Click Throughs in the Search Results

Google’s first pageview looks very crowded. In seeking to answer the searcher’s query as best they can, search engines are creating richer, more nuanced search result pages, with video, images, news and other kinds of information displayed along with links to the ranking sites. All this extra content has to go somewhere, and thus increases the competition for screen real estate.

The first spot for an organic result has always been the best, and the click through rate (CTR) certainly justifies this. The interesting question is where does this trend leave spots two through to ten? Is third still worth something? Can you be happy with being fourth on a competitive query, as the costs associated with ranking higher begin to scale upwards at an alarming rate? Just how bad is it once you fall below the fold, and where is this even happening?

The Personalised Search Nightmare

There is no single search engine result page (SERP) for any term. Assuming one person’s search experience is going to be the same as another’s is not a sustainable position. Previous behaviour on the part of the user as an individual, and users as a group defined by data-centre or location, all potentially affect what is shown. Recent news and updates need to be considered too in the fast updating post-caffeine world. You could build a model for an average SERP within a given audience, given access to enough information from a decent sample. This might give an indication of what is included in the SERP, and which results would be seen in the first pageview.

The Best Best Guess

There is an alternative to attempting to identify the most likely combination of organic sites, videos, news, places, snippets, images and paid ad units to appear to a given user for assessing the value of a position. Projected search volumes compared to visits can potentially shed light on the relative worth of a position between queries. For sites you personally manage, Google’s Webmaster Tools is a great source for this kind of data. Google is far from transparent with most published numbers relating to organic search, and the figures presented are by no means precise. But for a site with significant search visibility, there should be enough data to begin to make reasonable assumptions.

The graph at the start of this blog post was created for just this purpose. The data was taken from Google Webmaster Tools for a site that gets a reasonable amount of organic traffic. The actual data set used is for searches of over 100 reported impressions for terms with an average position of ten or less within a single geographic region (country is the most specific location available). The data at a glance indicates that once the average position is greater than two, CTR is rarely better than 25%. (The graph is available here via Impure.)

What to Ask Next?

The terms used in building this data set include brand queries, product queries and general searches. They cover transactional, navigational and informational behaviours and numerous specific geographic terms. There is a lot more that can be done from here to find interesting, actionable insights.

The search terms themselves are an important part of the data set, and so far under-utilised. The next step in examining the data could be to:

• Examine geographic queries:
  • As one data set
  • As individual locations
• Remove branded queries
• Examine product queries
• Examine news/information queries

Splitting the data by query potentially accounts for the effect of maps in the SERPs, visibility by Place listing, the effect of the query matching the brand or product on CTR, and CTR for informational searches.

The options for examining the effects of ranking, CTR and search type is dependent on the nature of the site in question and what its actual search visibility is. Looking closer at what content gets clicked in search versus position across different kinds of queries can give great insights into what content works. It will also reveal where a few well performing search types are hiding the gaps in a poorly performing SEO strategy.