertising is exceedingly difficult, even with millions of observations. As an advertiser, the data are stacked against you."
Even if I don't want to believe this conclusion, I can't help look at the fact that this paper was written by the scientists at Google and Microsoft! Probably this is not the whole story or my interpretation is wrong. This requires more research. More to follow!
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