MOZCON 2017 WINNING WITH CHOICE & INFORMATION SYSTEMS FOR BOTH CRAWLERS & CONSUMERS

@dawnieando from @MoveItMarketing
Click To Edit Presentation SubtitleClick To Edit Presentation Subtitle
WINNING WITH CHOICE & INFORMATION
SYSTEMS FOR BOTH CRAWLERS &
CONSUMERS

Managing Director Move It Marketing
Associate Lecturer – Digital
Marketing, Search & Analytics –
Manchester Metropolitan University
UK, US, EU, MENA Search Awards
Judge
International & Technical SEO
Consultant – 10+ Yrs
Googebot Hunter (Practice &
Academia)
Dawn
Anderson

Click To Edit Presentation SubtitleClick To Edit Presentation SubtitleAttribution: @Rathergood

POTENTIAL CONFLICTS BETWEEN CHOICE
THEORY & SEO

THE LURE OF
CHOICE
(‘The Lure of Choice; Bown et al, 2003)
We are intrinsically
drawn to varietyCHOICE

THE LURE OF
CHOICE
BROWSING IS NOT BUYING
CHOICE

X 10
more jams sold from
displays of 6 ITEMS
than 24 ITEMS
‘Too Much Choice’ Effects (Iyengar & Lepper, 2000)
Too Much Choice…Iyengar & Lepper’s Much Cited Jam
Study
CHOICE

Iyengar & Lepper’s Chocolate Study
Those actually choosing
from many options
tended to experience
decision-‐regret
afterwards
(BUYER’S REMORSE)
DECISION
REGRET
‘Too Much Choice’ Effects (Iyengar & Lepper, 2000)
CHOICE

“LESS MAY BE
MORE WHEN
CHOOSING IS
DIFFICULT”
(
MORE features and
attributes to compare
(‘Size’, ‘Colour’,
‘Brand’),
the GREATER ‘too much
choice’ effectTASK COMPLEXITY
2010
Less May Be More When Choosing is Difficult - Greifender et al, 2010)
CHOICE

More so when items
are SIMILAR and no
clear winner is
identified as BEST
THE ‘SIMILARITY’ PHENOMENON
CHOICE

Or when people
don’t actually
know what they
want in the first
place
‘PREFERENCE UNCERTAINTY’
CHOICE

WE MAY DEFER (POSTPONE)
OR ABANDON CHOICE
It’s easier to
take the
‘No-Choice
Option’
“I’ll choose later
… or NEVER”
CHOICE

COGNITIVE LOAD
Costs of Thinking (Shugan) &
Costs of Searching
§ ‘Task Complexity’ (Tversky, 1972)
§ ‘Option Complexity Under Conditions’
(Chernev, 2015)
§ ‘Similarity Phenomenon’ (Dhar, 1997)
§ ‘Information Retention Capacity’
(Miller, 1956)
§ ‘Choice complexity & too much choice’
(Greifeneder et al, 2010)
WHY SO??
CHOICE

9 seconds
“I can concentrate
for longer than
you… so there”
AVG ATTENTION SPAN DROPPED BY 3
SECONDS SINCE 2000
GOLDFISH == 9
SECONDS
HUMAN == 8
SECONDS

SOMETIMES
‘CHOICE
REDUCTION’ IS
OFTEN A
POWERFUL
STRATEGY

Tesco were baffling
consumers with up
to 90,000 products
to consider during
weekly shop
“The average UK
household buys only
400 products a year,
with just 41 items in
their weekly shop”
Source: https://www.theguardian.com/business/2015/jan/30/tesco-‐cuts-‐range-‐products

228 DIFFERENT
AIR FRESHENERS
Source / Attribution : gfycat.comSource: https://www.theguardian.com/business/2015/jan/30/tesco-‐cuts-‐range-‐products
“If you go into Tesco you will be faced
with three of four bays of air
fresheners…It’s painful for the shopper to
navigate.” (Bryan Roberts, Analyst, Kantar Retail Market
Research Group, 2015)

Pulling up to 1/3of
products to make
navigating the weekly
shop easier for consumers
Source: https://www.theguardian.com/business/2015/jan/30/tesco-‐cuts-‐range-‐products

DIGITAL CHOICE

THE LURE
OF CHOICE
IN SEARCH

THE LURE OF
CHOICE
BROWSING IS NOT BUYING

Ecommerce Conversion Rates by Referrer
2016
Source: http://www.smartinsights.com/ecommerce/ecommerce-‐analytics/ecommerce-‐conversion-‐rates/

