Use Sorting and Filtering Aggressively to Make PPC Reports Actionable
Sorting & filtering are two powerful tools for preventing data paralysis and turning mounds of data into actionable insights. Today’s PPC platforms give you access to so much data that if you aren’t using sorting and filtering it’s virtually impossible to get any value out of reporting.
Do you know the difference between sorting and filtering? They seem similar on the surface but they actually work very differently and are useful in different scenarios.
Here’s a quick rundown of both and how to use them in your PPC reporting…
Sorting
Sorting takes a set of data and sorts it by a chosen metric or letter. The most important difference is that sorting does not remove entries from the data set. Sorting only puts the data into a new order.
For example, if you want to see which of your ads generated the most conversions you can sort by the ‘Conversions‘ column.
Or if you want to see which ad is eating up the most budget you can sort by the ‘Spend‘ column.
You can also sort by other useful metrics like:
Impressions
Clicks
CTR (click-through rate)
Sorting is a powerful way to look at all the data in an ad group or campaign without feeling paralyzed by the amount of information. Using sorting you can quickly make optimizations to your ads account and find out what is or isn’t working based on your success criteria (clicks, conversions, CTR, etc.)
In the screenshot below the Facebook ads report is broken out by placement and sorted by Spend meaning it will show the placements that spent the most money first. This lets me quickly see if any placements are eating up too much budget for the conversions they’re driving.
Scrolling further right in this report shows me that there’s a CPA difference of 31% between mobile and desktop devices. If $2.32 were above my CPA threshold I would then know to pause the mobile ads and reallocate the budget to desktop only.
Filtering
Filtering on the other hand is useful in a different way.
While sorting will give you the option of choosing which metric you want to prioritize, filtering actually removes data that’s irrelevant to your analysis.
For example…
Lets say you’re working on an AdWords account that has 20 paid search campaign and they’re all a total mess. It has tons of keywords, match types, different ad variations, landing pages, the whole shebang. Most AdWords accounts are mangled and mashed like this so knowing how to filter your data the right way is crucial.