SlideShare ist ein Scribd-Unternehmen logo
1 von 28
STARTING A TAXONOMY PROJECT
Case Study: eCommerce Product Taxonomy
#slataxo
Miraida Morales | miraidam@gmail.com | @MiraidaM
OUTLINE
 Company Background
 User Need
 Challenges
 Project Goals
 Chosen Method
 Implementation
 Key Learnings
COMPANY BACKGROUND
o eCommerce site dedicated to one-of-a-kind design,
antiques and luxury goods
o Marketplace platform of 2000 dealers = 100% user
generated content
o 11 years old = Lots of user data
o Initiative to improve the Buyer Experience
COMPANY BACKGROUND
COMPANY BACKGROUND
USER NEED
 Implement a classification system that allows
dealers to describe their items accurately
AND
 Allows buyers to easily find what they are looking
for
 Without overburdening the user
CHALLENGES
 Ignore MECE principle
 Mutually Exclusive, Collectively Exhaustive (McKinsey)
 a way of grouping information used in Consulting, but these
principles are useful for creating categories
 Inconsistent label naming strategy
 Glass and Pitchers under Serving
 Bronzes, Carvings, Lacquer under Other
 Redundant categories
 Chairs, Armchairs and Side Chairs are different subcategories
under Seating
 Duplicate categories
 Desks as a subcategory under Tables and under Case Pieces
 Rugs under Carpets and under Other
 Like items and similar categories not grouped together
 Tea Canisters under Other; Tea Sets under Serving
 Tobacco Accessories under Other; Ashtrays under Serving
 Inkwells and Desk Accessories are separate categories
CHALLENGES
 Misrepresented categories
 Antiquities under Folk Art
 Tribal Art under Folk Art
 Figurines under Serving
 Ashtrays under Serving
 Category simply called Other, including 64
subcategories – a mix of furniture and decorative items
 Approximately 2000 new items uploaded every
week & classified by users
 Inventory constantly changing
 Diversity of users uploading content
 Differing levels and areas of expertise, technology aptitude, etc
 Increasing number of dealers based outside the US
 Language problems; upload tools not localized
PROJECT GOALS
 Improve “findability”
 allow buyers to find relevant/desired items on the site =
increase conversion (click-through, contact dealer, sales)
 introduce new users to the site (by improving SEO)
 Reduce number of miss-categorized items
 Approximately 35%-40% of items are uploaded with a
categorization error every week
 Avoid category gaps that lead to unclassifiable items
 Ex: Sewing tables
 Create sustainable structure that can support growth
and future inventory needs
METHOD
 What are we describing? (Scope)
 Conducted audit of inventory on the site
 100,000+ furniture items, lighting elements, decorative objects,
collectibles, architectural elements
 Settees, chandeliers, pier mirrors, antique tall case clocks,
carnival art, trade signs, carpets, creamware tea sets, art
furniture
 Reviewed attributes and identified attribute gaps
 Antiques, modern and contemporary pieces
 By well-known makers and unknown provenance (attribution)
 Variable/non-standard sizes (e.g. scatter sizes for tribal rugs)
 Materials and techniques (e.g. burl wood, eglomized, gilt, flat
weave, hooked)
 Pieces from all over the world (e.g. French antiques, English
Silver, Turkish Rugs)
SOFA OR COUCH?
 What do others call it?
 Competitive analysis
 Auction houses, similar design/décor sites
 Consulted with experts and top dealers for each
category
 Appraisers, resources such as Yale Furniture Study, Period
rooms at Brooklyn Public Library
 Researched controlled vocabularies:
 Getty ULAN, Getty AAT, Categories for the Description of
Works of Art, Geographic name lists
DIVAN, SETTEE, CANAPÉ, CHESTERFIELD,
LOVESEAT, BENCH, SECTIONAL…
 How do buyers look for it?
 Keyword research
 Google Adwords Keyword tool
 Google Trends
 Site-based search keyword analysis
 Search logs
 User studies
 Real-time, monitored interview of users given a task to perform
on our site while we observe and record (audio, screenshots,
notes)
IMPLEMENTATION
 Update database, tables, relationships between items,
categories and attributes
 Update classification tools
 Used by dealers and
 Used by internal admin (curation team, category managers,
me)
 Reclassify existing inventory
 Introduce controlled vocabularies for attributes
 Creator names, Country of Origin, Condition & Wear, Styles
 Notify dealers about the changes to their tool and about
new classification structure
IMPLEMENTATION
 Improving search & browse experience
 Implement keyword-rich meta-tags, meta titles on html
