Applying Site Search Patterns to SEO/Paid Search

Site search can also provide a better understanding of search funnels, or keyword pathing. Search funnels are when you get a search followed by a second search. To get any sort of insights, though, we need to look at the data in aggregate.

A typical search, where we see a keyword followed by several related searches. This investigation may also prove valuable in discovering where your site search is breaking down. Searches followed by further searches usually indicate two things: the first is an unsuccessful search result, where refinement occurs because of irrelevant content, and the second is a successful result delivering content that requires further investigation. How can you distinguish the two? You can’t, really. This will require some good old-fashioned investigation by clicking and following the paths of your users. Then you will need to make some assumptions about what the users were looking for or saw.

Looking at site search patterns gives us a very unique insight into how users string words and terms together. You can capture searches in Google Analytics along with the other related terms that were searched. More advanced analytics tools can be adjusted to allow for tracking the search path or entire paths through a site. In analyzing your pathing reports, you should look for reports with multiple interactions with site search.

You should be able to track the original search term, the page clicked to, the following search term, and the following page clicked to. As you start to see these patterns, you can look for multiple instances of the same patterns occurring, and for any evolution in these patterns. This can help you identify pages that could be improved with the addition of cross-linkages, as well as potential problems with your content. People who search for a term and then repeat a search for a very similar term are very easily categorized as having gotten unsatisfactory search results.

Folks who do a broad search and then a more narrow version of that search give you a better idea of how search refinement may work. One trick you can use with Google Analytics to capture data on search refinement is to include a refinement option for users to select. For example, you can include a category drop-down in your site search, allowing users to select whether they’re looking for pages related to products, news, support, and so on. Google Analytics can capture that selection as well as the search term.

Capturing these refinements in site search can help you improve your landing pages for your site search users, but you may also be able to apply this data to your SEO or paid search campaigns. The caveat here is that site search users who are familiar with your products and are searching for a specific product may lean toward support, as they are already users (as opposed to people new to your products who may be looking to purchase). There is no easy answer here; your analytics tools will provide you with insights into the areas to target, but you will need to do some A/B or multivariate testing to validate what works for SEO/paid search traffic as opposed to site search users. There will always be some differences in usage, but there is still data that can correlate and provide indications as to what areas you should be focusing on. Utilize this data and apply where and when you can both what the analytics tell you and what your own investigations into the data and the user experience reveal.



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