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TAXONOMY:
ADVANCED CONTENT HERO
Laura Creekmore • @lauracreekmore
SLIDES HERE:
https://slideshare.net/lauracreekmore
PHOTO FROM
DTS
AUTOMAGICALLY
My favorite internet word
CHALLENGES FOR
MARKETERS
➤Extremely cluttered
landscape
➤Burdensome requirements
➤Endless content variations
➤Ineffective and expensive to
adapt for every channel
➤Channels not aligned
TRADITIONAL
SOLUTION
IT DOESN’T MEET YOUR
CUSTOMER’S NEEDS
GET OUT OF THE
CAMPAIGN BUSINESS…
GET INTO THE
RELATIONSHIP BUSINESS
REBUILD YOUR MINDSET
WHAT
PROBLEM IS
MY CUSTOMER
TRYING TO
SOLVE?
HOW CAN I
SUPPORT
THEM?
DIGITAL
PROCESS
STANDARD
CONTENT WORKFLOW
AUDIENCE STRATEGY OPERATIONS ANALYSIS GOVERNANCE
Identify
customers,
prospects,
people
Identify their
goals and
needs
Identify your
goals and find
synergy
Identify tools,
channels you
can use
Design
systems that
meet your
goals +
audience goals
Use systems to
create and
publish
content
Evaluate
success toward
goals
Iterate
Determine
ongoing
decisions to be
made
Define
framework for
decisions
Use
framework
ADVANCED
CONTENT WORKFLOW
AUDIENCE STRATEGY OPERATIONS ANALYSIS GOVERNANCE
Identify
customers,
prospects,
people
Identify their
goals and
needs
Identify your
goals and find
synergy
Identify tools,
channels you
can use
Design
systems that
meet your
goals +
audience goals
Use systems to
create and
publish
content
Evaluate
success toward
goals
Iterate
Determine
ongoing
decisions to be
made
Define
framework for
decisions
Use
framework
THE DIFFERENCE IS IN
THE FILLING
•CHATBOT [AI OR NOT]
•VOICE SKILLS
•AI
•ECOMMERCE
ADVANCED
CONTENT OPERATIONS
DIGITAL CHATBOTS VOICE SKILLS AI-DRIVEN ECOMMERCE
Topics
Formats
Write
Publish
Define
information
sets to support
conversations
Build
conversation
triggers
Test, rewrite!
Test, rewrite!
Determine
interactions
useful in voice
environment
Design
content for
common voice
interactions
Test! Test!
Test! Test!
Promote
Determine
where data
and needs
intersect
Jumpstart
with
taxonomy/
ontology/
semantic
content
Train! Train!
Train! Train!
Document
buyer’s
journey
Determine
content need
Structure to
create/store/
deliver content
Design
customer
experience
ADVANCED
CONTENT OPERATIONS
DIGITAL CHATBOTS VOICE SKILLS AI-DRIVEN ECOMMERCE
Topics
Formats
Write
Publish
Define
information
sets to support
conversations
Build
conversation
triggers
Test, rewrite!
Test, rewrite!
Determine
interactions
useful in voice
environment
Design
content for
common voice
interactions
Test! Test!
Test! Test!
Promote
Determine
where data
and needs
intersect
Jumpstart
with
taxonomy/
ontology/
semantic
content
Train! Train!
Train! Train!
Document
buyer’s
journey
Determine
content need
Structure to
create/store/
deliver content
Design
customer
experience
ADVANCED
CONTENT OPERATIONS
DIGITAL CHATBOTS VOICE SKILLS AI-DRIVEN ECOMMERCE
Topics
Formats
Write
Publish
Define
information
sets to support
conversations
Build
conversation
triggers
Test, rewrite!
Test, rewrite!
Determine
interactions
useful in voice
environment
Design
content for
common voice
interactions
Test! Test!
Test! Test!
Promote
Determine
where data
and needs
intersect
Jumpstart
with
taxonomy/
ontology/
semantic
content
Train! Train!
