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An Introduction to Treejack

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1 An Introduction to Treejack
Out on a limb with your IA Dave O’Brien Optimal Usability

2 Welcome Dave O’Brien Optimal Usability 22 Jan 2010 36 attendees
Wellington, New Zealand 22 Jan 2010 36 attendees USA, CA, UK, NZ, AU, BR, CO

3 Agenda Quickie Treejack tour What is tree testing?
Planning a tree test Setting up Treejack Running a test High-level results Detailed results Lessons learned (Q&A throughout)

4 Poll Have you used Treejack yet? No, haven’t tried it yet = 20%
Yes, but only a practice test = 60% Yes, have run a "real" test = 20%

5 Tree testing - the 5-minute tour
Creating a medium or large website Does your top-down structure make sense?

6 Does your structure work?
Can users find particular items in the tree? Can they find them directly, without having to backtrack? Could they choose between topics quickly, without having to think too much? Which parts of your tree work well? Which fall down? The Krug Test – “Don’t make me think!”

7 Create a site tree

8 Write some tasks

9 Put this into Treejack

10 Invite participants

11 Participants do the test
Browsing down Backing up Skipping

12 You see the results

13 Live demo for participants* Q: Can you control font size and color? Q: it would be great if all the options had an 'i'd pick this ' button - when it's on just one, feels leading Q: when you get to the deepest level, if all things are even, have the 'i pick this' button on every row

14 What is tree testing, really?
Testing a site structure for Findability Labeling

15 What’s it good for? Improving organisation of your site
Improving top-down navigation Improving your structure’s terminology (labels) Comparing structures (before/after, or A vs. B) Isolating the structure itself Getting user data early (before site is built) Making it cheap & quick to try out ideas Quick to get a test up and running Quick/easy for users: 10 min for 10 tasks Analysis is straightforward Can test baselines and revisions quickly By isolating the site structure - by removing other variables at this early stage of design - we can more clearly see how the tree itself performs, and revise until we have a solid structure. We can then move on in the design process with confidence. It’s like unit-testing a site’s organisation and labeling. Or as my colleague Sam Ng says, “Think of it as analytics for a website you haven’t built yet.”

16 What it’s NOT NOT testing other navigation routes
NOT testing page layout NOT testing visual design NOT a substitute for full user testing NOT a replacement for card sorting

17 Origin Paper tree testing “card-based classification” – Donna Spencer
Show lists of topics on index cards In person, score manually, analyse in Excel

18 Make it faster & easier Create a web tool for remote testing
Quick for a designer to learn and use Simple for participants to do the test Able to handle a large sample of users Able to present clear results Quick turnaround for iterating

19 But I already do card sorting!
Open card sorting is generative Suggests how your users mentally group content Helps you create new structures Closed card sorting – almost not quite Tree testing is evaluative Tests a given site structure Shows you where the structure is strong & weak Lets you compare alternative structures While closed card sorting mimics how users may file a particular item of content (e.g. where they might store a new document in a document-management system), it doesn’t necessarily model how users find information in a site. They don’t start with a document – they start with a task, just as they do in a usability test. What we wanted was a technique that more closely simulates how users browse sites when looking for something specific. Yes, closed card sorting was better than nothing, but it just didn’t feel like the right approach.

20 A useful IA approach Run a baseline tree test (existing structure)
What works? What doesn’t? Run an open card sort on the content How do your users classify things? Come up with some new structures Run tree tests on them (same tasks) Compare to each other Compare to the baseline results

21 Planning a tree test Stakeholder interview
Find out who, what, when, etc. fill in "planning questions" template Get the tree(s) in digital format use Excel tree-import template, etc. Show “planning questions” template – a canned set of questions specific to tree testing

22 Getting the tree Import a digital format Or enter in Treejack Excel
Text file Word Or enter in Treejack Show Excel template – multiple trees on worksheets

23 Poll How big are your trees? Small (less than 50 items) = 25%
Medium ( items) = 39% Large ( items) = 22% Huge (more than 250 items) = 14%

