In order to design better search experiences, we need to understand the complexities of human information-seeking behaviour. In previous work, we proposed a model of information behavior based on an analysis of the information needs of knowledge workers within an enterprise search context. In this presentation, we extend this work to the site search context, examining the needs and behaviours of users of consumer-oriented websites and search applications.
We found that site search users presented significantly different information needs to those of enterprise search, implying some key differences in the information behaviours required to satisfy those needs. In particular, the site search users focused more on simple “lookup” activities, contrasting with the more complex, problem-solving behaviours associated with enterprise search. We also found repeating patterns or ‘chains’ of search behaviour in the site search context, but in contrast to the previous study these were shorter and less complex. These patterns can be used as a framework for understanding information seeking behaviour that can be adopted by other researchers who want to take a ‘needs first’ approach to understanding information behaviour.
Classic IR (information retrieval) is predicated on the notion of users searching for information in order to satisfy a particular ‘information need’. However, much of what we recognise as search behaviour is often not informational per se. In this presentation, we examine the behaviour of individuals across a range of site search scenarios, and define a taxonomy of fundamental behaviours or 'search modes'. We compare these with a comparable set of modes derived from the domain of enterprise search, and examine some of the key differences between the two. We also discuss some initial implications and techniques for the design of more effective site search experiences.
Research into how people find and share expertise can be traced back to the 1960s, with early studies focusing on knowledge workers such as engineers and scientists and the information sources they consult. However, in recent years there has been a growing recognition that the effectiveness of expertise retrieval systems is highly dependent on a number of contextual factors, where the emphasis is on how people search for expertise in the context of a specific task. These studies have typically been performed in an enterprise context, where the aim is to utilize human knowledge within an organization as efficiently as possible. This talk presents results of an Innovate-UK funded project investigating the use of complex search strategies in the workplace, with the aim of producing requirements for the design of next generation search tools.
A taxonomy of search strategies and their design implicationsTony Russell-Rose
The focus of this particular talk is on extending the review of information search strategies (aka ‘Modes of Discovery‘) with a deeper exploration of their implications for design at the application (architectural) level.
An overview of the key theories and models of human information-seeking behavior and how these translate into principles for the design of effective search and discovery experiences.
This presentation describes a framework for describing and categorising personalisation as experienced within eCommerce. It explores its application to a number of examples, and discusses the implications (e.g. instances that could in theory exist but don’t).
Danny Sullivan, Chief Content Officer and Founding Editor of Marketing Land and Search Engine Land, speaks about past, present, and future trends in search engines and discusses how to optimize your company's website for Google, Bing, and mobile devices.
Classic IR (information retrieval) is predicated on the notion of users searching for information in order to satisfy a particular ‘information need’. However, much of what we recognise as search behaviour is often not informational per se. In this presentation, we examine the behaviour of individuals across a range of site search scenarios, and define a taxonomy of fundamental behaviours or 'search modes'. We compare these with a comparable set of modes derived from the domain of enterprise search, and examine some of the key differences between the two. We also discuss some initial implications and techniques for the design of more effective site search experiences.
Research into how people find and share expertise can be traced back to the 1960s, with early studies focusing on knowledge workers such as engineers and scientists and the information sources they consult. However, in recent years there has been a growing recognition that the effectiveness of expertise retrieval systems is highly dependent on a number of contextual factors, where the emphasis is on how people search for expertise in the context of a specific task. These studies have typically been performed in an enterprise context, where the aim is to utilize human knowledge within an organization as efficiently as possible. This talk presents results of an Innovate-UK funded project investigating the use of complex search strategies in the workplace, with the aim of producing requirements for the design of next generation search tools.
A taxonomy of search strategies and their design implicationsTony Russell-Rose
The focus of this particular talk is on extending the review of information search strategies (aka ‘Modes of Discovery‘) with a deeper exploration of their implications for design at the application (architectural) level.
An overview of the key theories and models of human information-seeking behavior and how these translate into principles for the design of effective search and discovery experiences.
This presentation describes a framework for describing and categorising personalisation as experienced within eCommerce. It explores its application to a number of examples, and discusses the implications (e.g. instances that could in theory exist but don’t).
Danny Sullivan, Chief Content Officer and Founding Editor of Marketing Land and Search Engine Land, speaks about past, present, and future trends in search engines and discusses how to optimize your company's website for Google, Bing, and mobile devices.
