Volume 3, Issue 5 - May, 2013
Darius Jose, Data Scientist, Visual IQ
Reach is a critical metric for planning and measuring the success of online display advertising campaigns. Used to measure the total number of people exposed to an ad at least once in a given time period, reach analysis can provide insights to help marketers maximize their display performance
Most publishers sell impressions based on a flat rate or CPM. But when a hundred million impressions are served, how many impressions - and therefore media dollars - are potentially wasted by serving the same ad to the same person again and again?
To demonstrate how much media is wasted, reach data was recently analyzed from an actual advertiser’s campaign to see how many times the same user was exposed to the same ad, with the same creative, by the same publisher, more than 100 times. Out of the total 71.6 million impressions served during a three-month period, 9.2 million impressions met this criteria. That’s more than one impression wasted to that extreme for every eight impressions served. And this doesn’t count the number of impressions being served over 75 times, or over 50 times, etc.
It is important to note that the data used in this analysis came from an advertiser with a relatively small media budget. Imagine how much spend would be just as wasted by an advertiser who purchased 100 times as many impressions. Reach and frequency analysis can help mitigate this waste by identifying the amount, and magnitude, of duplication among users. Further drill-down on reach data can also uncover which publishers are contributing to the bulk of this waste, as a large percentage might be attributable to just a few publishers.
Popularity of Web Pages
Marketers want an accurate understanding of the number of users who visit the websites on which their display ads appear, but this visitor data regarding web pages isn’t always readily available. Fortunately, display reach analysis offers a simple way to estimate the overall number of visitors to a page without using complex math.
For example, let’s say 100,000 cookies were served at least one impression on a specific web page during the past 30 days. The next week, 5,000 cookies were served at least one impression. If 400 of those cookies are common to both data sets, then the number of visitors to the web page during the past month can be approximated at 1.25MM (100K x 5K / 400). With this information, marketers can make informed decisions about ad placement on sites using accurate traffic volumes.
Diminishing Returns in Media Budget
Is it beneficial to have someone exposed the same ad a sixth time when he has already been exposed to it five times? Display ad reach analysis can help determine the point of diminishing return on ad frequency and inform the establishment of frequency caps. To convert customers in the most cost-effective way, marketers should set caps at the frequency where the probability of conversion multiplied by the expected return per conversion is equal to or less than the cost per impression.
For example, let’s assume there is a .10% chance of conversion for cookies that are served an ad five times, and a .12% chance of conversion for cookies that are served an ad six times. This means that of 10,000 cookies, a marketer can expect ten conversions from ads served five times and 12 conversions from ads served six times. Now suppose the margin per conversion is $100. If the benefit of two extra conversions (i.e., $200) is greater than the cost of serving an additional ad to 10,000 cookies, a marketer may decide to increase the frequency cap from five to six.
Media wastage, page popularity and frequency capping are just three of the insights that marketers can glean from display ad reach analysis to help maximize the value of their investments in that channel.
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