Classic IR (information retrieval) is predicated on the notion of users searching for information in order to satisfy a particular “information need”. However, it is now accepted that much of what we recognize as search behaviour is often not informational per se. Broder (2002) has shown that the need underlying a given web search could in fact be navigational (e.g. to find a particular site) or transactional (e.g. through online shopping, social media, etc.). Similarly, Rose & Levinson (2004) have identified the consumption of online resources as a further common category of search behaviour.
In this paper, we extend this work to the enterprise context, examining the needs and behaviours of individuals across a range of search and discovery scenarios within various types of enterprise. We present an initial taxonomy of “discovery modes”, and discuss some initial implications for the design of more effective search and discovery platforms and tools.
2. The landscape of search
The information-seeking process
Models and frameworks
Search strategies and tactics
Patterns of search behaviour
Mode networks
Design implications
Conclusions
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4. Web Search Key differences
• Multiple engines Rich link structure
• Single source
Redundancy
Adversarial search &
spam
Enterprise search
• Single engine User goals & tasks:
• Multiple sources fact finding to
exploratory search
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5. James
Joyce’s
Ulysses?
Irish
PR6019.O9 U418 G42 writer?
5
6. James Joyce’s
Irish writer?
Ulysses?
Fact finding Discovery
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7. Keyword search works when you know what
you want, and how to ask for it
Fails when you don’t know what you want, or
even what questions to ask
information
retrieval
Part of a larger cycle
sense-
analysis
making
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8. Models and frameworks
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9. Standard Model
Broder 2002, Sutcliffe
& Ennis 1998
Cognitive Model
Norman 1988,
Marchioni 1989
Dynamic Model
Bates 1989, O‘ Day
and Jeffries 1993
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10. • to keep a search on track and
Monitoring efficient
Information • for navigating through the file or link
structure structure of the individual resources
Query • to support the overall query or
reformulation search specification)
• to aid the selection of words or
Term phrases in the current query
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11. Search Modes
• Monitoring a known topic or set of variables over time
• Following a specific plan for information gathering
• Exploring a topic in an undirected fashion
Analysis Techniques
• Looking for trends or correlations
• Making comparisons
• Experimenting with different aggregations/scaling
• Identifying critical subsets
• Making assessments
• Interpreting data to find meaning
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12. • The immediate intent is to reach a
Navigational particular site
• The intent is to acquire some
Informational information assumed to be present on
one or more web pages
• The intent is to perform some web-
Transactional mediated activity
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13. UXLabs - User Experience Research and Design - www.uxlabs.co.uk 13
14. Marchionini, 2005
• Lookup
• Learn
• Investigate
Spencer, 2006 Morville, 2010
• Known-item • Quit
• Exploratory • Narrow
• Don’t know what • Expand
you need to know • Pearl-growing
• Re-finding • Pogo-sticking
• Thrashing
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15. Locating Verifying Monitoring Comparing Comprehending Exploring
Scenarios
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16. • To find a specific (possibly known) item
Locating • e.g. I need to find a new part with particular technical attributes
and then source it from the most qualified supplier –
Engineering
• To confirm or substantiate that an item or set of items meets
Verifying some specific criterion
• e.g. How can I determine if I am looking at the latest
information for a part or supplier? - Supply Chain Specialist
• To maintain awareness of the status of an item or data set for
Monitoring purposes of management or control
• e.g. I need to monitor at risk/failing customers/dealers so I can
prompt my Account Reps to fix the problems - Sales Manager
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17. • To examine two or more items to identify similarities & differences
• e.g. I need to compare our module set teardowns with competitive
Comparing teardown information to see if we’re staying competitive for cost,
quality and functionality – Engineering
• To generate insight by understanding the nature or meaning of an
item or data set
Comprehending • e.g. I need to analyze and understand consumer-customer-market
trends to inform brand strategy & communications plan – Director,
Brand Image
• To proactively investigate or examine an item or data set for the
purpose of serendipitous knowledge discovery
Exploring • e.g. I need to understand the cost drivers for this commodity so I can
negotiate better terms with my suppliers and forecast business risk
based on market indices - Procurement
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18. • To critically examine the detail of an item or data set to identify
patterns & relationships
Analyzing • e.g. I need to know the cost drivers for a part such as materials that
impact cost. Is the relationship a correlation or step function for a
part cost driver? – Engineering
• To use judgement to determine the significance or value of an item
or data set with respect to a specific benchmark or model
Evaluating • e.g. I need to determine my current state in my prints so I can
evaluate if I have price variation to negotiate a better price –
Procurement
• To generate or communicate insight by integrating diverse inputs to
Synthesizing create a novel artefact or composite view
• e.g. I need to prepare a weekly report for my boss (sales mgr) of how
things are going - Account Rep
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20. Mode chains and sequences
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21. Analyzing Comparing Evaluating
Engineering: Compare our module set teardowns with
competitive teardown information to see if we’re staying
competitive for cost, quality and functionality.