Train! Train!
Document
buyer’s
journey
Determine
content need
Structure to
create/store/
deliver content
Design
customer
experience
IT’S ABOUT THE
STRUCTURE
MISCONCEPTIONS
➤Throw it all in there; Google
will sort it out.
➤I don’t need to structure it.
➤I need to structure
everything.
➤My customer will see what I
want them to see.
➤I’m starting from scratch.
TRUTHS
➤Critical to start with
customer perspective.
➤You can’t script everything.
➤Creating the domain and
content model pays off.
➤Metadata for the win.
➤You should test some more.
WHY DOES IA MATTER
FOR AI?
You shortcut the pattern recognition.
TERMINOLOGY
INTERLUDE
DOMAIN MODEL
What it is: An organized way to describe the topics and
information related to your [business, industry, area of interest]
How you create it: Look for existing models, create your own
Format: No specific format. Could be an outline, a set of topics
and descriptions
What it’s good for: Overlay on your customer journey to find
where content is needed. A starting point for any content
strategy.
CONTENT MODELWhat it is: A structured representation of content types and
their relationships. The content version of a data model.
How you create it: Organize content types, determine
internal structure of each. Create metadata to make the system
work.
Format: Represented by fields in a content management
system. Designed in variety of software.
What it’s good for: Designing structure within a body of
content. Good starting point to write, even better for
determining how content can be reused.
HOW-TO: DOMAIN AND
CONTENT MODELS
KNOWLEDGE BASE
What it is: A group of electronic documents on a set of topics,
ideally in some organized form.
How you create it: Assemble all your stuff!
Format: Ideally, documents are text with metadata and
semantic structure. YMMV.
What it’s good for: Base of content for AI, chatbots.
WATCH OUT FOR:
TAXONOMY
What it is: A hierarchical structure for organizing information.
Could be topics, products, whatevs.
How you create it: Build categories that make sense. Create
metadata to extend the structure into other uses.
Format: Spreadsheet, folder structure, semantic tags, XML,
special software…possibilities are endless.
What it’s good for: Organizing items like content, products.
Structural base for AI, chatbot content, more.
HOW-TO: TAXONOMY
ONTOLOGY
What it is: A structure for demonstrating relationships. Could be
topics, products, whatevs.
How you create it: Group like entities, outline relationships
between them. Create metadata to extend the structure into other
uses.
Format: Semantic tags, XML, special software…many possibilities.
What it’s good for: Organizing items like content, products, and
especially complex information. Structural base for AI, chatbot
content, more.
KNOWLEDGE GRAPH
What it is: Google presents
structured data in a box on the
right side of the search results
page.
How you create it: Put good
metadata on your content, be
liked by Google’s algorithm.
What it’s mixed up with:
Non-branded information
representations.
WHATEVER YOU
CALL IT
REBUILD YOUR MINDSET
WHAT
PROBLEM IS
MY CUSTOMER
TRYING TO
SOLVE?
HOW CAN I
SUPPORT
THEM?
COORDINATION
AND CAPABILITIES
➤Does any other system need to
understand your structure?
➤Do you need to map to any
other system?
➤Does your industry have a
standard structure?
➤What can your tech system do
now?
ADVANCED CONTENT
OPERATIONS: CHAT & VOICE
CHATBOTS VOICE SKILLS
Define topics
covered
Define
unsuccessful
interactions
Q & A/
Triggers
Supporting
content
Similar to
chatbots, but add
challenges of
speech recognition
Evaluate voice vs.
typed conversation
ADVANCED CONTENT
OPERATIONS: AI
Define
knowledge base
Create
taxonomy/
ontology
Add semantic
structure
FOR WHAT?
➤PPC program management
➤Topic and editorial calendar recommendations
➤Competitor analysis
➤The Holy Grail: Content creation?
HOW MUCH DATA
DO I NEED?
No, even more.
Still more.
More than that, even.
