Volume 1, Issue 4 - May, 2011
Bill Muller, Editor
Along with the most obvious campaign attributes that impact cross channel marketing performance - traits like publisher, size, creative, keyword, placement, etc. - are a number of less intuitive factors that can significantly influence your results. Among these more ancillary factors is “frequency” - specifically the frequency with which online users are exposed to a given marketing tactic in advance of an eventual conversion. A byproduct of applying multi-dimension attribution modeling to your cross channel marketing results will be findings that uncover the number of impressions generated within one channel beyond which an acceptable return in conversions fails to take place via other channels.
Let’s take the example of conversions that are recorded via the search marketing channel. Not only do we all intuitively know that online display ad impressions drive users to perform searches for specific keywords that eventually lead to conversions that take place on the search engines, but through the application of attribution management we can actually quantify this impact. But one dimension to those attribution findings that is often overlooked - that also needs to be quantified - is the maximum number of display impressions for which you are willing to pay to produce a search conversion. In effect, you need to start thinking about establishing cross channel frequency caps.
Digital media planners and buyers are familiar with applying frequency caps to their display assets based on some number of impressions above which the ads have historically failed to produce an acceptable return based on conversions recorded through clicking directly on the ads. But the reality is that a frequency cap established using that one-dimensional criteria might be limiting a very positive return that those ads may be generating via conversions they drive within the search channel.
Once this frequency data is revealed through your marketing attribution results, this number will probably differ from publisher to publisher. But the beauty of multi-dimensional attribution is that you can easily drill down to as granular a level as you wish in order to uncover these findings, which will inform the actions you take (across the combination of the publisher, keyword and search engine dimensions, for example) to optimize the performance produced by the interaction of the display and search channels.
As an example, imagine that the acceptable return on advertising spend (ROAS) for a given marketer is 8.5. In this case this ROAS includes both the cost of the search clicks, as well as well as the cost of the display impressions. In the chart below, you’ll see that running a specific paid search ad on a specific search engine produces an ROAS of 8.5 or greater until online users have been exposed to eight display ad impressions recorded by a specific display ad on a specific publisher.
After that point, the ROAS drops well below 8.5 as additional costs are incurred but conversion delivery tapers off. So in this case marketers would want to apply a frequency cap of eight to this particular display ad on this particular publisher. But the fact is that in this example the frequency cap that the marketer probably would have applied based solely on the ROAS of conversions recorded through clicks directly on the display ad would have been five - leaving lots of affordable conversions that could have been recorded via the search channel still on the table.
Now the impact of such a frequency cap on the other dimensions of your marketing ecosystem should certainly be assessed to ensure that performance gains achieved for this keyword/search engine/publisher combination do not have corresponding losses elsewhere. By looking at the attribution results for display ad frequency across all keywords and engines, odds are you’ll be able to identify a number of instances where significant media efficiencies and performance gains can be achieved by toggling up or down impression frequency caps as needed.
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