pages
 Implement synonym rings for search (in development)
 Include popular search terms for search auto-complete
feature
 Reduces 0 results by avoiding typos, ambiguous terms, etc
 Implement Product schema: http://schema.org/Product
 Implement Goodrelations schema:
http://www.heppnetz.de/ontologies/goodrelations/v1.htm
l
 Implement redirects, canonical tags, update sitemap
 Buillotte lamps -> table lamps
IMPLEMENTATION
 For this site, implementation and maintenance was
manual for many reasons.
 Cost
 Database architecture re-design was simultaneous
 Reticence on the part of site owners
 Other options:
 Automated systems for classification based on
descriptive content
 Using search feature to allow dealers to query site to
help them place hard-to-classify items near relevant
items
 Develop in-house taxonomy management/development
tool
 License a taxonomy development tool
RUGS OR CARPETS?
 Semantics
 How are they described?
 By Origin (Indian, Turkish, Persian, Navajo, Irish) and Region
(Amritsar, Agra, Donegal)
 By Technique (flat-weave, hooked, knotted-pile, hand-woven)
 By Style (Herati design, Arts and Crafts, Art Nouveau)
 What should we call them?
 Traditionally, rugs are smaller than carpets
 Today, we use „carpet‟ often to mean „wall-to-wall carpeting‟; this
definition does not apply to antique/collectible carpets
 Origin/Regional designations also encapsulate styles, techniques
and colors common to the region
KHOTAN RUGS
 From ancient city of Khotan in present
day Uygur Autonomous Region of
Xinjiang (Chinese Turkistan)
 Also known as Samarkand Rugs
 Incorporate Asian motifs, lattice-
patterns
 Rugs and Carpets (BT)
 Central Asian (NT)
• Khotan Rugs (NT)
• Samarkand Rugs (VT)
INDIAN AGRA RUG
 From city of Agra (TajMahal)
for Mughal Empire, also
produced in Lahore
 Back in vogue during British
colonial period
 Designs often based on
classical Persian motifs
 Rugs and Carpets (BT)
 Indian Rugs (NT)
• Indian Agra Rugs (NT)
• Moghul Carpets (VT)
TURKISH KILIM RUG
 Kilims can be Persian, Turkish,
Moroccan, from the Balkans
 Flat-woven (pile-less)
 Tapestry style designs, geometric
 Rugs and Carpets (BT)
 Turkish Rugs (NT)
• Turkish Kilim Rugs (NT)
• MoroccanKilim (RT)
SPANISH SAVONNERIE CARPET
 Savonnerie Carpets originally
French, inspired by Turkish
rugs
 Knotted-pile, Ghiordes knot
 Floral motifs, rococo elements
 Rugs and Carpets (BT)
 Western European Rugs (NT)
• Spanish Savonnerie Rugs
(NT)
• French Savonnerie Rugs
(RT)
IRISH DONEGAL CARPET
 From County Donegal, Ireland
 Wool, handwoven
 Celtic designs, Arts & Crafts, Art
Nouveau, border designs
 Rugs and Carpets (BT)
 Western European Rugs (NT)
• Spanish Rugs (NT)
• Irish Rugs (NT)
• Donegal Carpets(NT)
NAVAJO RUG
 Tribal weaving from Four Corners
region of US
 Flat tapestry-woven, wool
 Geometric patterns
 Rugs and Carpets (BT)
 North and South American Rugs (NT)
• Navajo Rugs (NT)
• American Hooked Rugs (NT)
AMERICAN HOOKED RUG
 From Northeast US
and Eastern
Canada
 Hooked, pile, made
from linen, jute,
flax, hemp
 Floral designs,
scenes, people
 Rugs and Carpets (BT)
 North and South American Rugs (NT)
• American Hooked Rugs (NT)
• Navajo Rugs (NT)
IMPLEMENTATION: RUGS AND CARPETS
 Mix of Styles, Periods, Shapes and Regions
 Modernist, Art Deco, Arts and Crafts
 Chinese
 Runners vs. Wide Runners vs. Turkish Kilim Runners
 New Carpets, Vintage European
 Not mutually exclusive
 Kilim vs. Turkish
 Some regions were over-represented and over-developed
 15 Persian Rug categories
 4 Indian Rug categories
 While others were very general
 Kilim (no way to filter down to Moroccan Kilim, Turkish Kilim,
Persian Kilim, etc)
 American Hooked, Rag and Indian rugs all one category
IMPLEMENTATION: RUGS AND CARPETS
KEY LEARNINGS
 Classification errors have decreased
 Feedback:
 Easier navigation for buyers, better browse experience
 Easier upload process for dealers, less time to upload
per item
 Easier review process for curation team, less edits
needed
 Google Analytics tracking shows increased traffic to
category landing pages
KEY LEARNINGS
 Due diligence
 Research, ask, document, ask someone else
 Communicate to stakeholders, get them on board, address
their concerns
 Plan
 Cost, resources, (timing)?
 Identify dependencies
 Test
 User studies (beta testing), identify use cases
 Launch!
 Implement your plan
 Gather Feedback
 Establish modes of communication, suggestions, complaints
 Iterate
 Improve
THANK YOU!
Tweet: #slataxo
Contact me:
miraidam@gmail.com
@MiraidaM