Mobile… has appalling conversion rates
2016

Browse on mobile, buy on desktop??? Desktop is worse
2016

CHOOSING IS HARD WORK… WE SEEK SHORTCUTS
We are ALL
choosing strategists
§ ‘FIRST or BEST’ choosers
§ ‘Maximisers or Satisficers’
§ ‘Elimination By Aspects’ strategy
EMPLOYING HEURISTICS

How Are Choosing Strategies Catered For in Ecommerce?
§ Decline of desktop
§ Horrendous PC
shipment decline
§ Mobile overtaking
search
§ More searches on mobile
than desktop now
§ FACETED NAVIGATION
& WEBSITE FILTERS ==
Allows for ‘Elimination by
Aspects’
§ PAGINATION == Reduces
‘Too Much Choice’ effects
§ SORTING == Caters for
‘FIRST / BEST’ choosing
strategies
CHOICE-‐
ASSISTING
FUNCTIONALITY
HEURISTICS

Enter URL Parameter-driven Popular Ecommerce Platforms

And with these choice-assisting functionalities come…
“Exponentially
multiplicative
URLs”
MANY URL
REPRESENTATIONS
OF THE SAME
CONTENT
MANY
INTERMEDIATE
PATHS TO TRAVERSE
BEFORE
WORTHWHILE
CONTENT
POTENTIAL DUST & NEAR-‐DUPLICATE CONTENT

URL PARAMETERS

Exponentially Multiplicative URLs From Faceted Navigation…
100 DRESSES
5 COLOURS
10 SIZES
2 LENGTHS
4 SUPPLIERS
100 x 5 x 10 x
2 x 4 =
40,000
URLs

And that’s without HTTPS, WWW/non or internationalization
100 DRESSES
5 COLOURS
10 SIZES
2 LENGTHS
4 SUPPLIERS
100 x 5 x 10 x
2 x 4 =
40,000
URLs
X 2 BECAUSE…
HTTPS VERSION
80,000
URLs
X 2… BECAUSE…
WWW / NON
WWW VERSION 160,000
URLs
X 5…
BECAUSE…
EN / FR / ES /
DE / IT (e.g.)
800,000
URLs

THAT’S A LOT
OF URLs FOR
100 DRESSES

A lot of busy Googlebots & potential for duplicates
• The web doubled in
size 2010 – 2012
• Another 1/3 by 2015
• Finite search engine
resources
• Processes automated
for scale
“I just never have
any ‘me’-‐time’
any more”
EFFICIENCY

WEB CRAWLING EFFICIENCY
CRAWLING EFFICIENCY
IS REQUIRED

Handling Near-Duplicate Content Attracted Lots of Research
§Dennis Fetterly
§Marc Najork
§Mark Manasse
§Ziv Bar-‐Yossef
§Monica Henzinger
§William Pugh
Some Notable ‘Spot the
Difference’ Researchers
DETECTING DUPLICATES & NEAR-‐DUPLICATES
EARLY SAVES ON RESOURCES / EFFICIENCY

Because… Near Duplicate Content is More Difficult to Detect
than Exact Duplicates
’Detecting Duplicate and
Near Duplicate Files’
IT’S AN ONGOING REAL
WORLD CHALLENGE
(Henzinger / Pugh, 2003, 2009, 2011,
2012, 2011, 2016)
These Google patents in the series
keep being ‘tweaked’ (A is not the
same as B)

DUSTBUSTER - Do Not Crawl in The Dust… Ziv Bar-Yossef
Reduce crawling and wasted
resources to low importance pages
CAVEAT: IT IS NOT
KNOWN WHETHER
THIS IS BEING USED
AT ALL. RESEARCH
AND THEORY
§ Builds crawling ‘rules’
§ Detects duplicate content
URL patterns
§ From small ‘sampling’ visits
§ Swerves ‘DUST’
§ DUSTBUSTER
§ Saves crawling resources
§ Potentially Popular CMS
configurations URL
parameters detect ‘DUST’
2003

Important findings… Near-Duplicates Evolve Slowly
“Clusters of near-‐
duplicate documents
are fairly stable: Two
documents that are
near-‐duplicates of one
another are very likely
to still be near-‐
duplicates 10 weeks
later”
(Fetterly & Najork,
2003)
THE SLOW PAGE EVOLUTION OF NEAR-‐
DUPLICATES
ABOUT 1/3 OF THE WEB IS NEAR-‐
DUPLICATES
THESE PAGES DON’T NEED
VISITING A LOT BECAUSE THEY
RARELY CHANGE
DETECING THESE PAGES EARLY
HAS BIG BENEFITS FOR
RESOURCE EFFICIENCY
They’re largely a big waste of crawling
resources
2003