How awesome is site search today, often it isn't... Frequently it is badly tracked or with just Google analytics "out of the box" so it misses some of the most important performance metrics. What is the life of a query today and some mistakes I have made in the past.
My slides from #MeasureFest 2016
Search is undergoing dramatic changes taking it away from a focus on keywords and websites, towards conversational search and app indexes. In this presentation Distilled discusses the ways search is fundamentally changing including compound queries, implicit search signals, user signals as a ranking factor, the move from keywords to intents, and the drive towards data driven search.
Stimulus-response Model Of Buyer Behavior
The Five Values Influencing Consumer Choice Behavior
Solomon Model Of Comparison Process
Nicosia Model
Howard-sheth Model
Engel-kollat-blackwell Model
Lean Startup Circle talk in Austin, Texas - August 20, 2013. Presented by Jon-Eric Steinbomer, Progress UX Principal and Research Director. Topics included: personas, remote research techniques, hardware and mobile research methods, card sorting and diary studies.
Intention of the talk was to provide a general framework of UX research methods and guidance to entrepreneurs and startups so that they could feel empowered to either try their own customer research or better understand how it fits in with the UX ecosystem.
UXPA 2023: UX Fracking: Using Mixed Methods to Extract Hidden InsightsUXPA International
Users do not always accurately describe what they mean or feel. There are many reasons for this, ranging from politeness to poor introspection, to lack of sufficient technical vocabulary. Fortunately, UX researchers have tools in their trade to deduce what was really meant. We call this UX Fracking, a mixed methods approach that is optimized for extracting hidden user insights. We will illustrate the dangers of inadequate, superficial research, and how this may lead to outcomes incapable of addressing the users’ core issues. We will explore ways to avoid these pitfalls by leveraging mixed research methods to test hypotheses about the users’ intent and needs. This starts with a thorough understanding of who the user is, their goals, and how they work today, to an approach that combines surveys, interviews, and comment analysis with behavioral observation, and finally, validating the newly discovered user insights with the users themselves.
Mobile Center of Excellence is perfect for organizations looking to ensure the long-term success of their mobile strategies and Applications. It’s built to help you create and define the building blocks of a successful Center of Excellence for Mobile.
Mobile UX COE Strategists will work with your team to understand your current state readiness, build a vision for the Mobile Center of Excellence within your organization, and define the requirements for standing up a Mobile COE. Beyond just the components of a Center of Excellence, helps team creates a realistic roadmap for COE creation based on the people, process, and technology maturity within your business
UX Research & PP projects @UXScotland 2014Abi Reynolds
I gave this presentation at UX Scotland 2014. I talked about UX Research in the product development process and discussed different methods and methodologies that can be used to generate user insights at different stages of the design process. The session focused on my experience as UX Research Manager in Paddy Power.
Webinar: Increase Conversion With Better SearchLucidworks
Hear from IBM Product Line Manager Iris Yuan & Lucidworks VP of Partner Engineering Sarath Jarugula for a deep discussion into how improving ecommerce search can drive conversions and increase revenue.
How awesome is site search today, often it isn't... Frequently it is badly tracked or with just Google analytics "out of the box" so it misses some of the most important performance metrics. What is the life of a query today and some mistakes I have made in the past.
My slides from #MeasureFest 2016
Search is undergoing dramatic changes taking it away from a focus on keywords and websites, towards conversational search and app indexes. In this presentation Distilled discusses the ways search is fundamentally changing including compound queries, implicit search signals, user signals as a ranking factor, the move from keywords to intents, and the drive towards data driven search.
Stimulus-response Model Of Buyer Behavior
The Five Values Influencing Consumer Choice Behavior
Solomon Model Of Comparison Process
Nicosia Model
Howard-sheth Model
Engel-kollat-blackwell Model
Lean Startup Circle talk in Austin, Texas - August 20, 2013. Presented by Jon-Eric Steinbomer, Progress UX Principal and Research Director. Topics included: personas, remote research techniques, hardware and mobile research methods, card sorting and diary studies.
Intention of the talk was to provide a general framework of UX research methods and guidance to entrepreneurs and startups so that they could feel empowered to either try their own customer research or better understand how it fits in with the UX ecosystem.