Portfolio Manager: Compare a lead's performance
claims with relevant benchmarks to assess the lead's
claims
Cost Estimators: Analyze & understand gaps between
current costs of commodity versus best in class
manufacturing costs
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22. Exploring Analyzing Evaluating
Core Engineer: Identify opportunities to optimize use of
tooling capacity for my commodity/parts
District Manager: Identify sales opportunities and
targets (increased key customer market share across
categories/brands; upsell-cross sell; promotional targets
Category Manager: Evaluate & optimize our product
portfolio: Which products should we de-list and retire?
What new products should we be making/selling?
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23. Analyzing Comprehending Evaluating
Engineering: Track module cost versus functionality
over time to determine trends.
Portfolio Manager: Understand a lead's underlying
positions so that I can assess the quality of the
investment opportunity
Procurement: Understand the cost drivers for a
commodity so I can negotiate better terms with my
suppliers and forecast business risk based on market
indices
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24. Monitoring Analyzing Evaluating
SVP Sales: Monitor how well we are tracking to
revenue and margin targets by division
Core Engineer: Monitor global commodity use in
relation to plan/guidelines to identify gaps that
require corrective action
Financial Analyst: Monitor & assess commodity
status against strategy/plan/target
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25. Analyzing Comparing Synthesizing
Director, Brand Image: Analyze and understand
consumer-customer-market trends to inform brand
strategy & communications plan
Engineering: Find out how many parts I have in my
module set of parts and find ways to reduce cost
across them
Core Buyer: Formulate scope & strategy for
sourcing and gap closure
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26. Verifying
Analyzing Comprehending Synthesizing
Comparing Evaluating
Monitoring Analyzing
Exploring
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27. Applying the insights
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28. Single element patterns
• Comparison views (Comparing)
• Contextual views (Analyzing)
Whole screen patterns
• Dashboard (Monitoring, Synthesizing)
• Visual discovery (Exploring, Evaluating, Verifying)
Application-level patterns
• Differentiated (Analysing, Comparing, Evaluating,
Monitoring Strategic Oversight)
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29. Map search modes to screen components
Avoid “one size fits all”
Create views by combining components
Communicate conceptual relationships through
Gestalt principles of organization (e.g. similarity,
closure, proximity, etc.)
Compose applications by combining views
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31. Purpose Page 1 Page 2 Page 3
Present global
overview / summary Metrics Bar Metrics Bar
of key metrics
Metrics Bar Metrics Bar Alerts
Modes Metrics Bar Metrics Bar
Monitoring
Metrics Bar
Exploring
Metrics Bar Chart Alerts
Components Metrics Bar
Metrics Bar
Alerts
Chart
Cross Tab Cross Tab
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32. Purpose Page 1 Page 2 Page 3
Explore unstructured data
Search
Modes Breadcrumb Results List
Comprehending
Exploring
Synthesizing
Compare
Components
Search Guided
Navigation Record Detail Find Similar
Breadcrumb
Faceted Navigation
Results List
Compare Record Detail
Record Detail
Find Similar
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33. Data
Source
B
analyze
evaluate compare
Data Data
Source Source
A C
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34. Data
Source Metrics Metrics Metrics
C Bar
Data Bar
Data Bar
Data
A B C
analyze
monitor
evaluate compare
Data Data
Source Source
A B
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35. Explore
Monitor
Compare
Comprehend
Analyze
Evaluate
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36. Summary and future work
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37. A Taxonomy of Enterprise Search
• A perspective for understanding information-seeking behaviour
• A framework for designing discovery applications
Search Modes
• Combine academic and practitioner perspectives
• Atomic units and composite patterns
Further Work
• Larger data sample, more principled sampling strategy
• Acquire data directly & consistently (from primary sources)
• Refine and validate process
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38. Tony Russell-Rose, PhD
Director, UXLabs
Web: http://uxlabs.co.uk
Email: tgr@uxlabs.co.uk
Blog: http://isquared.wordpress.com
LinkedIn: http://uk.linkedin.com/in/tonyrussellrose
Twitter: @tonygrr
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