{"id":700,"date":"2021-12-15T10:00:00","date_gmt":"2021-12-15T10:00:00","guid":{"rendered":"https:\/\/blogs.york.ac.uk\/marketing\/?p=700"},"modified":"2021-12-10T09:45:30","modified_gmt":"2021-12-10T09:45:30","slug":"getting-a-handle-on-site-search","status":"publish","type":"post","link":"https:\/\/blogs.york.ac.uk\/communications\/2021\/12\/15\/getting-a-handle-on-site-search\/","title":{"rendered":"Getting a handle on site search"},"content":{"rendered":"\n

Have you ever visited a website looking for a specific piece of information; maybe a swimming pool timetable, or a specific recipe? <\/p>\n\n\n\n

Have you ever used a search function within the website in order to do this?<\/p>\n\n\n\n

If so, you have been a \u2018user\u2019 engaging with \u2018site search\u2019. <\/p>\n\n\n\n\n\n\n\n

We get a significant number of searches every month across york.ac.uk<\/a> for information ranging from accommodation to fees, timetables to departments. <\/p>\n\n\n\n

\"Website
Site search bar on york.ac.uk<\/figcaption><\/figure><\/div>\n\n\n\n

We use Funnelback<\/a> to facilitate site search which contains our web content in collections and, through both manual and automated configuration, presents the most appropriate results to search terms. <\/p>\n\n\n\n

Getting irrelevant results from these searches can result in a negative user experience, something we\u2019re keen to avoid.<\/p>\n\n\n\n

So, why do we need to get a handle on this?<\/h2>\n\n\n\n

Over time additions or changes to our collections result in \u2018experience rot\u2019. This is a slow deterioration of user experience as our search function increasingly fails to meet their needs. <\/p>\n\n\n\n

Most of the changes we make in Funnelback are reactive, responding to requests such as adding or modifying promoted results (best bets), or removing results that are no longer relevant. <\/p>\n\n\n\n

The reactive nature of this work meant that we had no strategy or process in place to optimise our search function and improve results.<\/p>\n\n\n\n

How can we optimise our site search?<\/h2>\n\n\n\n

Preventing the deterioration of results was at the heart of getting a handle on search results; shifting the focus away from problem solving to problem prevention. <\/p>\n\n\n\n

The first step of this was to properly understand the current state of our site search.<\/p>\n\n\n\n

Step 1 – Quantifying our search experience<\/h3>\n\n\n\n

Quantifying an experience is typically a challenging undertaking. A majority of our site search feedback is both anecdotal and emotive with specific failures in search results causing user frustration which sometimes gets fed back to the relevant team. <\/p>\n\n\n\n

However, successful searches are rarely commented on and we had no process in place of assessing search performance outside of user experience case studies. <\/p>\n\n\n\n

Utilising Louis Rosenfeld\u2019s methodology for \u2018Measuring the Unmeasurable\u2019 as outlined in his book, \u2018Search analytics for your Site<\/em>\u2019, I undertook a process of quantifying and measuring site search performance. <\/p>\n\n\n\n

Identifying objective \u2018best results\u2019 for our top search terms, provided by Google Analytics, I was able to set benchmarks for our site search relevancy and precision. <\/p>\n\n\n\n

Being a niche piece of work, this didn\u2019t provide a metric by which we could compare ourselves to competitor institutions. Instead, we now had a better, more objective, understanding of our site search performance and a means of measuring any improvements resulting from configuration changes. <\/p>\n\n\n\n

Step 2 – Carrying out configuration changes<\/h3>\n\n\n\n

I focused on the following configuration settings within Funnelback: <\/p>\n\n\n\n

Best bets:<\/h4>\n\n\n\n
\"Screenshot
Example of a best bet appearing when \u2018politics\u2019 is searched.<\/em><\/figcaption><\/figure><\/div>\n\n\n\n

These are Funnelback\u2019s promoted results and appear highlighted at the top of search results. <\/p>\n\n\n\n

Best bets can be created for important content that needs promoting in a timely manner. However, their relevance can expire, or their destination URL may change, and we had no process of determining which best bets needed updating or removing. <\/p>\n\n\n\n

Importing a list of our best bet destination URLs into https:\/\/httpstatus.io\/<\/a> meant I could identify those with redirects and update them accordingly. It also allowed for a sense check of live URLs meaning specific, outdated ones could be deleted. <\/p>\n\n\n\n

Search refinements:<\/h4>\n\n\n\n

This is a key site search metric reported in Google Analytics. It\u2019s the rate at which a search term is amended and re-entered. It can indicate that users did not find what they were looking for in their initial search and so had to try again, which isn’t an ideal user experience. <\/p>\n\n\n\n

As search refinements are most commonly the result of a misspelling, the best solution is to input a synonym telling Funnelback to return the results that would have been shown, had the search been entered correctly. For example: <\/p>\n\n\n\n

\"Screenshot
Screenshot of ‘accommodation’ synonyms impacting search results<\/figcaption><\/figure><\/div>\n\n\n\n

By adding \u2018acomodation\u2019 as a synonym for \u2018accommodation\u2019 the user experience is preserved and they can more quickly reach relevant information. We did this for all common misspellings appearing in our Google Analytics reports.<\/p>\n\n\n\n

Exclude and Include patterns:<\/h4>\n\n\n\n

The content we include in, or exclude from, our search results is managed via Include and Exclude patterns. <\/p>\n\n\n\n

I reviewed what\u2019s included in these lists to ensure any new domains are included in search if necessary, and removing legacy exclusions of sites which no longer exist. <\/p>\n\n\n\n

For example, we no longer needed to include www.capanina.org\/<\/a> so this was removed from the Include list, I also added utm_campaign parameters to the Exclude patterns to ensure campaign pages were kept out of search results. <\/p>\n\n\n\n

This update helps to keep Funnelback up to date with relevant content as well as streamlining results by removing legacy domains. <\/p>\n\n\n\n

It was important to record the number of documents crawled by Funnelback so as to investigate any sudden increases which may slow site search down. I also listed everything excluded along with a brief description of its purpose to future-proof our exclusion rules. <\/p>\n\n\n\n

Tuning:<\/h4>\n\n\n\n

Funnelback tuning is \u201c…a process that can be used to determine which attributes of a document are indicative of relevance and adjust the ranking algorithm to match these attributes\u2026\u201d (Tuning search ranking docs – Squiz<\/a>)<\/p>\n\n\n\n

Adjusting tuning configuration requires search terms to be added with their best result. Funnelback then uses this information to adjust search result rankings accordingly, providing more accurate search results. <\/p>\n\n\n\n

I took the top search terms with the best result as identified in the benchmarking stage (step 1) and entered them into our tuning configuration. Funnelback predicted that this would have a positive impact on our results so the config changes were published. <\/p>\n\n\n\n

\"Predicted
Funnelback’s predicted improvement based on tuning data update.<\/figcaption><\/figure><\/div>\n\n\n\n

Step 3 – Test that configuration changes have helped<\/h3>\n\n\n\n

Checking it\u2019s worked! <\/p>\n\n\n\n

After updating best bets, adding to our synonym collection, reviewing Include and Exclude patterns and tuning our results, I undertook another round of precision analysis to determine if these changes had led to any measurable improvements.<\/p>\n\n\n\n

I saw that our search precision increased across the three main definitions of precision.<\/p>\n\n\n\n