Information Architecture

Information Architecture

Author

Louis Rosenfold, Peter Morville and Jorge Arango

Year
2015
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Review

This book blew the doors off a world I knew nothing about. It helped me become a better product manager. I gained a stronger understanding of taxonomy, navigation and search. Many of the concepts here will be familiar to engineers, this book brought be closer to that discipline and enabled me to have conversations at a much deeper level. I believe that Product Managers should read around their discipline, a lot of the magic happens at the edges and this is a good place to start.

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Key Takeaways

The 20% that gave me 80% of the value.

  1. Information Architecture is the art and science of shaping products to support usability, find-ability and understanding. Increasing amounts of content, metadata and complexity are making it increasingly important.
  2. Information ecology is interested in the intersection of users, context and content
    • Context: Business goals, funding, politics, culture, technology, resources and constraints
    • Content: Data objects of different types & their metadata
    • Users: Audience, tasks, needs, information-seeking behaviour, user experience
  3. There are 4 main types of information seeking
    1. Known item seeking: You know what you're looking for. E.g. What's the population of London?
    2. Exploratory seeking: You don't know exactly what you're looking for, you need a few results to achieve your goal: What are the best restaurants in Kings Cross?
    3. Exhaustive Research: You want to see everything.
    4. Re-Finding: Finding information you've found before. Think 'pin to top' or 'favorite'.
  4. Information seeking behavior can include:
    • A combination of 'search', 'browse' and 'ask'
    • Search and browse are often used together. Users often only 'ask' when stuck
    • Berry picking behavior: users iterate their approach as information is revealed when interacting with the product
    • Pearl growing: users see content that resonates, and follow 'more like this' prompts (sideways?)
  5. IA helps create consistency and coherency. Even though content changes, and channels have different capabilities and limitations, users become familiar with semantic structures and become disorientated if they change.
  6. Components of information architecture:
    • Organisational Systems: how we organise information (by subject, chronology)
    • Navigation Systems: how we help users move through content (click hierarchy)
    • Search Systems: allow users to search content (executing a search against an index)
    • Labelling Systems: how we represent information (titles, abstracts, link)
  7. Information architecture can be determined top down (shaped by user journeys) or bottom up (shaped by the information/content structure)
  8. A single user action (like searching) can touch many IA decisions (query builders, indexing decisions, display decisions, search tradeoffs) which impact the user experience.
  9. Information Architecture is challenging. Language is ambiguous. Information can be diverse and seem unrelated. People see things differently. Company politics can get in the way.

Organisation Systems:

  1. Organisation schemes can be exact (alphabetical, geographical, chronological) or ambiguous (topic, task, audience specific, metaphorical, hybrids). Supermarkets use topic/task hybrids
    • Exact schemes are best for known-item searching. They're also easy to maintain and automate.
    • Ambiguous schemes are difficult to design and maintain. However, they're more useful for exploratory seeking, associated learning and serendipity.
      • Libraries offer author, title and subject schemes. Subjects are more popular because customers often don't know exactly what they're looking for.
  2. Hierarchies (Top Down) are typically mutually exclusive groups with parent-child relationships. They give users an overview of the information space and their place in it.
    • think about the tradeoff between exclusivity and inclusivity. It's hard to make ambiguous organisational schemes mutually exclusive. Hierarchies that cross list items are called polyhierarchical.
    • think about balance between breadth and depth. Breadth refers to options per level. Depth refers to number of levels. Avoid both 'narrow and deep' and 'broad and shallow'. Don't overwhelm the user with options or make them click through lots of levels. If in doubt, start with broad and shallow, levels can be added as content increases.
  3. Databases (Bottom up). Without defining a hierarchy, its still possible to leverage the metadata we have on information objects to make them findable. Using tags to create powerful searching, browsing, filtering and dynamic linking. This approach is scalable, and best paired with a more traditional top-down approach
  4. Hypertext (Sideways) Links are flexible and can be used creatively to make useful relationships between content, unlocking new pathways. However links don't provide the user with a sense of place, or help them understand the nature of the relationship. Used in isolation, they are confusing and overwhelming, but can be a powerful supplement to a more traditional hierarchy
  5. Social classification (Sideways)Users generate content and tag it (in text or tag fields) creating 'folksonomies'. Public tags allow users to move freely between objects (that wouldn't otherwise be grouped together) enabling discovery. Large numbers of engaged people are needed to make tagging work.