Current experience shows that AI
initiatives often fail due to the lack of
appropriate data or low data quality.
--Introducing Semantic AI white paper
Pool Party
WHAT KIND OF
DATA?
ADVANCED CONTENT
OPERATIONS: ECOMMERCE
Determine
integrations
Define existing
structures
Structure at least
as granular as the
most granular
system
Structure to
create/store/
deliver content
FOR WHAT?
➤Integration between all suppliers/retailers
➤Make it easy to find and buy your products
➤Create faceted navigation, search filters
➤Create comparison tools, rich content
experiences
WHAT YOU CAN
ORGANIZE
➤Topics
➤Articles
➤Images
➤Videos
➤Products
BUILDING A
TAXONOMY
BUILDING A TAXONOMY
GOALS INFORMATION ORGANIZATION GOVERNANCE
Manage
information well
Integrate with
other systems
Help people find
things
Support
advanced
content
What will be
covered?
How will info be
categorized?
What facets
matter?
How do you
identify the
characteristics?
Are relationships
important?
Document and
understand
integrations
Be flexible
Maintain
organizing
principles until
there’s reason
not to
Look for industry
standards
Group like things
together
Seek clarity
Use user language
for labels
Be cautious and
intentional about
redundancy
Test!
HOW-TO: CARD SORTING
BUILDING BLOCKS
OF CONTENT
THE BATTLE FOR THE
BODY FIELD
TRAINING THE CMS
KEY:
SEMANTIC
TAGGING
TIPS FOR TAGGING
➤Investigate industry
standards
➤https://schema.org
➤SKOS compliant
➤Use plain language
➤Clarity over all
STRUCTURED
CONTENT
ENABLES THE
AUTOMAGIC
My favorite internet word
RESOURCES
➤ Taxonomy in the Age of Amazon Echo. Mike
Doane, Taxonomy Bootcamp 2018
➤ Taxonomies and AI Chatbots. Gary Carlson,
Taxonomy Bootcamp 2018
➤ AI UX: 7 Principles of Designing Good AI
Products
➤ Machine Learning for Everyone
➤ Designer’s Field Guide to Data
➤ How Voice-Activated Tech Will Change Content
Marketing
➤ Opportunities for AI in Content Marketing
➤ Google’s Machine Learning Crash Course
➤ Designing Connected Content by Mike Atherton
and Carrie Hane
➤ The Human Insights Missing From Big Data,
Ted Talk by Tricia Wang
➤ Why Big Data Needs Thick Data, Medium post
by Tricia Wang
➤ Designing Bots by Amir Shevat
➤ Designing Voice User Interfaces by Cathy Pearl
➤ The Accidental Taxonomist by Heather Hedden
➤ The Battle for the Body Field article by Jeff
Eaton
➤ Training the CMS article by Eileen Webb
➤ Card Sorting by Donna Spencer
Laura Creekmore
@lauracreekmore
laura.creekmore@syndigo.com

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Taxonomy: Hero of Advanced Content - SXSW 2019

  • 1. TAXONOMY: ADVANCED CONTENT HERO Laura Creekmore • @lauracreekmore
  • 5.
  • 6. CHALLENGES FOR MARKETERS ➤Extremely cluttered landscape ➤Burdensome requirements ➤Endless content variations ➤Ineffective and expensive to adapt for every channel ➤Channels not aligned
  • 8. IT DOESN’T MEET YOUR CUSTOMER’S NEEDS
  • 9.