UXPA 2023: UX Fracking: Using Mixed Methods to Extract Hidden InsightsUXPA International
Users do not always accurately describe what they mean or feel. There are many reasons for this, ranging from politeness to poor introspection, to lack of sufficient technical vocabulary. Fortunately, UX researchers have tools in their trade to deduce what was really meant. We call this UX Fracking, a mixed methods approach that is optimized for extracting hidden user insights. We will illustrate the dangers of inadequate, superficial research, and how this may lead to outcomes incapable of addressing the users’ core issues. We will explore ways to avoid these pitfalls by leveraging mixed research methods to test hypotheses about the users’ intent and needs. This starts with a thorough understanding of who the user is, their goals, and how they work today, to an approach that combines surveys, interviews, and comment analysis with behavioral observation, and finally, validating the newly discovered user insights with the users themselves.
Mobile Center of Excellence is perfect for organizations looking to ensure the long-term success of their mobile strategies and Applications. It’s built to help you create and define the building blocks of a successful Center of Excellence for Mobile.
Mobile UX COE Strategists will work with your team to understand your current state readiness, build a vision for the Mobile Center of Excellence within your organization, and define the requirements for standing up a Mobile COE. Beyond just the components of a Center of Excellence, helps team creates a realistic roadmap for COE creation based on the people, process, and technology maturity within your business
UX Research & PP projects @UXScotland 2014Abi Reynolds
I gave this presentation at UX Scotland 2014. I talked about UX Research in the product development process and discussed different methods and methodologies that can be used to generate user insights at different stages of the design process. The session focused on my experience as UX Research Manager in Paddy Power.
Webinar: Increase Conversion With Better SearchLucidworks
Hear from IBM Product Line Manager Iris Yuan & Lucidworks VP of Partner Engineering Sarath Jarugula for a deep discussion into how improving ecommerce search can drive conversions and increase revenue.
The State of UX: Industry Trends & Survey Results - IA Summit 2017Lyle Kantrovich
What’s the most valuable UX method? What are the best UX tools? What techniques do teams use the most? This presentation covers those topics and more in fresh findings from research with UX practitioners from across the industry. You’ll learn something useful whether you’re a manager, a seasoned pro, a newcomer planning your next career move, or just want a few ideas about new skills to learn.
Introduction to Information Architecture & Design - 2/13/16Robert Stribley
Introduction to Information Architecture & Design - Workshop as presented by Robert Stribley at SVA's School of Continuing Education, February 13th, 2016
What is User Experience Design?
The Business Case for User Experience Design
What are the UX processes?
How can we measure its effectiveness?
Who needs to be involved?
Open Day activity for Computing @ University of East London.
This is a very cut down version of what students are going to study on their second year when taking Usability Engineering.
Introduction to usability evaluation methods & usability testing.
Shilpa Lewis UX Professional Samples of UX artifacts produced across the span of 15+ years in the field of UX, work reflects a balance in skills between Interaction Design & User Research (methodologies ranging from Contextual Inquiry to controlled usability studies - both on-site and remote). I offer rapid prototyping, with iterative user research, within a User Centered Agile Process.
Similar to A Model of Consumer Search Behaviour (20)
Anyone seeking to pull meaning and insight from large datasets suffers from the current primitive state of search tools. Users develop search strategies that have to be painstakingly constructed using complex logic, and are difficult to maintain or reuse, especially across multiple data sources. They are also highly error prone. And yet continuous, consistent application of rigorous search is necessary to keep up with new materials. "Advanced" search interfaces are notoriously counter-intuitive and difficult to learn, and rigidly procedural. One wrong step and the whole query can go wrong. Spotting errors can be very hard.
In this session, Tony Russell-Rose will describe how the search interfaces for such problems can be simplified and made more intuitive, and he will demonstrate a "visual search" technique using a canvas to build and test complex search queries in a two dimensional frame, and which can be applied to major search engines such as Google and Bing, or content sources such as LinkedIn, Twitter and Github, to deliver highly precise and relevant results, in a repeatable, consistent, and easy-to-maintain way.
Professions such as healthcare, law, recruitment and patent search all share an interest in the resolution of complex information needs. This typically involves the formulation of structured search strategies that are expressed as Boolean strings. However, creating effective Boolean queries remains an ongoing challenge, often compromised by a lack of transparency and reproducibility. In this paper we explore some of the shortcomings of current approaches, examine alternative solutions and make recommendations towards improved explainability in professional search.
Anyone seeking to pull meaning and insight from large datasets suffers from the current primitive state of search tools. Users develop search strategies that have to be painstakingly constructed using complex logic, and are difficult to maintain or reuse, especially across multiple data sources. They are also highly error prone. And yet continuous, consistent application of rigorous search is necessary to keep up with new materials. "Advanced" search interfaces are notoriously counter-intuitive and difficult to learn, and rigidly procedural. One wrong step and the whole query can go wrong. Spotting errors can be very hard.
