Just a few years ago, the paid search landscape could adequately be summed up as “text ads on desktop computers.”
This simplicity meant analyzing performance didn’t require too much slicing and dicing to get meaningful takeaways from paid search data, and often a simple brand vs. non-brand look would do the trick.
With the rise of additional ad formats and devices, however, understanding search performance requires that PPC managers and analysts dissect their data in several specific ways before coming to any conclusions.
Here, we delve into the most important of those segmentations and why each is critical in paid search performance analysis.
Device segmentation is critical
According to Merkle’s Q1 Digital Marketing Report (registration required), the share of paid search traffic coming from desktop computers is now just 47 percent, with 39 percent coming from phones and 14 percent from tablets.
For most advertisers, these devices perform very differently from one another.
For example, on average, phones produce revenue per click that’s 62 percent lower than that of desktop computers for Merkle advertisers, while tablet revenue per click is 30 percent lower.
So lumping all three device types together when analyzing performance can hide the details of the true value of each. By segmenting, advertisers can understand how each device type is performing and set bids accordingly.
While Google campaigns used to lump desktop and tablet computers together for use in keyword base bids, recent updates announced these two device types will be split up, and advertisers will also now be able to set desktop, tablet or mobile as the base bid for keywords.
Aside from different per-click value, there are also frequently updates made by the engines which stand to impact only a single device type.
For example, Google’s addition of a third text ad above the organic links on phones in Q3 of 2015 significantly increased mobile traffic, with phone clicks up 51 percent for that quarter.
Source: Three of the most important data segmentations for any Google paid search analysis
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