Weitere ähnliche Inhalte

Andere mochten auch

Taxonomy Development and Digital Projects
Taxonomy Development and Digital ProjectsTaxonomy Development and Digital Projects
Taxonomy Development and Digital Projects daniela barbosa
 
Taxonomy and UX lessons learned for e-commerce
Taxonomy and UX lessons learned for e-commerceTaxonomy and UX lessons learned for e-commerce
Taxonomy and UX lessons learned for e-commerceGary Carlson
 
Taxonomy Displays: Bridging UX & Taxonomy Design
Taxonomy Displays: Bridging UX & Taxonomy DesignTaxonomy Displays: Bridging UX & Taxonomy Design
Taxonomy Displays: Bridging UX & Taxonomy DesignHeather Hedden
 
Taxonomies for Text Analytics and Auto-indexing
Taxonomies for Text Analytics and Auto-indexingTaxonomies for Text Analytics and Auto-indexing
Taxonomies for Text Analytics and Auto-indexingHeather Hedden
 
Shop vertical classification - Meetup Presentation
Shop vertical classification - Meetup PresentationShop vertical classification - Meetup Presentation
Shop vertical classification - Meetup Presentationprevota
 
Taming taxonomy—a practical intro
Taming taxonomy—a practical introTaming taxonomy—a practical intro
Taming taxonomy—a practical introAlberta Soranzo
 
Taxonomies and Folksonomies
Taxonomies and FolksonomiesTaxonomies and Folksonomies
Taxonomies and FolksonomiesHeather Hedden
 
Taxonomy, ontology, folksonomies & SKOS.
Taxonomy, ontology, folksonomies & SKOS.Taxonomy, ontology, folksonomies & SKOS.
Taxonomy, ontology, folksonomies & SKOS.Janet Leu
 
Understanding Website Taxonomy
Understanding Website TaxonomyUnderstanding Website Taxonomy
Understanding Website TaxonomyIksula
 
Taxonomy Is User Experience
Taxonomy Is User ExperienceTaxonomy Is User Experience
Taxonomy Is User ExperienceDave Cooksey
 
Enterprise Knowledge - Taxonomy Design Best Practices and Methodology
Enterprise Knowledge - Taxonomy Design Best Practices and MethodologyEnterprise Knowledge - Taxonomy Design Best Practices and Methodology
Enterprise Knowledge - Taxonomy Design Best Practices and MethodologyEnterprise Knowledge
 
Taxonomies and Metadata in Information Architecture
Taxonomies and Metadata in Information ArchitectureTaxonomies and Metadata in Information Architecture
Taxonomies and Metadata in Information ArchitectureAccess Innovations, Inc.
 
7 Machine Learning techniques in pratice in a Startup (Robson Motta - WIAMS U...
7 Machine Learning techniques in pratice in a Startup (Robson Motta - WIAMS U...7 Machine Learning techniques in pratice in a Startup (Robson Motta - WIAMS U...
7 Machine Learning techniques in pratice in a Startup (Robson Motta - WIAMS U...Robson Motta
 

Andere mochten auch (18)

User-Driven Taxonomies
User-Driven TaxonomiesUser-Driven Taxonomies
User-Driven Taxonomies
 
Taxonomy Development and Digital Projects
Taxonomy Development and Digital ProjectsTaxonomy Development and Digital Projects
Taxonomy Development and Digital Projects
 
Taxonomy and UX lessons learned for e-commerce
Taxonomy and UX lessons learned for e-commerceTaxonomy and UX lessons learned for e-commerce
Taxonomy and UX lessons learned for e-commerce
 
Taxonomy Displays: Bridging UX & Taxonomy Design
Taxonomy Displays: Bridging UX & Taxonomy DesignTaxonomy Displays: Bridging UX & Taxonomy Design
Taxonomy Displays: Bridging UX & Taxonomy Design
 
E-Commerce Taxonomies
E-Commerce TaxonomiesE-Commerce Taxonomies
E-Commerce Taxonomies
 
