Search design patterns

10 major search design patterns:

• Autocomplete/suggestions
• Best (results) first: Relevance, Date, Popularity, Format, Personalisation, Diversity
• Federated search (simultaneous search of different databases)
• Faceted navigation
• Advanced search
• Personalisation
• Pagination
• Structured results
• Actionable results
• Unified discovery

Morville and Callender (2010). p: 81-130

Search Manifesto

1. Search is a problem too big to ignore.
2. Browsing doesn’t scale, even onm an iphone.
3. Size matters. Linear growth compels a step change in decision.
4. Simple, fast, and relevant are table stakes.
5. One size won’t fit all. Search must adapt to context.
6. Search is iterative, interactive, social, and multisensory.
7. Increments aren’t enough. Even Google must innovate or die.
8. It’s not just about findability. It’s not just about the Web.
9. The challenge is radically multidisciplinary.
10. We must engage engineers and executives in design.
11. We can learn from the past. Library science is still relevant.
12. We can learn from behavior. Interaction design affords actionable results.
13. We can learn from one user. Analytics is enriched by ethnography.
14. Some patterns, we should study and reuse.
15. Some patterns, we should break like a bad habit.
16. Search is a complex adaptive system.
17. Emergence, cocreation, and self-organisation are in play.
18. To discover the seeds of change, go outside.
19. In science, fiction, and search, the map invents the territory (Note from somewhere elsein the book: maps hide more than they reveal…)
20. The future isn’t just unwritten – it’s unsearched.

Morville and Callender (2010), p.20

David Ellis: Behavioural model of information seeking

Six primary behaviour patterns in information seeking:

1. Starting: identifying relevant sources of interest
2. Chaining: following and connecting new leads in an initial source
3. Browsing: scanning content of identified sourcves for subject affinity
4. Differentiating: filtering and assessing sources fior usefulness
5. Monitoring: keeping abreasts of developments in a given subject area
6. Extracting: systematically working through a given source for material of interest

David Ellis, cited in Kalbach (2007, p.26)

Search results best practices

For easy reference, here is a list of some of the best practices that have been gleaned from different search results pages:

• User should have easy access to the search box for follow-up searches
• Where possible, search terms should be clearly indicated at the top, and in context in the results
• Related sponsored links can be included below the search box, near the bottom, or on the right
• Titles should be clickable and clearly differentiated from details
• Visited links should be indicated
• Pagination units should be visibly block-shaped and have a hover effect, to easily differentiate from one another
• Related products, tags, or keywords should be displayed in a non-obtrusive section
• E-Commerce sites should allow the “view” to be toggled between “list” and “grid”
• Advanced search options should be easily accessible
• Should allow re-sorting or filtering of results
• Where possible, results pages should have RSS feeds or “subscribe” options
• For complex interfaces, clear, easy-to-access search tips or instructions should be provided
• Sorting and Filters should be JavaScript or Ajax-driven, where possible
• Popularity or star-ratings should be shown for individual results
• Include an option to increase the number of results per page
• To monitor future improvements, request feedback from users after searches are conducted
• If results span different sections of the website, indicate this by sub-headings or other dividers

Louis Lazaris: Search Results Design: Best Practices and Design Patterns

Faceted Search

1. Decide on your filter value-selection paradigm—either drill-down or parallel selection.
2. Provide an obvious and consistent way to undo filter selection.
3. Always make all filters easily available.
4. At every step in the search workflow, display only filter values that correspond to the available items, or inventory.
5. Provide filter values that encompass all items, or the complete inventory.

G. Nudelman: Best Practices for Designing Faceted Search Filters

Confusion around sorting and filtering lists

“… many of the participants [in a usability study] said, “I am filtering by price,” while manipulating [the] Sort By control. After observing this phenomenon numerous times, it became clear to me that this was not merely a matter of a simple confusion of terms between filtering and sorting. Instead, it revealed a strong mental model of filtering by sorting that blurred the difference between these two modes of search results’ refinement.”

Greg Nudelman: The Mystery of Filtering by Sorting

SERP (design of search results page)

1. #1-guideline: mimic SERPs on major Web search engimnes
2. no need to number results
3. start wth a clickable headline
4. you might want to add URL or identification of destination (?) at the
   end of the entry
5. date of up-date

From: Nielsen, J. and Loranger, H. (2006), Prioritizing Web Usability, Berkeley, CA.: New Riders

site-search vs. web-search

Why should site-search perform better than web-search
1. smaller set of pages
2. better handle on user’s intent
3. prioritizing of documents is possible
4. older documents can get a lower priority
5. access to meta-data
6. controlled vocabulary
7. you can write summaries in your own words
8. no spammers

From: Nielsen, J. and Loranger, H. (2006), Prioritizing Web Usability, Berkeley, CA.: New Riders, p.139-140

Search patterns (Morville)

1. Behaviour Patterns
   1. narrowing results down e.g. by adding search terms
   2. browsing
   3. ‘pearl-growing’: picking one document and use metadata (author,
      links etc.) to expand on results
2. Design Patterns
   1. Best Bets for popular search terms
   2. Federated Search (?)
   3. Faceted navigation as means of narrowing down results
   4. Auto suggest
   5. Structured results
   6. Social search (Using ocial data for improvement of search results, e.g.
      popularity)
   7. Media Search
   8. Mobile Search

Source: P. Morville, IA summit 2008 http://www.iasummit.org/proceedings/2008/search_patterns