24 Tree tips Recommend <1000 items Bigger? Cut it down by:
Using top N levels (e.g. 3 or 4) Testing subtrees separately* Pruning branches that are unlikely to be visited Remove “helper” topics e.g. Search, Site Map, Help, Contact Us Watch for implicit topics! which assumes that users can navigate the top level easily – a big assumption Helper topics - If we leave them in, it makes it too easy for users to choose them as alternatives to browsing the tree, and we don’t learn as much. Q: We are testing some IA's which need supporting text for the links - not ideal, but are there any ways to factor this sort of support into a Treejack evaluation (if not that's fine)

25 Implicit topics Create your tree based on the content, not just the page structure. Home Products Support Contact Us South America Europe Contact Us North America Lorem ipsum dolor sit amet, consectetur adipisicing elit sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. South America Home Products Support Contact Us North America South America Europe Beware content-management systems that spit out page trees. They need careful review! Europe

26 User groups and tasks Identify your user groups
Draft representative tasks for each group Tasks must be “real” for those users! ~10 tasks per participant Beware the learning effect Small tree ~8, large tree ~12 More tasks? Limit per participant Randomise the task order Example – Shimano website with sections for bike parts and fishing equipment. Q: What’s the upper limit on # of tasks? Q: Since you can only have 1 user test 10 or so paths, can you combine data sets so you can get a bigger sampling? So by running 100 people through test A, 100 through test B, etc..... I can combine results from A-Z tests to see a picture of something with 100's of paths

27 Drafting tasks What parts of the tree do you want to test?
Coverage should reflect importance Each task must: Be specific Be clearly worded Use the customer’s language Be concise Beware “give-away” words! Review now, preview before the real test Show Excel template – tasks and coverage Customer’s language – “How would you upgrade a fixed asset, such as your laptop?” Q: can task instructions include images (e.g. Where would you find this and show a picture of a sofa). (In ecommerce, it's much better to show an image since the text description for a product can be misleading, ambiguous, or biasing.) A If you add images to this, please keep in mind that some may administering tests in a couple of languages, so images should not contain text (or should be available in a couple of languages) --- sorry, us Canadian government folk have to do things in Engliish and French! Q: With the instruction " I smell garlic bread" this influenced my search because I thought it was an instore bakery item, was this what you are intended? Does this point to th eimportance of the instruction phrasing.

28 Setting up a Treejack project
Creating a Treejack project Entering your tree Entering the tasks and answers Less on mechanics, more on tips

29 Creating a project New vs. Duplicate Survey name vs. address
Identification The “Other” option Passing an argument in the URL

30 Entering your tree Paste from Excel, Word, text file, etc.
“Top” – how to replace Randomising Not the same as randomising tasks Changing the tree after entering answers Lesson learned: Edit/review/finalise the tree elsewhere before putting it into Treejack

31 Entering tasks and answers
Preview is surprisingly useful Multiple correct answers The “main” answer is usually not enough Check the entire tree yourself Must choose bottom-level topics Workaround: Mark all subtopics correct Workaround: Remove the subtopics Choose answers LAST

32 Task options Randomising tasks – almost always Limiting the # of tasks
20-30 tasks = 10 per participant Increase the # of participants to get enough results per task Skip limit Eliminate users who didn’t really try Defaults to 50% Q: does it 'randomize' or 'rotate' the order of the tasks (i.e. will the tasks be evenly distributed across the sample of participants)?

33 Testing the test Not previewing/piloting is just plain dumb
Spot mistakes before launch Preview the entire test yourself Pilot it with stakeholders and sample users Launch it, get feedback, duplicate, revise Look for: Task wording (unclear, ambiguous, typos) Unexpected “correct” answers Misc. problems (e.g. instructions)

34 Poll How many participants do you get per test? 1 – 20 = 44%
21 – 40 = 20% 41 – 100 = 24% Over 100 = 12%

35 Running the tree test Invite participants
Website-page invitations invitations Recommend >30 users per user group/test Monitor early results for problems low # of surveys started invitation not clear? Subject = spam? Not engaging? low completion rate didn’t set expectations? Test too long? Too hard? Generally less taxing than card sorting Q: Is there any benefit in testing 100 people rather than 5-7? Traditional user testing doesn't need statistical significance in sample size, so what benefit does this add?