Taxonomies for Text Analytics and Auto-indexing
Taxonomies for Text Analytics and Auto-indexingTaxonomies for Text Analytics and Auto-indexing
Taxonomies for Text Analytics and Auto-indexing
 
Shop vertical classification - Meetup Presentation
Shop vertical classification - Meetup PresentationShop vertical classification - Meetup Presentation
Shop vertical classification - Meetup Presentation
 
Taxonomy Governance and Iteration
Taxonomy Governance and IterationTaxonomy Governance and Iteration
Taxonomy Governance and Iteration
 
Taming taxonomy—a practical intro
Taming taxonomy—a practical introTaming taxonomy—a practical intro
Taming taxonomy—a practical intro
 
Taxonomies and Folksonomies
Taxonomies and FolksonomiesTaxonomies and Folksonomies
Taxonomies and Folksonomies
 
Taxonomy, ontology, folksonomies & SKOS.
Taxonomy, ontology, folksonomies & SKOS.Taxonomy, ontology, folksonomies & SKOS.
Taxonomy, ontology, folksonomies & SKOS.
 
Taxonomy And Metadata
Taxonomy And MetadataTaxonomy And Metadata
Taxonomy And Metadata
 
Understanding Website Taxonomy
Understanding Website TaxonomyUnderstanding Website Taxonomy
Understanding Website Taxonomy
 
Taxonomy Is User Experience
Taxonomy Is User ExperienceTaxonomy Is User Experience
Taxonomy Is User Experience
 
Enterprise Knowledge - Taxonomy Design Best Practices and Methodology
Enterprise Knowledge - Taxonomy Design Best Practices and MethodologyEnterprise Knowledge - Taxonomy Design Best Practices and Methodology
Enterprise Knowledge - Taxonomy Design Best Practices and Methodology
 
Taxonomies and Metadata in Information Architecture
Taxonomies and Metadata in Information ArchitectureTaxonomies and Metadata in Information Architecture
Taxonomies and Metadata in Information Architecture
 
Metadata Workshop
Metadata WorkshopMetadata Workshop
Metadata Workshop
 
7 Machine Learning techniques in pratice in a Startup (Robson Motta - WIAMS U...
7 Machine Learning techniques in pratice in a Startup (Robson Motta - WIAMS U...7 Machine Learning techniques in pratice in a Startup (Robson Motta - WIAMS U...
7 Machine Learning techniques in pratice in a Startup (Robson Motta - WIAMS U...
 

Ähnlich wie Starting a Taxonomy Project (Presented at SLA 2013 Conference)

Akruti Sinha - Curriculum Vitae
Akruti Sinha - Curriculum VitaeAkruti Sinha - Curriculum Vitae
Akruti Sinha - Curriculum VitaeAkruti Sinha
 
Machine Learning for retail and ecommerce
Machine Learning for retail and ecommerceMachine Learning for retail and ecommerce
Machine Learning for retail and ecommerceAndrei Lopatenko
 
DESIGN & INNOVATIVE WORKSHOP FOR MEXICAN CRAFTSMEN
DESIGN & INNOVATIVE WORKSHOP  FOR MEXICAN CRAFTSMEN DESIGN & INNOVATIVE WORKSHOP  FOR MEXICAN CRAFTSMEN
DESIGN & INNOVATIVE WORKSHOP FOR MEXICAN CRAFTSMEN Diana Albarran Gonzalez
 
Startup of product brand - Hera
Startup of product brand - HeraStartup of product brand - Hera
Startup of product brand - HeraKranthi Manthri
 
Jump-Starting Data Standards I: Launching a Data Clean-Up Program
Jump-Starting Data Standards I: Launching a Data Clean-Up ProgramJump-Starting Data Standards I: Launching a Data Clean-Up Program
Jump-Starting Data Standards I: Launching a Data Clean-Up ProgramCollectiveImagination
 
Component content 101 - Noz Urbina
Component content 101 - Noz UrbinaComponent content 101 - Noz Urbina
Component content 101 - Noz UrbinaNoz Urbina
 
eBay Search Query Intent
eBay Search Query IntenteBay Search Query Intent
eBay Search Query IntentBrian Johnson
 
Trends In Garment Decoration
Trends In Garment DecorationTrends In Garment Decoration
Trends In Garment DecorationMartinBorley
 
Macro and micro level analysis of apparel design process
Macro and micro level analysis of apparel design processMacro and micro level analysis of apparel design process
Macro and micro level analysis of apparel design processShweta Iyer
 
Nuage Designs Marketing Insights
Nuage Designs Marketing InsightsNuage Designs Marketing Insights
Nuage Designs Marketing InsightsZaira Vallejo
 
