Competitor analysis is something clients and bosses love. Over the years, we have gotten better at formatting and presenting auction insights data, but it was lacking in both device specific data as well as recommendations. In this new templated report we pull in the best of both worlds – device analysis and auction insights competitor data. In this post we’ll walk through what data we’re using and how to put it all together.
The first thing you’ll want to look at is performance by device. This is straightforward, download (or run a Supermetrics report) breaking your campaigns down by device.
I like to look at overall performance, as well as any trends or shifts. To make this easier, segment by date (or whichever time segment you prefer).
Report on the success metrics for your account. Most of the time, this will be conversions, CPL, revenue, etc. This will give you a good pulse on how each device performs.
Device Impression Share & Competitors
Next we’ll visit the Auction Insights section of AdWords to take a look at what our competitors are up to. In addition to Auction Insights, I make sure to include search impression share, lost impression share due to budget, and lost impression share due to rank in the campaign data pull mentioned above. This gives us a more holistic view of impression share.
Segment the report by device and time (choose which time segment you’d like to use – matching whatever you used in the Campaign data pull).
Current Modifiers in Place
I also like to download a campaign report showing which modifiers we’re currently using. This is important, because your interpretation of the data will be different if you’re looking at a campaign with no modifiers, and one with -50% on mobile.
Putting It All Together
Now that we have a bunch of data, it’s time to put it all together to tell a story and get some meaningful insights.
We are using Google Sheets for this task for a few reasons. The first is that it’s easy to pull data into (we use Supermetrics to pull campaign data). Second, I’m a fan of Query functions and sparklines for easy data manipulation and visuals. Another benefit of Sheets is that it’s easy to share and collaborate with.
Alright, let’s get reporting!
First, we create a chart with a device overview, and separate weekly charts for each device type.
Now we can start building the components of the dashboard.
Here is a snapshot of Mobile devices. The “trend” is calculated by taking the slope of the data over time frame selected. Once the slope is calculated we compare that to a set of ranges that we have determined (if the slope is in this range, the trend is decreasing, if it’s within x range it’s flat, etc.) Before you yell at me, it’s not a perfect method. Which is why we include the sparkline is give the overall graph of the metric. Sometimes the slope reads in the “decreasing” range, but as you can see, the metric has been pretty spikey. We don’t want the trend to be deceiving, so the sparkline gives a bit more context.
Next up is the top competitors in terms of impression share, this is from the auction insights report. Again, this uses the handy-dandy notebook query function.
Some quick visuals give the user a good overview of how different competitors stack up in terms of impression share by device.
The last component is some automated recommendations. Like most of our tools, this one will evolve over time. Some specific projections and recommendations for device modifiers will be built out, to give the account manager some more concrete numbers to work with.
Here’s a closer look at the recommendations:
The upfront time investment in building templates like this one can be daunting. However, you’ll end up saving a lot of time in the long run, especially if you run this report frequently.
When creating a report that’s meant to provide insight, takeaways, and action items, be sure to put some thought into how you can make that easier on yourself. Write a formula that will tell you if a campaign is over or under performing, and have it spit out some bid suggestions.