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Weighted Avg Position

Weighted Avg. Position

Contents:

Weighted Avg. Position

We cover the average position metric in another guide; this guide looks specifically at how to aggregate average position across multiple campaigns, ad groups or products.

Depending on how your campaigns are structured you may have products targeted across multiple campaigns and ad groups and it may not be possible to see (in AdWords) the average position of ads across all of these areas / components. But knowing what the average position of ads is across multiple components is something many account managers will need to know at some point.

Why Use Weighted Average Position?

Unlike most other calculated metrics in AdWords such as Avg. CPC (Average Cost per Click), CTR (Click Through Rate), etc, there aren’t two metrics we can use to calculate the average position. Avg. CPC is simply the cost divided by the clicks; we can get this from or at any level in the account and easily calculate the metric.

Avg. Position however requires slightly more maths!
If we have three campaigns that all target a product, lets assume we have the following data:


Campaign

Impressions

Avg. Position

Campaign A

10,000

3.1

Campaign B

145,000

2.5

Campaign C

111,500

5.8

If we were to take an average of the average positions we would find that the average (mean) of 3.1, 2.5 & 5.8 is 3.8… But this does not take into consideration that ‘Campaign A’ only has 10K impressions and ‘Campaign B’ has 145K impressions. The campaign with more impressions will have a larger impact on the overall average position.

To simplify this, if we assume there are two groups of people:

Group A – 2 person – Average Age of 18

Group B – 150 People - Average Age of 30

If we followed this logic we would end up with an average age across both groups of 24, but one group has 150 people while the other only has 2 people, so clearly the average age is not 24. This is why we need to weight the data to take into account group size.

Calculating a Weighted Average Position

Calculating Average position is easily done in Excel, for example (using the data above) we would apply the following formulas:
Impressions x Average position

Apply the above formula to each row of data in a new column (see example below), where in each row we multiply the impressions by the average position for each row:


Campaign

Impressions

Avg. Position

Impr x Avg. Pos

Campaign A

10,000

3.1

31,000

Campaign B

145,000

2.5

362,500

Campaign C

111,500

5.8

646,700

Once we have done this we perform the following calculation:

(Sum of Impressions x Avg. Position) / sum of impressions

In the table below we have added in a row that sums (totals) the data in the above cells, so the sum of the impressions column is 266,500 and the sum of the ‘Impr x Avg. Pos’ column is 1,040,200:


Campaign

Impressions

Avg. Position

Impr x Avg. Pos

Campaign A

10,000

3.1

31,000

Campaign B

145,000

2.5

362,500

Campaign C

111,500

5.8

646,700

266,500

1,040,200

All we need to do is divide 1,040,200 by 266,500 to get 3.9, and 3.9 is the weighted average position across all the above campaigns.

This can be applied to any data set such as ad groups, keywords, ads, etc in the exact same way to get the weighted average position.

Post 2016 SERP Changes

In February 2016 Google changed the SERPS by removing the side ads from desktop and tablet searches and included a 4th ad at the top of the page, leaving just three more ads on the page under the organic results.

This had a significant impact on both SEO and SEM for many businesses and prompted an international effort by most SEMs to understand the average position of their ads in an attempt to anticipate the potential impact on account performance. Any ads outside of the top four positions were likely to have traffic reduced massively.

Hence understanding the weighted average position across multiple campaigns became very important from then on.

More Information

You may also be interested in reading our guides on the following topics:

  • Average Position
  • Avg. CPC
  • CTR 9Click Through Rate)

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