DENNIS FETTERLY & MARC NAJORK
EFFICIENCY

Mostly Stable For Years… But… The Web is Always Changing
2017

… The Raters Guidelines still ask raters to catch ‘dupes’
In Fact… There’s
a whole section
of the guidelines
dedicated to
them
2017

Near-Dupes are still doing strange things
John Mu at International Search Summit
§ Nearly the same but not
the same still causes
confusion
§ Particularly problematic
on internationalisation
§ But applies to all sites
with pages not the same
but ’nearly-‐the-‐same’
2017

Reduce crawling and wasted
resources to low importance WHOLE
site branches / sections
Transitive Nature? and Dynamic Web Nature Conflicts
§ Dynamic web nature negates
transitive nature?
§ A whole site section deemed low
quality may be crawled less
§ The ‘transitive’ nature of near-‐
duplicates (not all agree)
§ Search engines will pick one page
& drop the others
§ Brands have less control
§ Reduced crawling means it may
take a while to fix
Transitive -‐ A == B + B == C then A == C
2016 2010

DUPLICATE CONTENT & CANONICALS

Enter the Canonical Tag - Otherwise Known As… RFC 6596
‘THE
CANONICAL
LINK
RELATION’
2012

‘The Canonical Link Relation’ – RFC6596 Is Still Adhered To
2017

But there are many signals at play
CANONICALIZATION
§ Canonical tag (HINT)
§ 30X redirects (DIRECTIVE)
§ Href lang (HINT)
§ HTTPS protocol (Preferred
over HTTP protocol)
§ Global canonicalization
rules (Likely automatic
e.g. convert to lower case)
These are ALL
types of
canonicalization
(DIRECTIVES or
‘HINTS’
2012

You Must Align All Of These Signals To Get This Right

There Are Many Signals To Consider In Canonicalization
404 & 410
301
302, 303, 307
Valid canonical from ‘context’ URL to valid target
Fall back to default pre ‘Canonical Link
Relation’duplicate handling signals
Valid href lang (if present and applicable)
Manual Action SUPER STRONG
STRONG -‐ DIRECTIVE
STRONG -‐ HINT
STRONG -‐ HINT
DEFAULT
ALL NEED TO BE IN UNISON
HTTPS (Google Specific)

+ Interviews with
- 5 International SEOs
working on ecommerce
sites with >100k URLs &
> 10 years SEO
experience
2017
SEO Survey
339 SEOs
Objective -‐ “Understand how SEOs handle near-‐duplicate content
and explore experiences with it”

Q: Canonicalization is an Easy Concept to Understand?
76% of SEOs surveyed
considered;;
“CANONICALIZATION
IS AN EASY
CONCEPT TO
UNDERSTAND”
2017

LESS THAN 50% of
SEOs surveyed
considered;;
“CANONICALIZATION
IS ADVANCED
TECHNICAL SEO”
Q: Is canonicalization advanced technical SEO?
2017

50% OF SEO’S
“SEARCH ENGINES HAVE
IGNORED CANONICAL TAGS
THEY HAD IMPLEMENTED”
Q: Have Search Engines Ever Ignored Canonical Tags?
2017

ON WHAT IS
CANONICALIZATION …
And what is not
But… There Seemed To Be A Lot of Misunderstanding
2017

Q: Is Rel = Next/Prev a form of canonicalization?
47% of SEOs categorizing
themselves as ‘TECHNICAL
SEO’s considered;;
“REL=NEXT / REL =
PREV” IS A FORM OF
CANONICALIZATION
-- IT’S NOT -- 2017

Q: Which 30X Are Forms of Canonicalization?
Lots weren’t sure whether;;
“301s AND 302s ARE
BOTH A FORM OF
CANONICALIZATION”
-- THEY ARE --
2017

Q: Is HRef Lang A Form of Canonicalization?
ONLY 64% of SEOs
categorizing themselves as
‘TECHNICAL SEO’s
considered;;
“HREF LANG IS A FORM
OF CANONICALIZATION”
-- IT IS -- 2017

CANONICAL
IS NOT ALWAYS
SIMPLE

Google’s Maile Ohye on ‘How To Hire An SEO’

Without &filter=0 Appended to end of Query
https://www.google.co.uk/search?q=red+dress
es+size+10+long+sleeves&oq=red+dresses+siz
e+10+long+sleeves&aqs=chrome.0.69i59.1257
0j0j7&sourceid=chrome&ie=UTF-‐8
NOBODY HAS MORE
THAN ONE LISTING
RED DRESSES SIZE 10
LONG SLEEVE QUERY