36 Skimming high-level results
10/100/1000 level of detail Middling overall score Often many highs with a few lows Inspect tasks with low scores (low total or low sub-scores) Inspect the pie charts Show sample results Q: Is there any way to export these high-level views into Excel as well? They can be useful in presentations when reporting back results.

37 Success % who chose a correct answer (directly or indirectly)
low Success score check the spreadsheet to see where they went wrong Destinations tab Path tab

38 Directness % of successful users who did not backtrack
Coming soon: making this independent of success low Directness score check the spreadsheet for patterns in their wandering Paths tab

39 Speed % who completed this task at about the same speed as their other tasks % who completed task within 2 standard deviations of their average task time for all tasks 70% Speed score 7/10 users went their “normal” speed 3/10 users took substantially longer than normal for them Low Speed score indicates that user hesitated when making choices e.g. choices are not clear or not mutually distinguishable Wish: add the raw times to the spreadsheet, so you can do your own crunching as needed. Overall score uses a grid to combine these scores in a semi-intelligent fashion

40 Detailed results – destinations
Where did people end up? # who chose a given topic as the answer Wrong answers High totals - problem with that topic (perhaps in relation to its siblings) Clusters of totals – problem with the parent level Ignore outliers For >30 sessions, ignore topics that get <3 clicks. Show sample results from food shopping – Destinations tab

41 Detailed results – destinations
Look for high “indirect success” rates (>20%) Check paths for patterns of wandering Look for high “failure” rates (>25%) Check the wrong answers above Look for high skip rates (> 10%) Check paths for where they bailed out. Look for "evil attractors" Topics that get clicks across several seemingly unrelated tasks. Usually a vague term that needs tightening up Q: Need to split out the values: How many skipped before even clicking a level; how many quit after truly despairing? Evil attractors - We saw this happen to a consumer-review site that had a “Personal” category; they meant personal-care products like electric shavers, but participants also went there for “personal” items like cell phones, watches, etc.

42 Detailed results – first clicks
Where they went on their first click Important for task success Which sections they visited overall Did they visit the right section but back out? Show sample results from food shopping – First Click tab The first click is the one most highly correlated with eventual success – if we can get users to the right section of a site, they’re much more likely to find the right topic. Perhaps the participants completely ignored the correct section, or maybe they visited it, but backed out and went somewhere else instead.

43 Detailed results – paths
Click-by-click paths that they took through the tree Useful when asking: How the heck did they get way over there? Did a lot of them take the same detour? No web UI for removing participants. Support and we’ll fix you up. Show sample results from food shopping – Paths tab

44 Some lessons learned Test new against old
Revise and test again – quick cycles Test a few alternatives at the same time Cover the sections according to their importance Analysis is easier than for card sorting Use in-person testing to get the “why” Paper is still effective (and free!) for this Tree testing is only part of your IA work New vs. old - we promised a client we would deliver a better IA, not just a different one? Tree testing proved to be a great way to demonstrate this. In our baseline test, the original structure notched a 31% success rate. Using the same tasks, the new structure scored 67% - a solid quantitative improvement. Q: Can you do A/B testing in the tool? Q: We've used it in face-to-face sessions as we get other data too. We've never run it as remote-only as we're nervous of losing the rich insights. Any experiences or thoughts? Tree testing not enough - A good tree still needs to be married up to an effective navigation system, content design, and visual treatment before we can say we’ve built a good information architecture.

45 What’s coming Better scoring for Directness, Speed
Improved results (10/100/1000) General enhancements across Treejack, OptimalSort, and Chalkmark Whatever you yell loudest for…  GetSatisfaction lets you “vote” for issues

46 Tree testing – more resources
Boxes & Arrows article on tree testing Donna Spencer’s article on paper tree testing Treejack website Webinars, slides, articles, user forum

47 Getting your input Specific issues/questions Feature requests
Feature requests Check the support forum (GetSatisfaction) “Feedback” button Show GetSatisfaction

48 Thanks!

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