Iksula Content Solutions
Iksula Content SolutionsIksula Content Solutions
Iksula Content SolutionsIksula
 
Multilingual Strategy Case Study
Multilingual Strategy Case Study Multilingual Strategy Case Study
Multilingual Strategy Case Study Gemma Fontane
 
Understanding Taxonomy, Drupal Camp Colorado, June 2009
Understanding Taxonomy, Drupal Camp Colorado, June 2009Understanding Taxonomy, Drupal Camp Colorado, June 2009
Understanding Taxonomy, Drupal Camp Colorado, June 2009David Lanier
 
Search Patterns: An Early Talk
Search Patterns: An Early TalkSearch Patterns: An Early Talk
Search Patterns: An Early TalkPeter Morville
 
HomeHub Investor Presentation - 2014-02-18
HomeHub Investor Presentation - 2014-02-18HomeHub Investor Presentation - 2014-02-18
HomeHub Investor Presentation - 2014-02-18David Albert
 

Ähnlich wie Starting a Taxonomy Project (Presented at SLA 2013 Conference) (20)

Akruti Sinha - Curriculum Vitae
Akruti Sinha - Curriculum VitaeAkruti Sinha - Curriculum Vitae
Akruti Sinha - Curriculum Vitae
 
Machine Learning for retail and ecommerce
Machine Learning for retail and ecommerceMachine Learning for retail and ecommerce
Machine Learning for retail and ecommerce
 
Taxonomies for Users
Taxonomies for UsersTaxonomies for Users
Taxonomies for Users
 
DESIGN & INNOVATIVE WORKSHOP FOR MEXICAN CRAFTSMEN
DESIGN & INNOVATIVE WORKSHOP  FOR MEXICAN CRAFTSMEN DESIGN & INNOVATIVE WORKSHOP  FOR MEXICAN CRAFTSMEN
DESIGN & INNOVATIVE WORKSHOP FOR MEXICAN CRAFTSMEN
 
IKEA Case Study
IKEA Case StudyIKEA Case Study
IKEA Case Study
 
Talk ebay altaweel
Talk ebay altaweelTalk ebay altaweel
Talk ebay altaweel
 
Startup of product brand - Hera
Startup of product brand - HeraStartup of product brand - Hera
Startup of product brand - Hera
 
SWOT Analysis
SWOT AnalysisSWOT Analysis
SWOT Analysis
 
Jump-Starting Data Standards I: Launching a Data Clean-Up Program
Jump-Starting Data Standards I: Launching a Data Clean-Up ProgramJump-Starting Data Standards I: Launching a Data Clean-Up Program
Jump-Starting Data Standards I: Launching a Data Clean-Up Program
 
Component content 101 - Noz Urbina
Component content 101 - Noz UrbinaComponent content 101 - Noz Urbina
Component content 101 - Noz Urbina
 
eBay Search Query Intent
eBay Search Query IntenteBay Search Query Intent
eBay Search Query Intent
 
Trends In Garment Decoration
Trends In Garment DecorationTrends In Garment Decoration
Trends In Garment Decoration
 
Macro and micro level analysis of apparel design process
Macro and micro level analysis of apparel design processMacro and micro level analysis of apparel design process
Macro and micro level analysis of apparel design process
 
SURVEY PRESENTATION
SURVEY PRESENTATIONSURVEY PRESENTATION
SURVEY PRESENTATION
 
Nuage Designs Marketing Insights
Nuage Designs Marketing InsightsNuage Designs Marketing Insights
Nuage Designs Marketing Insights
 
Iksula Content Solutions
Iksula Content SolutionsIksula Content Solutions
Iksula Content Solutions
 
Multilingual Strategy Case Study
Multilingual Strategy Case Study Multilingual Strategy Case Study
Multilingual Strategy Case Study
 
Understanding Taxonomy, Drupal Camp Colorado, June 2009
Understanding Taxonomy, Drupal Camp Colorado, June 2009Understanding Taxonomy, Drupal Camp Colorado, June 2009
Understanding Taxonomy, Drupal Camp Colorado, June 2009
 
Search Patterns: An Early Talk
Search Patterns: An Early TalkSearch Patterns: An Early Talk
Search Patterns: An Early Talk
 
HomeHub Investor Presentation - 2014-02-18
HomeHub Investor Presentation - 2014-02-18HomeHub Investor Presentation - 2014-02-18
HomeHub Investor Presentation - 2014-02-18
 

Mehr von Miraida Morales

Easy-to-Read Health Materials (NLM Boost Box)
Easy-to-Read Health Materials (NLM Boost Box)Easy-to-Read Health Materials (NLM Boost Box)
Easy-to-Read Health Materials (NLM Boost Box)Miraida Morales
 
