Long Tail: Calculating Total Search Exposure

Examine the long tail traffic associated with the targeted keywords. Calculate the long tail ratio, leading to an estimate of the expected number of search exposure.
August 27, 2012

Overview: Long Tail Traffic

While our analyses seemingly concentrate on a handful of individual high volume keywords, the far more attractive target are the associated thousands of obscure long tail keyword searches. Searches in most industries are not concentrated in a single keyword – rather it is distributed across a vast array of variations. But, given that there are so many targets and each target represents so little traffic – we cannot optimize for these long tail keywords directly. Instead we usually optimize for the associated high volume keywords – and with little extra work we get the long tail for ‘free.’

The phrase long tail describes these keywords where search volume is distributed among a large number of search terms, each with only a small share of search volume. Conversely, short tail keywords have search volume concentrated in relatively few keywords. For example, searches for bowling are highly fragmented (long tail). While there are over 4 million monthly searches every month that contain the word bowling, only 90,000 (2%) are for the exact word bowling. Those 2 millions searches containing plumber are composed of hundreds of thousands of low volume searches like bowling parties (30), bowling shoe (260) and bowling alleys in Dallas (58).

In contrast, other keywords are more concentrated (short tail). For example, of the 60,000 broad searches associated with the word unicycle, 12,000 (20%) are for the exact word unicycle. But note, even for phrases we describe as short tail, still the vast majority of traffic lies in the variations rather than the primary keyword.

The length of the tail is a useful metric because it shows how much additional traffic is available if you optimize for keywords. As we previously mentioned, if you optimize for a long tailed keyword like “bowling”, and win the keyword, you are likely to pick up some of the long tail traffic with little or no extra effort.

As a rule of thumb, keywords with long tail search volume are more attractive, as you will get more traffic from them than if the keyword did not have the long tail. In this section we discuss how to measure the long tailedness of a keyword (long tail factor), and how to use that factor to estimate the number of search exposure that will be created when you win a keyword.

Long Tail Factor

The long tail factor measures the degree to which a keyword is long tail (long tailedness). We use this factor to help predict the amount of additional search exposure that will be generated as a result of winning a primary keyword in the google rankings.

Calculate the long tail factor for each individual keyword by dividing the number of broad-match searches by the number of exact-match searches (you should have these two data points from your search volume research).

Formula 1 – Long Tail Factor Formula.

Long Tail Factor Formula

Using the unicycle example above, the Long Tail Factor is 4.

Long Tail Factor Example

A higher Long Tail Factor suggests searches for a keyword are spread out among many variations of the keyword phrase. A low factor indicates that the search is concentrated in the exact keyword.

Using our keyword analysis spreadsheet, the Long Tail Factor will be automatically calculated for each keyword in the Long Tail Factor column on the Traffic Analysis tab.

Search Exposure

We can use the Long Tail Factor to estimate the total amount of search traffic that a keyword is likely to generate once you have won the #1 position. The #1 position for a keyword phrase results in exposure to all the searches for that exact phrase but also to a fraction of the long-tail traffic – even if you have done little to optimize for the long tail.

Note, this calculation only estimates the number of searchers that will be exposed to your search listing, not the number of searchers that will actually click-through to your site and become visitors. We cover the click-through rate and how to use it to calculate the amount of on-site traffic here.

To calculate the total search traffic exposure, use the following formula:

Formula 2 – Search Exposure Formula.

Search Exposure Formula

For example, returning to our unicycle example from the previous section, if we ranked #1 for “unicycle”, we would expect total search exposure to be 260,000 searches per year.

Search Factor Example

If you are using the Keyword Analysis Spreadsheet, the Total Search Exposure will be automatically calculated for each keyword in the Total Search Exposure column on the Traffic Analysis worksheet.

Frequently Asked Questions

Question: The numbers are only based on Google, what about traffic from other search engines like Google and Bing?
Answer: We use traffic numbers from Google, because it is the primary source of search traffic in most markets. The search exposure equation takes into account that search traffic also comes from other sources, and other factors such as traffic from mobile search.

Question: When do the numbers deviate?
Answer: The search exposure numbers assume that you have at least 500 words of keyword rich text on the page to help you attract the long tail traffic. If the target webpage has little traffic, you need to reduce the search exposure estimates downward, closer to the just the exact match traffic numbers.


The Long Tail – Chris Anderson’s first coined the expression, Long Tail to describe the phenomenon of increasing fragmentation. An interesting read. The prior link is to original article, see also the subsequent Long Tail Book and wikipedia on Long Tail.

{ 2 comments… read them below or add one }

David October 18, 2012 at 7:35 am

Quick question if I may… Where do you get the ’5′ from in the Total Search Exposure formula in the SEO Keyword Strategy ebook ? It seems to be a random figure?


Gajan October 18, 2012 at 9:48 am

Hi David,

In the search exposure formula we are trying to generate an estimate of the amount of traffic you will get when you win a keyword. When you win a keyword like ‘seaweed snacks’ as well as getting search exposure for searches for ‘seaweed snacks’, you also get exposure in similar long-tail searches such as ‘organic seaweed snacks’, and ‘seaweed chips’ even though you did not deliberately optimize for these variations.

In most cases this collateral traffic you pick up ends up being a more significant source of traffic than exact match for the exact keyword you were optimizing for.

To get a working estimate for amount of traffic you can expect from these long-tail variations we looked at a data sets of SEO campaigns we have run at the amount of additional traffic generated from non-targeted keywords and found it was correleated with the amount of broad-match traffic. We ran a regression analysis, giving us the ’5′ on the denominator.

As always, these are estimates and you need to use judgment when applying the formulas. In a less competitive setting and where you have an information (text) rich site I would expect the formula underpredicts Total Search Exposure. And Where you are in a more competitive space and where you have a site with less on-page text, the formula is going to overestimate the search exposure.


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