The Accidental Developer

Online Advertisements and Statistical Analysis

Quite a few years ago, I was in the online advertising business. My team and I created banner ads to run alongside web site content, to entice viewers to click on ads and find out more about advertiser offers. We scheduled ads to run alongside specific content. We targeted ads towards users in specific geographic regions, thanks to a browser cookie that told us their ZIP code. And we constantly managed inventory.

Although we made animated ads, we avoided anything that blinked. There were no monkeys to punch.

Click-Through Rate (or Click-Thru Rate or CTR) was a key measurement of an ad’s success. Although at first we would sometimes see click CTRs between 1-2% (meaning that an ad was clicked between 10 and 20 out of every 1000 views, or impressions), as online advertising proliferated, and as our systems got better at filtering out false impressions and clicks from various robots, crawlers, and spiders, CTRs trended much lower: 0.25% suddenly looked good, and 0.10% was not uncommon in some cases. That’s 1 click for every 1000 impressions.

That’s why we were insanely interested in a blog post we found, now presumably lost to the ages, that ran a set of 6 banner ads, which varied only slightly, and analyzed the results to determine what aspects of the ads could improve CTRs. Did including the phrase “click here” really help? If the words “click here” were in blue and underlined, like a typical web link, would that improve the CTR?
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Tags: banner ads, click-thru rate, ctr, online ads, online advertising, statistics, stats