Methodological Challenges Related to Working with Vulnerable Participants
Methodological Challenges Related to Working with Vulnerable ParticipantsMethodological Challenges Related to Working with Vulnerable Participants
Methodological Challenges Related to Working with Vulnerable ParticipantsMiraida Morales
 
CRE Grad Forum 2015 presentation
CRE Grad Forum 2015 presentationCRE Grad Forum 2015 presentation
CRE Grad Forum 2015 presentationMiraida Morales
 
Digital Library Toolkit: Building a small digital library on a shoestring
Digital Library Toolkit: Building a small digital library on a shoestringDigital Library Toolkit: Building a small digital library on a shoestring
Digital Library Toolkit: Building a small digital library on a shoestringMiraida Morales
 
Buried Treasure: NJLA Adult Services Forum Presentation
Buried Treasure: NJLA Adult Services Forum PresentationBuried Treasure: NJLA Adult Services Forum Presentation
Buried Treasure: NJLA Adult Services Forum PresentationMiraida Morales
 

Mehr von Miraida Morales (6)

Easy-to-Read Health Materials (NLM Boost Box)
Easy-to-Read Health Materials (NLM Boost Box)Easy-to-Read Health Materials (NLM Boost Box)
Easy-to-Read Health Materials (NLM Boost Box)
 
Methodological Challenges Related to Working with Vulnerable Participants
Methodological Challenges Related to Working with Vulnerable ParticipantsMethodological Challenges Related to Working with Vulnerable Participants
Methodological Challenges Related to Working with Vulnerable Participants
 
SymposiumPoster2015
SymposiumPoster2015SymposiumPoster2015
SymposiumPoster2015
 
CRE Grad Forum 2015 presentation
CRE Grad Forum 2015 presentationCRE Grad Forum 2015 presentation
CRE Grad Forum 2015 presentation
 
Digital Library Toolkit: Building a small digital library on a shoestring
Digital Library Toolkit: Building a small digital library on a shoestringDigital Library Toolkit: Building a small digital library on a shoestring
Digital Library Toolkit: Building a small digital library on a shoestring
 
Buried Treasure: NJLA Adult Services Forum Presentation
Buried Treasure: NJLA Adult Services Forum PresentationBuried Treasure: NJLA Adult Services Forum Presentation
Buried Treasure: NJLA Adult Services Forum Presentation
 

Kürzlich hochgeladen

CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):comworks
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Mattias Andersson
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time ClashPowerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clashcharlottematthew16
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxNavinnSomaal
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionDilum Bandara
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfRankYa
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Enterprise Knowledge
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfPrecisely
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxhariprasad279825
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 

Kürzlich hochgeladen (20)

CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time ClashPowerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clash
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptx
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An Introduction
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdf
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptx
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 

Starting a Taxonomy Project (Presented at SLA 2013 Conference)