Navigation Systems:

  1. Labels are representations of concepts. 'Contact us' triggers a powerful understanding of the information that likely sits behind it (without us thinking).
    • Spoken language is essentially a labelling system for concepts and things
    • Its harder to convey meaning through products than conversation, its one way, you have no live feedback
    • Use language familiar to your users, that makes sense in context and alongside content.
  2. Create better labels:
    • Labels are hard because language is ambiguous (synonyms, homonyms, context). Content, users and context affect the perception of a labels meaning.
    • Apply a consistent labelling system across the product. Style, presentation, syntax, granularity, comprehensiveness, audience comprehension levels (medical PHDs?)
    • Audit labels in a single document. Audit comparable products and competitors. Adopt industry standard topologies or controlled vocabularies.
    • For inspiration: look at your content, look at your search terms, ask authors, ask user advocates, test with users (card sorting, free listing). Label tomorrows product features now, they should impact today's choices.
    • Links mean different things to different people. They require trust to action. Surround them with clear context. Make it clear where the link takes the user. Provide guidelines to authors.
    • Headings describe content that follows them. Headings establish hierarchy within content. Hierarchy between headings is established with styling. Users follow reading paths dictated by heading hierarchy
    • Navigation labels are best when repeated and kept consistent throughout the environment. Avoid using the same label for two different things.
    • Icons are aesthetically pleasing, but users have a limited icon vocabulary. Text labels are more clear. If you don't have space, use icons, but only common ones.
  3. Global Navigation: shown on every page, shows the user where they are, gives them quick access to major tasks
  4. Local Navigation: shows what's nearby (hierarchy levels, steps), compliments global
  5. Contextual navigation: shows what's related to what's here. Create new connections and pathways. Where does the user want to go next?
  6. Supplemental navigation: Only important in large information environments. Used as a backup to main navigation
    • Sitemaps reinforce information hierarchy, good for known-item seeking. Strip out content and provide access.
    • Indexes: alphabetical keywords. Granularity must be sensible. Consider term rotation "Car hire" and "Hire car"
    • Guides: best for new users, or sneak peaks of paid products. Keep them short, allow users to exit, keep navigation consistent, allow users to step forward and backward.
  7. Configurators used for complex decision trees. Show the impact of each choice as you go (change product images, price, shipping dates etc)
  8. Search: Users use their own terms. Allows specificity. However, there's ambiguity in language which causes problems.
  9. Personalisation is guessing what the user wants (based on behaviour, needs). Customisation lets the user specify what they want (presentation, navigation, content). Both are hard to do well. Users don't spend much time customising. Customising only applies to power users who return frequently, and even they don't always know what's best for them.
  10. Social: when actions of related individuals has value. Feed are ordered based on social graph. Good for discovery. Dynamic social navigation systems are becoming increasingly complex and useful. Beware the echo chamber!
  11. Navigation tips:
    • Innovate selectively. Use interaction norms and platform conventions.
    • Let users know they've arrived (brand identity). Provide a sense of where they are (information hierarchy) and what they can do (actions). Stress test it.
    • Balance the flexibility of movement, with user overwhelm from navigational clutter
    • Plan how your global, local and contextual navigation work together

Search Systems:

  1. Search often has a high engineering cost, so be sure you need it. Don't build search because navigation is broken, fix that first.
  2. Search works great when there's lots of content, or content is dynamic or fragmented.
  3. Search logs help you understand what your users want
  4. Indexing most things allows for richer results. Exclude documents or content components that users don't need to see, or that will hinder search results (e.g reviews of restaurants could mention competitors and confuse results).
  5. Only use search zones when users have shown an interest in the segment, would expect results only from that segment and when segmenting would improve results.
    • Segment ideas: content type, audience, roles, subject, topic, chronology, geography, author or business unit
    • Tradeoff between improving results and introducing complexity. Many users will ignore search zones.

