How it all began
In February 2019, Google announced the retirement of one of its key metrics – average position. Since the launch of advertising on Google search (originating back to when RSA meant right side ads), average position had served as one of the legacy performance indicators for advertisers. Average position was simply a metric used by advertisers to determine where their ads appeared on the search results page (SERP) in comparison to other ads appearing.
For an everyday advertiser, analyzing average position and adjusting bids to achieve its campaigns goals was expediently simple and straight forward. Advertisers trusted the good old average position to not only control the position & performance but also assist in managing a campaign’s spend.
Clearly as average position proved to be such a valuable asset, it did have a few snags. To understand them, we need to draw back to the actual definition of average position and why it was possibly not a great measure of performance all along. Average position is just a mean average, a sum of positions simply divided by the sum of impressions. This fundamentally means that our ad could have been 50% of the time in position 2, and other 50% of the time in position 4, but the average would mathematically be 3. Here is the where the problem starts. Google simply gave us an average without a standard deviation - leading an advertiser to believe that their ads appeared in a position, which they may not have been in even once. This causes the metric to be slightly misleading and optimizing campaigns based simply off average position would lead to some advertisers relying solely on the metric as a constant as opposed to considering it as an average.
The problem then evolves as there is more hidden truth behind average position. The quality score along with the actual bid helps determine an ad rank. Within every auction, Google calculates and ties an ad rank to every ad that then defines the position on the SERP. Theoretically, that implies that our beloved metric is simply an indicator of where our ADs appeared in competition to the other paid results and not the actual location of the page. In simpler terms, our AD could’ve appeared in the first position throughout but could’ve always been below the organic search results at the bottom of the page. We’ve learnt over time that even though average position has been a good indicator, it can be confusing and shouldn’t be taken at face value.
So why did Google finally make a change?
Although no official statement reasoning why we bid adieu to average position, Google only stated that -to support advertisers further new metrics were released in November 2018 which gave a much clearer view of an advertiser’s prominence on the page than average position did1. From our viewpoint, over the years with various updates the literal meaning of average position doesn’t really stand anymore and is now more of an average auction position. This would drive the rationale of all advertisers to not look at the metric as where the ADs appeared overall on the page since average position could never tell us if ads ever appeared above the organic results or not. Migrating to newer metrics would ultimately benefit advertisers and hopefully now tell a complete story. Another potential reason to retire average position could be to possibly expect advertisers to switch from bidding for a specific position to now bid towards an impression share and further encouraging them to adopt a more automated bidding approach across their campaigns. The retirement although does raise specific concerns for advertisers that relied on year on year comparison data. As average position can no longer be reported on, and as the new metrics were introduced as recent as last November any yearly trends will now be difficult to identify and assess.
So what is life after Average Position?
In November 2018, Google released two new metrics for Search: Search top Impression Share and Search absolute Top Impressions Share metrics to provide a better picture of our ads distinction on a SERP, rather than average position. In addition, Search top impression rate & Search absolute top impression rate were also rolled out to allow for a more position based approach to optimize. Absolute Top impression as a metric has been available for shopping campaigns since 2017, where the left-most ad through the shopping carousel is considered a top spot. Based on Google’s internal data for the mobile shopping carousel in the US, the left-most ad results get up to 3X more engagement from shoppers2. For shopping advertisers, it has been imperative to adopt top impression share metrics as a performance metric and this has seen Google roll it out for Search further. After average position, advertisers can rely on -
- Search top impression share – Indicated by the impressions an advertiser received at the top location in comparison to an estimated number of impressions that they were eligible to receive in the top location.
- Search absolute top impression share – Indicated by the impressions an advertiser received in the absolute top location divided by the estimated number of impressions they were eligible to receive in the top location.
- Search top impression rate - Indicates the percent of ad impressions that are shown anywhere above the organic search results.
- Search absolute top impression rate – Indicates the percent of ad impressions that are shown as the very first ad above the organic search results.
These metrics are expected to fill the gaps that average position lacked and give more context to advertisers on the actual visibility of their ads and not simply the order. Advertisers now have complete transparency over the current position their ads and can measure it against the positions they would want to aim for by adjusting their bids accordingly. In terms of automation advertisers can adopt a target impression share bidding strategy to reach & optimize their campaigns for a prominent location on the SERP.
We have drawn the inference that optimizing and reporting towards average position had become less efficient to use and imprecise to break down conclusive results for clients. We have now adapted to Google’s new metrics to explain and optimize on more meaningful and accurate data, which allows for a clearer view to report on and take decisions for our clients.
At Merkle MENA, we pride ourselves on having specialist knowledge and adapting to the ever-changing Search landscape. If you’re interested to know more on what we recommend, get in touch at [email protected].