  • 1. STARTING A TAXONOMY PROJECT Case Study: eCommerce Product Taxonomy #slataxo Miraida Morales | miraidam@gmail.com | @MiraidaM
  • 2. OUTLINE  Company Background  User Need  Challenges  Project Goals  Chosen Method  Implementation  Key Learnings
  • 3. COMPANY BACKGROUND o eCommerce site dedicated to one-of-a-kind design, antiques and luxury goods o Marketplace platform of 2000 dealers = 100% user generated content o 11 years old = Lots of user data o Initiative to improve the Buyer Experience
  • 6. USER NEED  Implement a classification system that allows dealers to describe their items accurately AND  Allows buyers to easily find what they are looking for  Without overburdening the user
  • 7. CHALLENGES  Ignore MECE principle  Mutually Exclusive, Collectively Exhaustive (McKinsey)  a way of grouping information used in Consulting, but these principles are useful for creating categories  Inconsistent label naming strategy  Glass and Pitchers under Serving  Bronzes, Carvings, Lacquer under Other  Redundant categories  Chairs, Armchairs and Side Chairs are different subcategories under Seating  Duplicate categories  Desks as a subcategory under Tables and under Case Pieces  Rugs under Carpets and under Other  Like items and similar categories not grouped together  Tea Canisters under Other; Tea Sets under Serving  Tobacco Accessories under Other; Ashtrays under Serving  Inkwells and Desk Accessories are separate categories
  • 8. CHALLENGES  Misrepresented categories  Antiquities under Folk Art  Tribal Art under Folk Art  Figurines under Serving  Ashtrays under Serving  Category simply called Other, including 64 subcategories – a mix of furniture and decorative items  Approximately 2000 new items uploaded every week & classified by users  Inventory constantly changing  Diversity of users uploading content  Differing levels and areas of expertise, technology aptitude, etc  Increasing number of dealers based outside the US  Language problems; upload tools not localized
  • 9. PROJECT GOALS  Improve “findability”  allow buyers to find relevant/desired items on the site = increase conversion (click-through, contact dealer, sales)  introduce new users to the site (by improving SEO)  Reduce number of miss-categorized items  Approximately 35%-40% of items are uploaded with a categorization error every week  Avoid category gaps that lead to unclassifiable items  Ex: Sewing tables  Create sustainable structure that can support growth and future inventory needs
  • 10. METHOD  What are we describing? (Scope)  Conducted audit of inventory on the site  100,000+ furniture items, lighting elements, decorative objects, collectibles, architectural elements  Settees, chandeliers, pier mirrors, antique tall case clocks, carnival art, trade signs, carpets, creamware tea sets, art furniture  Reviewed attributes and identified attribute gaps  Antiques, modern and contemporary pieces  By well-known makers and unknown provenance (attribution)  Variable/non-standard sizes (e.g. scatter sizes for tribal rugs)  Materials and techniques (e.g. burl wood, eglomized, gilt, flat weave, hooked)  Pieces from all over the world (e.g. French antiques, English Silver, Turkish Rugs)
  • 11. SOFA OR COUCH?  What do others call it?  Competitive analysis  Auction houses, similar design/décor sites  Consulted with experts and top dealers for each category  Appraisers, resources such as Yale Furniture Study, Period rooms at Brooklyn Public Library  Researched controlled vocabularies:  Getty ULAN, Getty AAT, Categories for the Description of Works of Art, Geographic name lists
  • 12. DIVAN, SETTEE, CANAPÉ, CHESTERFIELD, LOVESEAT, BENCH, SECTIONAL…  How do buyers look for it?  Keyword research  Google Adwords Keyword tool  Google Trends  Site-based search keyword analysis  Search logs  User studies  Real-time, monitored interview of users given a task to perform on our site while we observe and record (audio, screenshots, notes)
  • 13. IMPLEMENTATION  Update database, tables, relationships between items, categories and attributes  Update classification tools  Used by dealers and  Used by internal admin (curation team, category managers, me)  Reclassify existing inventory  Introduce controlled vocabularies for attributes  Creator names, Country of Origin, Condition & Wear, Styles  Notify dealers about the changes to their tool and about new classification structure
  • 14. IMPLEMENTATION  Improving search & browse experience  Implement keyword-rich meta-tags, meta titles on html pages  Implement synonym rings for search (in development)  Include popular search terms for search auto-complete feature  Reduces 0 results by avoiding typos, ambiguous terms, etc  Implement Product schema: http://schema.org/Product  Implement Goodrelations schema: http://www.heppnetz.de/ontologies/goodrelations/v1.htm l  Implement redirects, canonical tags, update sitemap  Buillotte lamps -> table lamps
  • 15. IMPLEMENTATION  For this site, implementation and maintenance was manual for many reasons.  Cost  Database architecture re-design was simultaneous  Reticence on the part of site owners  Other options:  Automated systems for classification based on descriptive content  Using search feature to allow dealers to query site to help them place hard-to-classify items near relevant items  Develop in-house taxonomy management/development tool  License a taxonomy development tool
  • 16. RUGS OR CARPETS?  Semantics  How are they described?  By Origin (Indian, Turkish, Persian, Navajo, Irish) and Region (Amritsar, Agra, Donegal)  By Technique (flat-weave, hooked, knotted-pile, hand-woven)  By Style (Herati design, Arts and Crafts, Art Nouveau)  What should we call them?  Traditionally, rugs are smaller than carpets  Today, we use „carpet‟ often to mean „wall-to-wall carpeting‟; this definition does not apply to antique/collectible carpets  Origin/Regional designations also encapsulate styles, techniques and colors common to the region
  • 17. KHOTAN RUGS  From ancient city of Khotan in present day Uygur Autonomous Region of Xinjiang (Chinese Turkistan)  Also known as Samarkand Rugs  Incorporate Asian motifs, lattice- patterns  Rugs and Carpets (BT)  Central Asian (NT) • Khotan Rugs (NT) • Samarkand Rugs (VT)
  • 18. INDIAN AGRA RUG  From city of Agra (TajMahal) for Mughal Empire, also produced in Lahore  Back in vogue during British colonial period  Designs often based on classical Persian motifs  Rugs and Carpets (BT)  Indian Rugs (NT) • Indian Agra Rugs (NT) • Moghul Carpets (VT)
  • 19. TURKISH KILIM RUG  Kilims can be Persian, Turkish, Moroccan, from the Balkans  Flat-woven (pile-less)  Tapestry style designs, geometric  Rugs and Carpets (BT)  Turkish Rugs (NT) • Turkish Kilim Rugs (NT) • MoroccanKilim (RT)
  • 20. SPANISH SAVONNERIE CARPET  Savonnerie Carpets originally French, inspired by Turkish rugs  Knotted-pile, Ghiordes knot  Floral motifs, rococo elements  Rugs and Carpets (BT)  Western European Rugs (NT) • Spanish Savonnerie Rugs (NT) • French Savonnerie Rugs (RT)
  • 21. IRISH DONEGAL CARPET  From County Donegal, Ireland  Wool, handwoven  Celtic designs, Arts & Crafts, Art Nouveau, border designs  Rugs and Carpets (BT)  Western European Rugs (NT) • Spanish Rugs (NT) • Irish Rugs (NT) • Donegal Carpets(NT)
  • 22. NAVAJO RUG  Tribal weaving from Four Corners region of US  Flat tapestry-woven, wool  Geometric patterns  Rugs and Carpets (BT)  North and South American Rugs (NT) • Navajo Rugs (NT) • American Hooked Rugs (NT)
  • 23. AMERICAN HOOKED RUG  From Northeast US and Eastern Canada  Hooked, pile, made from linen, jute, flax, hemp  Floral designs, scenes, people  Rugs and Carpets (BT)  North and South American Rugs (NT) • American Hooked Rugs (NT) • Navajo Rugs (NT)
  • 24. IMPLEMENTATION: RUGS AND CARPETS  Mix of Styles, Periods, Shapes and Regions  Modernist, Art Deco, Arts and Crafts  Chinese  Runners vs. Wide Runners vs. Turkish Kilim Runners  New Carpets, Vintage European  Not mutually exclusive  Kilim vs. Turkish  Some regions were over-represented and over-developed  15 Persian Rug categories  4 Indian Rug categories  While others were very general  Kilim (no way to filter down to Moroccan Kilim, Turkish Kilim, Persian Kilim, etc)  American Hooked, Rag and Indian rugs all one category
  • 26. KEY LEARNINGS  Classification errors have decreased  Feedback:  Easier navigation for buyers, better browse experience  Easier upload process for dealers, less time to upload per item  Easier review process for curation team, less edits needed  Google Analytics tracking shows increased traffic to category landing pages
  • 27. KEY LEARNINGS  Due diligence  Research, ask, document, ask someone else  Communicate to stakeholders, get them on board, address their concerns  Plan  Cost, resources, (timing)?  Identify dependencies  Test  User studies (beta testing), identify use cases  Launch!  Implement your plan  Gather Feedback  Establish modes of communication, suggestions, complaints  Iterate  Improve
  • 28. THANK YOU! Tweet: #slataxo Contact me: miraidam@gmail.com @MiraidaM