In this session, Tony Russell-Rose will describe how the search interfaces for such problems can be simplified and made more intuitive, and he will demonstrate a "visual search" technique using a canvas to build and test complex search queries in a two dimensional frame, and which can be applied to major search engines such as Google and Bing, or content sources such as LinkedIn, Twitter and Github, to deliver highly precise and relevant results, in a repeatable, consistent, and easy-to-maintain way.
Knowledge workers (such as healthcare information professionals, patent agents and recruitment professionals) undertake work tasks where search forms a core part of their duties. In these instances, the search task is often complex and time-consuming and requires specialist expertise to formulate accurate search strategies. Interactive features such as query expansion can play a key part in supporting these tasks. However, generating query suggestions within a professional search context requires that consideration be given to the complex, structured nature of the search strategies they employ. In this paper, we investigate a variety of query expansion methods applied to a collection of Boolean search strategies used in real-world professional search tasks. The results demonstrate the utility of distributional models and the value of using ngram order to optimize precision and recall.
Think outside the search box: a AI-based approach to search strategy formulationTony Russell-Rose
Knowledge workers (such as healthcare information professionals, patent agents and legal researchers) need to undertake complex search tasks to identify relevant documents and insights within large domain-specific repositories and collections. The traditional solution is to use line-by-line query builders offered by proprietary database vendors. However, these offer limited support for error checking or query optimization, and their output can often be compromised by errors and inefficiencies.
In this talk, we present a new approach to query formulation in which concepts are expressed as objects on a two-dimensional canvas, and relationships are articulated by direct manipulation. Automated search term suggestions are provided using a combination of knowledge-based and statistical NLP techniques. This has the potential to eliminate many sources of inefficiency, make the query semantics more transparent, and provide a universal framework for search strategy formulation.
This is an update of a talk I originally gave in 2010. I had intended to make a wholesale update to all the slides, but noticed that one of them was worth keeping verbatim: a snapshot of the state of the art back then (see slide 38). Less than a decade has passed since then but there are some interesting and noticeable changes. For example, there was no word2vec, GloVe or fastText, or any of the neurally-inspired distributed representations and frameworks that are now so popular. Also no mention of sentiment analysis (maybe that was an oversight on my part, but I rather think that what we perceive as a commodity technology now was just not sufficiently mainstream back then).
Also if you compare with Jurafsky and Martin's current take on the state of the art (see slide 39), you could argue that POS tagging, NER, IE and MT have all made significant progress too (which I would agree with). I am not sure I share their view that summarisation is in the 'still really hard' category; but like many things, it depends on how & where you set the quality bar.
This presentation compares four tools for analysing the sentiment in the content of free-text survey responses concerning a healthcare information website. It was completed by Despo Georgiou as part of her internship at UXLabs (http://uxlabs.co.uk)
In this talk we outline some of the key challenges in text analytics, describe some of Endeca's current research work in this area, examine the current state of the text analytics market and explore some of the prospects for the future.
UI Design Patterns for Search & Information DiscoveryTony Russell-Rose
This talk examines the role of patterns in designing information search and discovery applications, describes some of the challenges involved in creating the Endeca UI Design Pattern Library, and explores some of the issues involved in maintaining and growing a pattern library as a resource for a company as well as the wider user experience design community.
Maximize Your Content with Beautiful Assets : Content & Asset for Landing Page pmgdscunsri
Figma is a cloud-based design tool widely used by designers for prototyping, UI/UX design, and real-time collaboration. With features such as precision pen tools, grid system, and reusable components, Figma makes it easy for teams to work together on design projects. Its flexibility and accessibility make Figma a top choice in the digital age.
White wonder, Work developed by Eva TschoppMansi Shah
White Wonder by Eva Tschopp
A tale about our culture around the use of fertilizers and pesticides visiting small farms around Ahmedabad in Matar and Shilaj.
PDF SubmissionDigital Marketing Institute in NoidaPoojaSaini954651
https://www.safalta.com/online-digital-marketing/advance-digital-marketing-training-in-noidaTop Digital Marketing Institute in Noida: Boost Your Career Fast
[3:29 am, 30/05/2024] +91 83818 43552: Safalta Digital Marketing Institute in Noida also provides advanced classes for individuals seeking to develop their expertise and skills in this field. These classes, led by industry experts with vast experience, focus on specific aspects of digital marketing such as advanced SEO strategies, sophisticated content creation techniques, and data-driven analytics.
