Optimizing content for findability requires efforts across business, user, information, and organizational dimensions. Key aspects include establishing governance through search analytics and metadata standards, involving users through testing and feedback, and ensuring high quality information through content cleanup and structured metadata. Continuous improvement requires measuring success metrics and taking actionable steps informed by search analytics.

1. OPTIMISING YOUR CONTENT FOR
FINDABILITY
Kristian Norling, JBoye 2012, 6 November, Aarhus, Denmark

2. #jboye12
@kristiannorling
@!ndwise

3. Introduction
• Who is here?
• Your expectations?
• Kristian?
• 3 hours
• One 20 minute break ≈ 10.20
• Lifetime answer Guarantee on this class

4. THE ENTERPRISE SEARCH AND
FINDABILITY SURVEY/REPORT
SIGN-UP & DOWNLOAD 2012 REPORT

5. Description
As the amount of content continues to increase, new approaches are
required to provide good user experiences. Findability has been
introduced as a new term among content strategists and information
architects and is most easily explained as :
“A state where all information is !ndable and an approach to reaching
that state.”
Search technology is readily used to make information !ndable, but as
many have realized technology alone is unfortunately not enough. To
achieve !ndability additional activities across several important
dimensions such as business, user, information and organisation are
needed.

6. Description
Search engine optimisation is one aspect of !ndability and many of the
principles from SEO works in a intranet or website search context.
Getting !ndability to work well for your website or intranet is a
di#cult task, that needs continuous work.
In this tutorial you will take a deep dive into the many aspects of
!ndability, with some good practices on how to improve !ndability.

7. Brief Outline
We will start some very brief theory and then use real examples and
also talk about what organisations that are most satis!ed with their
!ndability do.
Topics
•Enterprise Search Engines vs Web Search
•Governance
•Organisation
•User involvement
•Optimise Content for !ndability
•Metadata
•Search Analytics

8. IS IT EASY TO FIND THE RIGHT
INFORMATION WITHIN YOUR
ORGANISATION TODAY?
Source: The Enterprise Search and Findability Report 2012

9. EUROPE
77%
MODERATELY/VERY HARD

10. WHAT ARE THE OBSTACLES
TO FINDING THE RIGHT
INFORMATION?

11. EUROPE
64.2% POOR SEARCH FUNCTIONALITY
47.7% LACK OF ADEQUATE TAGS
48.6% INCONSISTENCY IN HOW WE TAG
CONTENT
47.7% DON'T KNOW WHERE TO LOOK

12. DATE -
THE SILVER BULLET OF ENTERPRISE SEARCH
Source: IntranetFocus

13. ENTERPRISE SEARCH:
UN-COOL AND MISSION CRITICAL
Source: Julie Hunt

14. History of Search
In Academia search is called Information
Retrieval.
It is an old discipline, dating back
thousands of years...
Basic concepts in Information Retrieval:
Recall and Precision, more later...

15. Wikipedia De!nition
“Enterprise search is the practice of
making content from multiple
enterprise-type sources, such as
databases and intranets, searchable to a
de"ned audience.”
http://en.wikipedia.org/wiki/Enterprise_search

16. The Concept of Enterprise
Search: Precision
In the !eld of information retrieval, precision is the
fraction of retrieved documents that are relevant to the
search.
Precision takes all retrieved documents into account,
but it can also be evaluated at a given cut-o" rank,
considering only the topmost results returned by the
system. This measure is called precision at n or P@n.
Source: Wikipedia

17. The Concept of Enterprise
Search: Recall
Recall in information retrieval is the fraction of the
documents that are relevant to the query that are
successfully retrieved.
For example for text search on a set of documents recall
is the number of correct results divided by the number
of results that should have been returned.
Source: Wikipedia

18. Precision and Recall
R number of
M number of N number of
retrieved documents
relevant documents retrieved documents
that are also relevant

19. Precision and Recall
Recall = R / M =
Number of retrieved documents that are
also relevant / Total number of relevant
documents.
Precision = R / N =
Number of retrieved documents that are
also relevant / Total number of retrieved
documents.

20. Relevance
...enterprises typically have to use other query-
independent factors, such as a document's recency or
popularity, along with query-dependent factors
traditionally associated with information retrieval
algorithms. Also, the rich functionality of enterprise
search UIs, such as clustering and faceting, diminish
reliance on ranking as the means to direct the user's
attention.
Source: Wikipedia

21. PageRank

22. Web/Consumer Data vs Enterprise Data
“Enterprise data simply isn’t like web or
consumer data – it’s characterised by
rarity and unconnectedness rather than
popularity and context.”
Charlie Hull, Flax Blog

23. Relevance
We do not have PageRank...
...but we have the bene"t of social!
CMSWire: Social Reconnects Enterprise Search
Emails, People Catalogues, Connections,
Tagging, Sharing etc.

24. The Concept of Enterprise Search

25. Organisation
• Resources!
IntranetFocus: Enterprise Search Team Management
• Work with all Stakeholders = The whole
organisation
•De!ne processes, roles and routines to
govern the solution
• Help publishers get started by creating
processes for better !ndability
• Create easy to use administration interfaces

26. Survey Results of Budget and Organisation
Amongst the organisations that are very satis!ed with their search,
they have a (larger) budget, more resources and systematically work
with analysing search.
As many as 45% of the respondents have no separate budget for
search, but 20% have had a budget for 3 years or more. In the group
with no budget 56% are very or mostly dissatis!ed with their current
search. The dissatisfaction with search drops to 30% for those
organisations with a dedicated budget for search. In the very satis!ed
(67%) and mostly satis!ed (59%) groups a large majority has a budget.
And 71% of the organisations without a strategy also have no budget.

