The purpose of our site search is to assist visitors acquire the knowledge they need as efficiently as possible. Unlike internet search engines, we only have to serve results for our 'family' of sites. However, with more than 150,000 pages, this is still a complicated task, made even more challenging by the distributed authorship model that we live with. In order to do search better we should focus our efforts in four main areas:
Context: We need to know more about our users, both as groups and as individuals, and their needs. Only then can we please most people most of the time. The starting point (and easiest to do) is reflect the site location into the search experience. This would mean a different result layout (or even different results) for a user searching from 'Future Students' than one searching from 'Research'. Taking this further, we could the type of visitor (in broad groups such as international/domestic) or their preferences (maybe by drawing on cookie information)..
Content: Search needs must feature in our content work (from strategy, through training and in writing) if we are to make real improvements to the relevance of search results. We must index and enrich the right content (not all of it), manage our recommend results, add promoted results for common queries (best bets), improve the visual catalog of the most important items (richer snippets), and eliminate junk from the default search experience.
Metadata: We need more and better structured information about our content in order to substantively improve search result relevancy.
UX: We need well researched, designed and built interfaces, with user feedback to enable continuous improvement. How come we don't ask where search found what the user was looking for? We should be continually gathering feedback, analysing, and refining our search experience and index.Look regularly at our top queries, abandoned queries and zero result queries.
Collections
Funnelback allows us to define collection, document/page/file groups with a common thread. We can then use these collections in search to better target and improve relevance, without having to micro-manage each document. For example, subject areas and UG degrees could be two collections, in turn grouped into a meta-collection 'UG study things'. We could search only over this metacollection on the KYM landing page or an UG study hub. So, combined with some site context information or a user-cookie value, we can improve relevancy without expensive content work.
Evaluation of search
Search fill its purpose when it deliver the right information, is fast about it and always available. To satisfy these requirements, the function of search is to be tested regularly and tests should be documented in test plans. Below are some of the tests that are appropriate:
- Search loads quickly, tested with Google Pagespeed Insights, with a minimum of 80/100.
- The response time of a query should be about 0.1 seconds, but never longer than 1 second, measured at the user interface.
- Search will be available 24/7 (around the clock seven days a week). Monitored by, for instance, Pingdom or Uptimerobot.
- Size of search indexes. Among other things, to see if more or fewer documents are indexed, which can provide warning signs in advance, help being proactive.
- Search’s user interfaces are accessible, tested with the W3C Validator.
- Search’s user interfaces are usable, tested against webbriktlinjer.seand W3C:s WCAG 2.0 at level AA.
- Survey the satisfaction of users.
- Reviewing search statistics and/or performing search analytics, to gain insight into how users are searching.
Insights
- We need to acknowledge site location/context for the search far, far more than presently, when most things default to a whole-of-site search.
- Collections are powerful, not only for grouping results, but also to power contextual searching.
- We need to internationalise more of the key pages, then use the key cookie settings to display the correct 'version'.
Questions
- Should we continue to use the 'promoted results' for courses, or transition to subjects? Or degrees?
- Should we be adding key words to subjects and/or subject areas? Can a subject area 'inherit' the keywords of it's component subjects?
- How do we strike a balance between what the user wants to see and what we want the user to see?
https://webstrategyforeveryone.com/example-enterprise-search-strategy/
One helpful model is to consider four different modes used when searching for information
- Known knowledge: Those searching for what is already known is easy to service because the user knows what they want, can express this well and has an idea of where to start looking. E.g. I want to learn my major requirements for the second and third year of my UG degree.
- Exploring: User has an idea of what they want to know, but may have difficulty expressing it, or cannot use the correct terms. The user often know when they have found the right content, but has no knowledge if the result is sufficient. E.g. I want to complete part of my study overseas.
- Do not know what they need: Users often do not know exactly what they need to know. They may believe that they need to know one thing, when in reality it is something else. Sometimes, they visit an information source without any specific purpose. E.g. I am looking for something to study, but don;t really know what I should do.
- Retrieve: User is looking for information that they have prior knowledge of and maybe can even remember where they saw it recently, which source of information it were or they have an idea where to find the content.
http://www.galaxyconsulting.net/images/White_Paper_April_2014.pdf
- Define specific objectives for specific search 'tools'
- Who is searching?
- What categories of information are they looking for?
- What are they likely to do with the information when they find it?
- Define logical types of searches
- People search
- Product search
- Customer search
- Define the desired scope and inventory repositories
https://www.clearbox.co.uk/enterprise-search-we-need-some-answers-on-a-card/