Managing PPC campaigns often raises questions about how well your activity is doing compared to everyone else and also against expectation. Whilst we can see what happens to our impression and click volumes and costs when we actively make changes to the account, often it is the behaviour of others which influences the final results. So how do you keep abreast of what everyone else is doing and how do you know if you’re doing well or not?
Unfortunately, you can’t see directly into another advertiser’s Google or Microsoft ads account, and even third party analysis tools use estimations to offer insight into what others are doing. So whilst third party tools can get more accurate by having all advertisers in your market plugged into them, there is always going to be some formulaic approach to reverse engineering what they’re doing (as not everyone will be sharing their data).
As an independent digital agency we don’t have deep pockets, and whilst we have used some of these tools in the past, we have found they can be wildly inaccurate and thus their cost outweighs their usefulness. However, we do pay a lot of attention to competitive metrics made available to us within the ad platforms - impression share and click share.
Click share vs impression share - the main difference
In the simplest terms, impression share shows you how many times an ad has appeared on a search results page, while the click share allows you to measure how frequently an ad is clicked on. The metrics essentially allow you to work out an ad's potential for generating a lead/sale and thus, performance. We go into more detail about how click share and impression share are worked out later on in this article.
Impression share
By definition:
"Search impression share" is the impressions that you’ve received on the Search Network divided by the estimated number of impressions that you were eligible* to receive.
It’s worth noting here that your search impression universe may be lower than the total available search volume for a given phrase because of your eligibility. In the keyword planner tool, if you do any kind of keyword research you’ll be familiar with the metric ‘ad impression share’ which is a variation of search impression share, but could highlight where there may be further gains to be made.
“Ad impression share” is the number of impressions you've received divided by the total number of searches for the location and network you’re targeting that matched the keyword exactly in the last calendar month.
*Eligibility is based on your current ads' targeting settings, approval statuses, bids and quality.
These impression metrics on their own can’t offer all the answers into whether we could/should be doing more to win more impressions. That’s where Search lost (budget) and Search lost (rank) impression share metrics come in.
For budgeting purposes I rely on the impression share value and search lost (budget) metric to determine whether my budget caps are preventing maximum exposure, and if money wasn’t an issue, what the potential exposure/spend could be.
If search lost (budget) is 0% and you’re still not hitting a 100% search impression share, then you’re missing out due to ad rank, which means you’re being held back by Google because of your ad account quality and relevancy for the keywords you want to appear on and/or because your competitors are willing to pay more than you.
Improving ad rank can be done by increasing your maximum CPC bid, and/or by improving your quality score. Depending on your performance the simplest solution would be to raise your bids, but most advertisers should seek to improve relevancy to prevent over-paying for clicks wherever possible.
Now, I have to admit that I was managing PPC campaigns when we had access to average position results. Whilst I understand the reasons behind their retirement, they were also really helpful to learn where in the ad landscape you (and your competitors) were appearing, and you could optimise to different positions. In their place we currently have ‘search top impression share’ and ‘search absolute top impression share’ which indicate more loosely where your ads appear in the search results.
“Search top impression share (IS)” is the impressions you've received in the top location on the search result page divided by the estimated number of impressions you were eligible to receive in the top location. The top location is anywhere ads appear above the organic search results.
"Search absolute top impression share" is the percentage of your Search ad impressions that are shown in the most prominent Search position.
I spend a lot of time monitoring these metrics for my clients, and have a keen interest in how percentages change when we optimise the account. Thankfully we can also see the same figures for other advertisers in the auction and often use these auction insights to explain why CPCs have risen/fallen or we’ve lost top impression share. Be mindful that their results are only based on the same keyword set you’re bidding on, so you can’t find extra information about what they’re doing that you’re not.
Interested in auction insight analysis? Read: Improving competitor intelligence for marketing decision making
Click share
Impression share metrics are only part of the puzzle. Click share has been around since 2019, but I’m not sure how many advertisers or agencies use this metric when reporting on results as CTR has been the prevalent indicator of response rates to ads for as long as I can remember.
We are however, spending more time reviewing click share as I think it is actually more useful than CTR in many cases. We’re often asked by clients ‘what is a good CTR?’ and whilst 15 year of experience can offer some educated responses based on brand vs. generic keywords and position, it is not as reassuring as seeing a comparative metric like click share.
Google’s definition:
"Click share" is the clicks that you've received on the Search Network divided by the estimated maximum number of clicks that you could have received.
Put a different way, if you had a CTR of 2% (which seems low) but a click share of 80%, what this means is that when your ads are shown they are getting clicked as often as they should and that they’re extremely relevant to the searcher. Despite a low CTR, for this search term you’re performing as expected. The ones to be concerned about are low CTR and low click share because then it means you’re under-performing.
If you need a little extra help, Google offers an ‘ad relevance’ and ‘expected CTR’ grade for keyword level analysis - this can range from poor to excellent. It also gives an ad strength score for Responsive Search Ads.
If you’re of a curious nature, it could be worth your while analysing your account and seeing if you have a correlation between impression share, click share, expected CTR and ad relevance which in turn may shed more light on how the Google ads system operates.
For those running display campaigns there is an additional benchmarking metric - relative CTR. This calculates your CTR divided by the average CTR of all advertisers on the websites that show your ads. A relative CTR close to 100% means your CTR is close to the average CTR of all advertisers on the same section of the website.
Put all your efforts into achieving high relevance
The final word is that thing to focus on above all of this is relevance. Regardless of the metrics and percentages mentioned in this article, the priority when running a PPC campaign is ensuring you have the right keywords and the right targeting for your business. We can all fall foul of chasing the highest CTR, the best impression share and best click share, but you have to make sure that you are buying the right traffic, traffic that brings in relevant site visitors who will engage with your website in the way you want them to.
Don’t just steam ahead looking to win all available impressions and clicks. Pause for a moment and consider whether there are layers of segmentation (audiences, devices, time of day) where you should concentrate your efforts, and contextualise what your results mean for your business. If in doubt, test and learn using experiments.
