How to Solve an Average Position Glitch in PPC Advertising

Have you discovered the average position of your ads is less than one?

Although the metric can be a misleading measurement sometimes, in pay-per-click (PPC) advertising, obtaining an average position of one is the target. Otherwise, somewhere in the top four spots is ideal.

No more so than when this common average position glitch rears its head, giving marketers the impression that their ad has taken up residence somewhere above the top spot in Google’s search engine results page positions (SERPs).

This illusory Bermuda triangle is not some promised land in paid advertising. It is merely the result of a slight flaw in the average position calculation used by Google Ads.

We’ll give you an overview of the issue here and explain how we solve the average position glitch in PPCexpo.

According to Google, the average position is “your ad’s position relative to those of other advertisers”, which essentially tells us where our ads are displayed on the Google Search Network.

There are seven ad positions on Google’s SERPs, with position #1 being the top position and position #7 being the lowest. Average position is the mean average of all positions that your ad has been displayed in.

The position that your ad appears in is directly related to the Ad rank it receives during the auction. The Ad rank is a product of several factors, including the keyword quality score and your maximum cost-per-click (CPC) bid.

Once this Ad rank is determined, your ad can be placed in any position, between 1 and 7 on the front page, or even lower on secondary pages if the Ad rank is lower.

Imagine that a particular user search query triggers your ad 100 times in eight hours. Out of those 100 impressions, your ad is displayed in an array of positions as follows:

• Position #1 – 10
• Position #2 – 12
• Position #3 – 45
• Position #4 – 15
• Position #5 – 18
• Total Impressions = 100

We can use the average position calculation below to determine the average position of your Ad for these 100 impressions.

AVG POSITION = (AD POSITION * TOTAL AD IMPRESSIONS) ÷ TOTAL IMPRESSIONS

{(1*10) + (2*12) + (3*45) + (4*15) + (5*18)}/100 = 3.19 = ~3.2

From this formula, we can see that the average position for this ad over the last eight hours is 3.2.

As you can see from the calculation above, the average position does not have to be a solid integer. In fact, rather than simply being 1 or 2, it is much more likely to be a decimal number such as the 3.2 figure from the example. This tells us that the ad earned the most impressions in ad position #3.

More importantly, we can also learn that it is impossible to end up with an average position of less than one when using that formula. To calculate an average position value of less than one is erroneous.

If an ad is being displayed once at position #1, its impression value would be “1”, as proven by the formula:

AVG POSITION = (AD POSITION * AD IMPRESSIONS) ÷ TOTAL IMPRESSIONS

1= {(1*1)}/1

Let’s calculate the average position for Ad position 8

8= {(8*1)}/1

As you can see, the formula will always return an average position that is greater than 1.

But what happens when Google Ads reports that your ad’s average position is less than one? What does that mean?

The marketing giant has advised that in such instances, you should consider the value to be an anomaly in your data. It occurs when the data used in the calculation is inaccurate or incomplete.

PPC advertising can be confusing enough as it is without anomalies complicating your data analysis. However, this issue is one that marketers should prepare for. While it’s easy enough to dismiss it if you ever encounter the problem, there is actually a better way to make sure the average position glitch doesn’t affect your analysis or reporting.

Using PPCexpo to help manage your advertising campaigns makes sense for plenty of reasons and tackling the average position glitch is just another benefit.

Our reports don’t include any data that refers to an average position of less than one. This is made possible by the use of average position buckets.

There is a ‘bucket’ for each ad position from position #1 to position #8, and then a Position #8+ bucket that houses the data for any scenario where the ad is displayed on lower pages in SERP.

Many marketers are under the illusion that they should be targeting an average position of #1 all the time. Therefore, when they see an average position of less than one, they may even be fooled into believing their ad is outperforming even the most successful competing ads.

The reality is that an average position of #1 isn’t always good news. There are many other factors to consider, such as your keyword match types, CPC metric, and your conversion rate.

If your average position is always #1, it may be coming at a high CPC cost, which renders your return on investment (ROI) far less impressive than a high conversion rate suggests.

It’s best to aim for a good ROI on your advertising spending, even if it means you sacrifice the top spot. An average position of #2 or #3 can still deliver a high click-through rate and plenty of impressions, but at a lower CPC, which is much better in the long-run.

Finding an impossibly low average position metric is nothing new in PPC advertising. While you shouldn’t read too deeply into it, it is worth considering what an average position glitch is telling you about your campaign data.

Not only can you solve an average position glitch in PPCexpo, but you can ensure that your data analytics and reports present the cold, hard truths about your campaign.

With more accurate, reliable data on hand, you can make the right decisions to improve your average position and ensure your ads are optimized to reach more viewers.