3. There's a tradeoff between precision and recall.

  • Precision is what proportion of the records returned were useful.
  • Recall is what proportion of the useful results in the system were returned
  • Often, you can only increase recall at the expense of precision (and vice versa).
  • Balance knowing your user needs, are they 'known-item seeking', 'exploratory seeking' or doing 'exhaustive research'

4. Use query builders to increase the effectiveness of queries

  • Spell checkers correct spelling before returning results
  • Phonetic tools (soundex) expand queries like 'Smith' to include "Smyth'.
  • Stemming tools retrieve documents by finding words that use the same stem
  • Natural language processing tools take 'how to' and 'who is' and use that to narrow retrieval results.
  • Controlled vocabularies and thesauri leverage semantic nature of a query by including synonyms within the query

5. What to show in search results:

  • Pick content components based on user needs.
  • Known-item searches benefit from less content and more results. Exploratory seeking benefits from more content (abstracts)
  • Consider providing user choice for result density and display type (list, map)
  • Use pagination but don't expect users to venture past the first page.
  • If the documents you search over are flat (no headings) show the sentences that surround your search term for context
  • Show the search query & the number of results, helping users iterate on searches
  • Including key call to actions in search results (e.g. 'Get' in AppStore)
  • Consider allowing users to save searches or 'pin' specific results to read later
  • Explain if you've edited the search term
  • Explain where the results came from if you've done something non-obvious
  • Integrate searching with browsing: look for opportunities to connect your search and browse experience

6. Default to ranking results by relevance. Relevancy ranking is often a combination of:

  • how many of the query terms appear in the doc
  • how frequently they appear in the doc
  • how close together they are
  • where the terms occur (title or body)
  • the popularity of the document.
    • popularity should play a larger role if you have the data (Google · PageRank)

7. When to deviate from ranking by relevance:

  • Alphabetically for names
  • Chronologically for time bound results (news, tweets)
  • Allow sorting if it helps with a task (sort by price)
  • Human editorial
  • Ads
  • Rankings / Reviews (sort best first)
  • Consider grouping results by type

8. Consider query language support and advanced search interfaces if you have a captive audience of frequent power users.

9. Keep search limited to a single box if you can, and keep it away from other boxes

10. AutoComplete and AutoSuggest help identify potential matches based on partial or incomplete information. Can give users hints as to how the system is structured, help them iterate on searches

Theasuri, Controlled Vocabularies, and Metadata

  1. Metadata describes the thing. Examples include: means of creation, purpose, time & date of creation, author, location, standards used, tags
    • tags are used to describe documents, pages, images, software, video and audio files and other content objects for the purposes of improved navigation and retrieval
    • HTML has a <meta> tag, which authors can stuff with keywords for search engines
  2. Metadata-driven systems support powerful navigation and discovery environments. In large metadata-driven products, controlled vocabularies act as the glue that holds the system together.
  3. Types of controlled vocabularies:
    1. Synonym Ring: connects a set of words that are defined as equivalent for the purposes of retrieval.
    2. Authority Files: List of preferred terms or accepted variables. They are synonym rings in which one term has been defined as the preferred term
    3. Classification schemes: They are authority files, but also introduce the concept of a term hierarchy.
      • Example: The Dewey Decimal Classification {1876} (DDC) book classification used in libraries. Starts with 10 master categories, and has others underneath
      • Netflix classification scheme helps movie discovery. Macro genres (Drama, comedy), micro genres (based on real life) and micro tags (#happyEnding) that are used to inform the categorisation process
    4. Theasuri: All of the above and more. A controlled vocabulary in which equivalence, hierarchical and associative relationships are identified for purposes of improved retrieval
      • Each preferred term becomes the centre:
        • Equivalence = manages synonyms
        • Hierarchical = classification into categories and sub categories
        • Associative = meaningful connections that aren't handled by hierarchical or equivalence relationships
    5. Implementation Tips:
      • you may confuse users, if you use these in search results without explaining it
      • you may reduce the relevance of search results (precision and recall tradeoff)
      • Synonym rings can dramatically improve recall (from 20-80%)
      • A good tradeoff might be to use synonym ring recall by default, but order exact matches towards the top
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Deep Summary

Longer form notes, typically condensed, reworded and de-duplicated.

1) Problems that IA addresses
2) Defining IA
3) Design for finding
4) Design for understanding

Basic Principles of IA

5) Anatomy of IA
6) Organisation Systems
7) Labeling Systems
8) Navigation Systems
9) Search Systems
10) Theasuri, Controlled Vocabularies, and Metadata

Getting IA Done

11) Research
12) Strategy
13) Design and Documentation