Workshop at Intranätverk 2013 in Gothenburg, Sweden.

1. Kristian Norling, Intranätverk 2013, 23 May, Gothenburg, Sweden
OPTIMISING YOUR CONTENT FOR
FINDABILITY

2. #intranatverk
@kristiannorling
@intranatverk

3. • Who is here?
• Your expectations?
• Kristian?
• 3 hours
• One 20 minute break ≈ 14.30
• Lifetime answer Guarantee on this class
Introduction

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

5. 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
Description

6. 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.
Description

7. 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
Brief Outline

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

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. Source: IntranetFocus
DATE -
THE SILVER BULLET OF ENTERPRISE

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

14. 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...
History of Search

15. “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
Wikipedia De"nition

16. 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
The Concept of Enterprise
Search: Precision

17. 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
The Concept of Enterprise
Search: Recall

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

19. 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.
Precision and Recall

20. ...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.
Relevance
Source: Wikipedia

21. PageRank

22. “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
Web/Consumer Data vs

23. 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.
Relevance

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. 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
Survey Results of Budget and

27. • 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
What Does the Organisations Do

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

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

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

43. • 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
Ways to add metadata

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

45. SEARCH ANALYTICS
GIVES USER INTENT

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

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

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

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

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

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

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

53. • 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
Summary

54. 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.
Bonus (SharePoint) tip 1

55. 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
Bonus (SharePoint) tip 2

56. 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.
Bonus (SharePoint) tip 3