27. What Does the Organisations Do That Leads
Findability?
• In the Very Satis!ed (VS) with their current search group, the number
of Full Time Equivalents (FTE) is 1-2 or more.
• 67% of VS and 71% of the mostly satis!ed groups do search analytics
• 50% do user testing regularly in the very satis!ed group
• 83% (VS) have a person or group that is responsible for analysing
user behaviour and to make sure that search supports the business
needs
• 84% have feedback functionality in the VS group
• 67% of VS have a taxonomy in place and 83% have a metadata
standard.

28. Search Team
• Search Manager
• Search Technology Manager
• Information Specialist
• Search Analytics Manager
• Search Support Manager
By Martin White, IntranetFocus

29. Organisation
• Not a project!
• Time and Money important
• Measure, KPIs/Search Analytics
CIO.com: How to Evaluate Enterprise Search
Findability Blog: Building a Business Case for Enterprise
Search

30. CONTENT STRATEGY
@jcolman: How to Build SEO into Content Strategy

31. Governance
• Information Quality, with KPI
• Metadata Quality, with KPI
• Information Lifecycle Management
- Time to live for di$erent content types
- Archive, delete or keep?
• SimCorp example
• Search Analytics on regular basis

32. User Involvement
• Get to know your users and their needs
• Make sure your solution is easy to use
• Perform continuous usability evaluations, like
usage tests and expert evaluations
• Make sure users !nd what they are looking for
• Enable feedback loops for complaints,
feedback and praise
• Examples: Nordea, VGR and many more

33. Information
• Good Data/Information hygiene
• Crap in = Crap out
• Metadata is very important!
Presentation: Taxonomy and Metadata demysti!ed
Video: TetraPak example
Video: VGR example

34. Information
• Clean up and archive or delete outdated/
unrelevant information
• Ensure good quality of information by
adding structured and suitable metadata
• Information Architecture and taxonomies
Early & Associates: 10 Common Mistakes When
Developing Taxonomies
• Tagging
Presentation: Social Tagging, Folksonomies Controlled
Vocabularies

35. METADATA

36. •List
yeraze

37. svenwerk

38. DEWEY DECIMAL CLASSIFICATION

39. KristianNorling

40. Author: Douglas Coupland
Title: Generation A
Publisher: Windmill Books
Year: 2009
Printed by: CPI Cox & Wyman
First published: 2004

41. Metadata
Semantic

42. ESEO: Actionable activities
• Metadata
• Titles
Example: Ernst & Young
Very Important
• Content Quality
• Information Life Cycle Management

43. Ways to add metadata
• Manually - Editors
• Automatic - Software
• Semi-automatic - Software + Editors
• Tagging - Users (+Software)
VGR Example: How to add metadata
Thomas Vander Wal:
Integrating Folksonomies With Traditional Metadata

44. Search Analytics
•Bene"t of Search Analytics
•What metrics are interesting?
•Actions to take based on search analytics
•Do’s and don’ts

45. SEARCH ANALYTICS
GIVES USER INTENT

46. Search Analytics
Important, delivers actionable to-dos quickly
• 0-results
• Top Terms Searched for
Video: Search Analytics in Practice

47. Actions to take
• Know what information is “most
wanted” and work with that
• Promote information when it is in
demand
• Are search queries seasonal?
• Find synonyms

48. Do
...Fix 0-results
...Check common terms
...Cluster synonyms
...Use Key Matches / Best Bets /
Sponsored Links

49. A FEW HOURS
EVERY MONTH,
CAN DELIVER
GREAT RESULTS!

50. Do - bonus
...Check user behaviour?
...Research in what context?
...Look at trending/temporal terms

51. Do not
...Forget to work with your content
...Forget metadata
...Only use search analytics - combine
with web analytics

52. Fantastic book
SEARCH ANALYTICS FOR YOUR SITE
Conversations with Your Customers
by LOUIS ROSENFELD
@louisrosenfeld

53. Summary
• Involve the users (and stakeholders!)
• Allow user input (forms)
• Training for editors and publishers
• Set up simple guidelines (E&Y)
• Lifecycle Manage Information
• Do Search Analytics
• Measure and follow-up

54. Bonus (SharePoint) tip 1
Create an information architecture or at least a content model,
answering the questions; What goes were, what information are
related and how should it be possibly to access the information?
Ensure that all information is mapped in this manner and if new types
of information arise that doesn't !t the model, revise and restructure
(not refactor). Make sure that information architecture is not optional
but mandatory.

55. Bonus (SharePoint) tip 2
The way forward in a more complex information landscape is metadata
and search. Use the term store to create taxonomies and metadata
structures, add as much needed information as possible and apply
them to the information through the content types in SP, to all the
information.
Applied term store information can be directly accessed via search as
facets which is a very powerful tool to quickly navigate to the correct
information. The term store also gives you other possibilities to create
other ways to navigate that are not based on the classical usually more
functionally or organisationally based navigation e.g. Via product,
customer or projects.

56. Bonus (SharePoint) tip 3
Socialise your content and make sure that user input counts towards
search relevance and the overall information architecture. User input
can be manifested as explicit or implicit. Explicit as likes or comment
on the information, implicit via search logs. The explicit input is quite
straight forward but might need a critical mass to become relevant
e.g. More likes = higher relevance. Implicit via search logs needs more
analysis but will give more leverage.

57. Kristian Norling
kristian.norling@!ndwise.com
@kristiannorling
@!ndwise
!ndwise.com
Findability Blog
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