Impressions and clicks have long dominated the metrics of online advertising. Yet these two metrics may be the least important metrics in measuring the effectiveness of any particular banner or display ad.
Ad Impressions reported by ad networks simply reports the number of ads that were sent from the ad server to the user’s browser. The term is misleading because it doesn’t mean that the ad was ever seen by the user. The ad may have never rendered within the browser or may have loaded below the fold where the user could only have seen it if they had scrolled down the page.
Clicks on display or banner ads are still the standard way success is measured when reporting results from online ad campaigns. It’s a logical assumption that clicks on ads that lead to pages designed to convert visitors would be the most important measure in attributing the value of a lead or sale.
A study released in April by ComScore and Pretarget questions these two fundamental metrics. Over a 9 month period, Pretarget and ComScore undertook a large scale study of 263 million ad impressions across 18 different advertisers. They gathered not only typical ad reporting data such as impressions and clicks but also other data including viewability and hover data. Clicks and cookie-based conversion data were also collected for the ads served. Conversion was defined as either a purchase or a request for information.
A Pearson correlation analysis of ”gross impressions,” “views” (defined as 75 percent of the pixels of an ad being visible in a browser either above the fold or after scrolling), “time-in-view,” “hover/engagements” and “total hover/engagement time,” ”clicks” and ”conversions.”
The Pearson product-moment correlation coefficient is widely used in statistics to measure the strength of linear dependence between two variables. The correlation coefficient value ranges from minus one to plus one (-1 to +1). A value of plus 1 denotes a direct linear relationship between the two variables while a value of minus 1 shows a direct inverse relationship between two variables (as one goes up the other goes down). Ä coefficient value of 0 means no linear correlation between the two variables.
What they found should lead to a reevaluation of Key Performance Indicators (KPIs) for online display and banner advertising campaigns. The metric with the highest correlation with conversion was ad hover/interaction with a correlation coefficient value of 0.49. Viewable correlations had the second highest correlation (coefficient value = 0.35) followed by a significantly lower gross impressions correlation (coefficient value = 0.17).
What should be most interesting for online advertisers is that the correlation coefficient value between the variables of clicks and conversions was 0.01! Let me repeat this finding: this study found no statistical correlation between ad “clicks” and conversions!
This study, along with other studies with similar conclusions should make online advertisers change the metrics they are using. MediaMind’s “2009 Benchmark Report" released in 2010 revealed that increasing average Dwell (hover) time from 5 percent to 15 percent increased conversion rate by 45%. In another study, Casale Media’s 2011 “Ad Visibility Report” showed that ads that appear above the fold were 6.7 times more effective at producing conversions than ads appearing below the fold.
It’s time for advertisers to look at their attribution models and definitions of KPIs. If you measure the success of your online advertising by looking at the last click to determine a display ad’s effectiveness you are missing the boat entirely. If you are using ad impressions as a KPI, there are better metrics to use.
Advertisers and their agencies should be paying close attention to how they measure the effectiveness of their online advertising campaigns. Clicks would appear to be a poor indicator of resulting conversions. These studies bring a new dimension to the shift away from last click to multi-touch attribution modeling underway.