2. Models of information seeking
Studying consumer search behaviour
Data acquisition
Data analysis
Mode sequences and patterns
Enterprise search vs. site search
Conclusions
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3. Analytical frameworks
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4. • 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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5. 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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6. Original Model
• Starting: activities associated with the initial search for information
• Chaining: following citation chains
• Browsing: semi-directed searches
• Differentiating: filtering the material examined
• Monitoring: maintaining awareness
• Extracting: working thru a source to locate material of interest
Additions
• Verifying: checking accuracy of information
• Ending: activities associated with the end of a project
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7. UXLabs - User Experience Research and Design - www.uxlabs.co.uk 7
8. UXLabs - User Experience Research and Design - www.uxlabs.co.uk 8
9. Data acquisition and analysis
UXLabs - User Experience Research and Design - www.uxlabs.co.uk 9
10. Information needs gathered thru client
engagements (stakeholder workshops)
▪ Find best offers before the others do so I can have a high margin.
▪ Get help and guidance on how to sell my car safely so that I can
achieve a good price.
▪ Understand what is selling by area/region so I can source the correct
stock.
▪ See year-on-year ad spend trends for TV and online to supply to the
Head of Global Media.
Moderated, normalised, then prioritised
277 ‘micro-scenarios’
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11. Interview
transcripts, Information Information Design
direct behaviours needs insights
observation
Start from interview transcripts / direct observation
Identify information behaviours
Infer information needs
Derive design insights
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12. Information Information
Interactions
needs behaviours
Design
insights
Start directly from information needs
Identify design insights
Infer behaviours and interactions to support them
UXLabs - User Experience Research and Design - www.uxlabs.co.uk 12
13. Real world data!
Field based, not lab based
Shortcomings of interview transcripts:
Observed behaviours are inevitably bounded by
current systems & working practices
Do not reflect aspirational or unmet needs
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14. Locating Verifying Monitoring Comparing Comprehending
Partially inductive
Apply the previous
model
Scenarios
Partially deductive
Identify new types of
behaviour
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16. Locate • Find a specific (possibly known) item
• “Find my reading list items quickly” – Student
• Confirm that an item meets some specific, objective
Verify criterion
• “See the correct price for singles and deals” – Professional
Purchaser
• Maintain awareness of the status of an item for purpose of
Monitor management or control
• “Alert me to new resources in my area” – Lecturer
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17. • To identify similarities & differences within a set of
items
Compare • “Compare cars that are my possible candidates in
detail” – Knowledgeable Seeker
• To generate independent insight by interpreting
patterns within a data set
Comprehend • “Understand what my competitors are selling” –
Independent Dealer
• To investigate an item or data set for the purpose of
Explore knowledge discovery
• “Find useful stuff on my subject topic” – Student
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18. • To examine an item or data set to identify patterns
& relationships
Analyze • “Analyze the market so I know where my strengths
and weaknesses are” – Franchise Dealer
• To use judgement to determine the value of an item
with respect to a specific goal
Evaluate • “I want to know whether my agency is delivering
best value” – Marketing Professional
• To create a novel or composite artefact from
diverse inputs
Synthesize • “I need to create a reading list on celebrity
sponsorship” – Faculty
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20. Search behaviour is not random
Framework captures common patterns
Repeating sequences of 2 or 3 modes
Composite chains (nested)
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21. Explore -> Analyze -> Comprehend (44/97)
Assess the proper market value for my car
Explore -> Locate -> Evaluate (31/97)
Find best offers before the others do so I can have a
high margin
Locate -> Verify (29/56)
Find a van that meets a customer's requirements
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22. Explore Analyze
Comprehend Comprehend
Locate Evaluate
Verify
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23. Verify
Analyze Comprehend Synthesize
Compare Evaluate
Monitor Analyze
Explore
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24. Greater emphasis on ‘Lookup’ modes
Locate, Verify
Synthesize represents a tiny fraction (2)
Less emphasis on ‘Investigate’ modes
Analyze, Evaluate
Much flatter distribution of patterns
Shorter chains
Less embedding
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26. Search modes
• A lens for understanding information-seeking
• A framework for describing composite patterns of behaviour
Site Search vs. Enterprise Search
• Same behaviours but different priorities and patterns
• Shorter chains, less embedding
Further Work
• Refine and validate ‘needs first’ process
• Extend framework to other data sources
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27.
28. 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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