  • 10. GET OUT OF THE CAMPAIGN BUSINESS… GET INTO THE RELATIONSHIP BUSINESS
  • 15. STANDARD CONTENT WORKFLOW AUDIENCE STRATEGY OPERATIONS ANALYSIS GOVERNANCE Identify customers, prospects, people Identify their goals and needs Identify your goals and find synergy Identify tools, channels you can use Design systems that meet your goals + audience goals Use systems to create and publish content Evaluate success toward goals Iterate Determine ongoing decisions to be made Define framework for decisions Use framework
  • 16. ADVANCED CONTENT WORKFLOW AUDIENCE STRATEGY OPERATIONS ANALYSIS GOVERNANCE Identify customers, prospects, people Identify their goals and needs Identify your goals and find synergy Identify tools, channels you can use Design systems that meet your goals + audience goals Use systems to create and publish content Evaluate success toward goals Iterate Determine ongoing decisions to be made Define framework for decisions Use framework
  • 17. THE DIFFERENCE IS IN THE FILLING
  • 18. •CHATBOT [AI OR NOT] •VOICE SKILLS •AI •ECOMMERCE
  • 19. ADVANCED CONTENT OPERATIONS DIGITAL CHATBOTS VOICE SKILLS AI-DRIVEN ECOMMERCE Topics Formats Write Publish Define information sets to support conversations Build conversation triggers Test, rewrite! Test, rewrite! Determine interactions useful in voice environment Design content for common voice interactions Test! Test! Test! Test! Promote Determine where data and needs intersect Jumpstart with taxonomy/ ontology/ semantic content Train! Train! Train! Train! Document buyer’s journey Determine content need Structure to create/store/ deliver content Design customer experience
  • 20. ADVANCED CONTENT OPERATIONS DIGITAL CHATBOTS VOICE SKILLS AI-DRIVEN ECOMMERCE Topics Formats Write Publish Define information sets to support conversations Build conversation triggers Test, rewrite! Test, rewrite! Determine interactions useful in voice environment Design content for common voice interactions Test! Test! Test! Test! Promote Determine where data and needs intersect Jumpstart with taxonomy/ ontology/ semantic content Train! Train! Train! Train! Document buyer’s journey Determine content need Structure to create/store/ deliver content Design customer experience
  • 21. ADVANCED CONTENT OPERATIONS DIGITAL CHATBOTS VOICE SKILLS AI-DRIVEN ECOMMERCE Topics Formats Write Publish Define information sets to support conversations Build conversation triggers Test, rewrite! Test, rewrite! Determine interactions useful in voice environment Design content for common voice interactions Test! Test! Test! Test! Promote Determine where data and needs intersect Jumpstart with taxonomy/ ontology/ semantic content Train! Train! Train! Train! Document buyer’s journey Determine content need Structure to create/store/ deliver content Design customer experience IT’S ABOUT THE STRUCTURE
  • 22. MISCONCEPTIONS ➤Throw it all in there; Google will sort it out. ➤I don’t need to structure it. ➤I need to structure everything. ➤My customer will see what I want them to see. ➤I’m starting from scratch.
  • 23. TRUTHS ➤Critical to start with customer perspective. ➤You can’t script everything. ➤Creating the domain and content model pays off. ➤Metadata for the win. ➤You should test some more.
  • 24. WHY DOES IA MATTER FOR AI? You shortcut the pattern recognition.
  • 26. DOMAIN MODEL What it is: An organized way to describe the topics and information related to your [business, industry, area of interest] How you create it: Look for existing models, create your own Format: No specific format. Could be an outline, a set of topics and descriptions What it’s good for: Overlay on your customer journey to find where content is needed. A starting point for any content strategy.
  • 27. CONTENT MODELWhat it is: A structured representation of content types and their relationships. The content version of a data model. How you create it: Organize content types, determine internal structure of each. Create metadata to make the system work. Format: Represented by fields in a content management system. Designed in variety of software. What it’s good for: Designing structure within a body of content. Good starting point to write, even better for determining how content can be reused.
  • 29. KNOWLEDGE BASE What it is: A group of electronic documents on a set of topics, ideally in some organized form. How you create it: Assemble all your stuff! Format: Ideally, documents are text with metadata and semantic structure. YMMV. What it’s good for: Base of content for AI, chatbots.
  • 31. TAXONOMY What it is: A hierarchical structure for organizing information. Could be topics, products, whatevs. How you create it: Build categories that make sense. Create metadata to extend the structure into other uses. Format: Spreadsheet, folder structure, semantic tags, XML, special software…possibilities are endless. What it’s good for: Organizing items like content, products. Structural base for AI, chatbot content, more.
