**Frequency** is the % of times Adthena sees a competitor when conducting our searches.

Therefore, if for example Adthena search for for "black dress" 100 times and sees competitor *retail-brand.com* showing an advert on 50 of those occasions, then *retail-brand.com* will have a **frequency** = 50% on that specific term.

If *retail-brand.com* is appearing on multiple terms, then the aforementioned % will be weighted according to the average monthly search volume of each term.

Using the two search terms "black dress" and "black cocktail dress", which Google tells us have an average search volume of say 3,000 searches per month and 300 searches per month.

For example, *retail-brand.com* appear on "black dress" 100% of the time and "black cocktail dress" 50% of the time. Rather than showing a resulting average frequency of 75%, this example scenario will be weighted based on the fact that "black dress" is searched for 10x more often, so the **frequency** will be 95%.

Calculation: 95.45% = (100% x 3,000 + 50% x 300) / (3000 + 300)

**Estimated Impressions **is the sum of each search terms **Frequency** x average monthly search volume [from Google]

Calculation: 3,150 = (100% x 3,000 + 50% x 300)

Note however that **Frequency** only includes the terms that a competitor does appear on.

**Share of Impressions** is the estimated impressions on a group of terms / the total available impressions over the selected period for all terms included in the filters, even those that a competitor has not appeared on.

In the simple example above, where there were only two terms and the competitor appeared on both, the **Share of Impressions** will also be 95%. If we include a third term that they competitor has not appeared on then then **Frequency** will remain the same, but the **Share of Impressions** will drop (as there were more impressions available for them to appear on).

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