Hinweis der Redaktion

  1. conversion rate is the proportion of visitors to a website who take action to go beyond a casual content view or website visit, as a result of subtle or direct requests from marketers, advertisers, and content creators.(SEO) is the process of affecting the visibility of a website or a web page in a search engine's "natural" or un-paid ("organic") search results.
  2. CDWA - Guidelines for the description of art objects and images, including a discussion of issues involved in building art information system; includes a taxonomy comrising 532 categories and subcategories.
  3. Schema.org – provides a collection of schemas, i.e. html tags, that webmasters can use to markup their pages in ways recognized by major search providers. Search engines including Bing, Google, Yahoo! and Yandex rely on this markup to improve the display of search results, making it easier for people to find the right web pages. Many sites are generated from structured data, which is often stored in databases. GoodRelations is a standardized vocabulary (also known as "schema", "data dictionary", or "ontology") for product, price, store, and company data that can (1) be embedded into existing static and dynamic Web pages and that (2) can be processed by other computers. This increases the visibility of your products and services in the latest generation of search engines, recommender systems, and other novel applications.A canonical tag is an HTML element that helps webmasters prevent duplicate content issues by specifying the "canonical", or "preferred", version of a web page[1][2] as part of search engine optimization.
  4. Rugs and Carpets went from 38 subcategories (narrower terms) to 1014 subcategories of Persian Rugs!Changed name from Carpets to ‘Rugs and Carpets
  5. Rugs and Carpets went from 38 subcategories (narrower terms) to 1014 subcategories of Persian Rugs!Changed name from Carpets to ‘Rugs and Carpets