  • 33. ONTOLOGY What it is: A structure for demonstrating relationships. Could be topics, products, whatevs. How you create it: Group like entities, outline relationships between them. Create metadata to extend the structure into other uses. Format: Semantic tags, XML, special software…many possibilities. What it’s good for: Organizing items like content, products, and especially complex information. Structural base for AI, chatbot content, more.
  • 34. KNOWLEDGE GRAPH What it is: Google presents structured data in a box on the right side of the search results page. How you create it: Put good metadata on your content, be liked by Google’s algorithm. What it’s mixed up with: Non-branded information representations.
  • 39.
  • 40. COORDINATION AND CAPABILITIES ➤Does any other system need to understand your structure? ➤Do you need to map to any other system? ➤Does your industry have a standard structure? ➤What can your tech system do now?
  • 41. ADVANCED CONTENT OPERATIONS: CHAT & VOICE CHATBOTS VOICE SKILLS Define topics covered Define unsuccessful interactions Q & A/ Triggers Supporting content Similar to chatbots, but add challenges of speech recognition Evaluate voice vs. typed conversation
  • 42. ADVANCED CONTENT OPERATIONS: AI Define knowledge base Create taxonomy/ ontology Add semantic structure FOR WHAT? ➤PPC program management ➤Topic and editorial calendar recommendations ➤Competitor analysis ➤The Holy Grail: Content creation?
  • 43. HOW MUCH DATA DO I NEED? No, even more. Still more. More than that, even.
  • 44. Current experience shows that AI initiatives often fail due to the lack of appropriate data or low data quality. --Introducing Semantic AI white paper Pool Party
  • 46. ADVANCED CONTENT OPERATIONS: ECOMMERCE Determine integrations Define existing structures Structure at least as granular as the most granular system Structure to create/store/ deliver content FOR WHAT? ➤Integration between all suppliers/retailers ➤Make it easy to find and buy your products ➤Create faceted navigation, search filters ➤Create comparison tools, rich content experiences
  • 49. BUILDING A TAXONOMY GOALS INFORMATION ORGANIZATION GOVERNANCE Manage information well Integrate with other systems Help people find things Support advanced content What will be covered? How will info be categorized? What facets matter? How do you identify the characteristics? Are relationships important? Document and understand integrations Be flexible Maintain organizing principles until there’s reason not to Look for industry standards Group like things together Seek clarity Use user language for labels Be cautious and intentional about redundancy Test!
  • 52. THE BATTLE FOR THE BODY FIELD
  • 54.
  • 56. TIPS FOR TAGGING ➤Investigate industry standards ➤https://schema.org ➤SKOS compliant ➤Use plain language ➤Clarity over all
  • 58. RESOURCES ➤ Taxonomy in the Age of Amazon Echo. Mike Doane, Taxonomy Bootcamp 2018 ➤ Taxonomies and AI Chatbots. Gary Carlson, Taxonomy Bootcamp 2018 ➤ AI UX: 7 Principles of Designing Good AI Products ➤ Machine Learning for Everyone ➤ Designer’s Field Guide to Data ➤ How Voice-Activated Tech Will Change Content Marketing ➤ Opportunities for AI in Content Marketing ➤ Google’s Machine Learning Crash Course ➤ Designing Connected Content by Mike Atherton and Carrie Hane ➤ The Human Insights Missing From Big Data, Ted Talk by Tricia Wang ➤ Why Big Data Needs Thick Data, Medium post by Tricia Wang ➤ Designing Bots by Amir Shevat ➤ Designing Voice User Interfaces by Cathy Pearl ➤ The Accidental Taxonomist by Heather Hedden ➤ The Battle for the Body Field article by Jeff Eaton ➤ Training the CMS article by Eileen Webb ➤ Card Sorting by Donna Spencer