With &filter=0 Appended to end of Query
https://www.google.co.uk/search?q=red+size+1
0+dresses+long+sleeves&oq=red+size+10+dress
es+long+sleeves&aqs=chrome..69i57.13605j0j7&
sourceid=chrome&ie=UTF-‐8&filter=0
ALL SITES HAVE AT
LEAST 2 LISTINGS
MISSED
OPPORTUNITIES ON THE
‘LONG TAIL’

CHOICE - Q: Giving consumers lots of choices is good?
§ Output more items in
ecommerce product listings?
§ Potentially ‘overwhelming’ the
consumer?
§ Drop pagination?
§ Giving consumers lots of
choices?
2017
48% THOUGHT GIVING
CONSUMERS LOTS OF CHOICES
WAS GOOD

The majority of SEOs
surveyed considered;;
“OUTPUTTING
MORE ITEMS IS
BETTER FOR SEO” 2017

SEOs – What is the best
number of products to
display together?
71% of SEOs
thought;
“> 24
products
displayed
together was
best”
Only 3% thought; “6
products displayed
together was best” 2017

THAT’S A LOT
TO CHOOSE
FROM
TOGETHER

SEO Familiarity With Consumer Choice Theory Concepts
2017
Only 19% of SEOs surveyed
were aware of ‘elimination by
aspects’
Only 25% were aware of ‘lure of
choice’
Only 37% were aware of ‘task-‐
complexity In choosing’
Objective -‐ “Investigate
awareness of consumer choice
theory concepts amongst SEOs”

AN ENDLESS
LOOP?
SEO’s –
More options
== (Crawl
yield &
content
richness, rank
higher)
CONSUMER
CHOICE
THEORIST
Limit options ==
(Reduce Choice
overload, Use
Heuristics, sell
more)

HOW TO RESOLVE?

2017
HEURISTICS TO HELP FIND THINGS ARE
NOW HIGH PRIORITY

AND…A
POMERAINBOW
WILL APPEAR
WE NEED TO HELP
BOTH HUMANS &
SEARCH
ENGINES
Credit: @jpsherman

SEARCH ENGINES
LOVE
CATEGORIZATION

The ‘Mere’ Categorization Effect (Phenomenon) FTW
§ Decline of desktop
§ Horrendous PC
shipment decline
§ Mobile overtaking
search
§ More searches on mobile
than desktop now
CLEAR LABELLING
FOR THE WIN
‘Signposting &
Identified Top-‐Tasks’
Simply by labelling products /
items as being part of a
category regardless of label
appears to increase
perception of variety &
positive experience (Mogliner
et al, 2003)
THE COMMON HAPPY
GROUND BETWEEN HUMANS
AND SEARCH ENGINES

SORT OUT YOUR
LIBRARY SYSTEM &
IDENTIFY GAPS

KEEP THE SCENT GOING

FRONT AND CENTRE
SUBCATEGORY DRILL DOWN
Nobody buys a ‘dresses’

GOOGLE FLIGHTS

DATA GOLDMINE

HEURISTICS – TAKE A LOAD OFF

SEARCH ENGINES & HUMANS
BOTH LOVE LOGICAL & CONCEPTUAL
LABELLING SYSTEMS
LABELS REPRESENT
LARGER ‘CHUNKS’ OF
INFORMATION / CONCEPTS
Mental Modelling

LABELLING SYSTEM HEURISTICS

Homonyms contribute to need for query refinement
HOMONYMS –WORDS THAT ARE SPELT OR PRONOUNCED
THE SAME BUT HAVE DIFFERENT MEANINGS
ROSE
EVENING WATCH
SINK
BACK
ARMS
BOW
CHECK
Here’s some
examples

QUERY
REFINEMENT
(WITH LOGIC) FOR
SUBCATEGORIES
IN SERPS
DISTINCTION BY
COLOUR REDUCES
‘TOO SIMILAR’

GLOBAL NAVIGATION STRENGTH
WHOLE AUDIENCE WIDE ‘TOP TASKS’ –
WHOLE ‘THEME’ STRENGTH

LOCAL NAVIGATION RELEVANCE
TABLE OF CONTENTS STYLE IN
PAGE NAVIGATIONAL HEURISTIC
FOR SEARCH ENGINE AND
HUMAN
PAGINATED TAB THROUGH ON
SECTIONS OF REVIEW
MICRO-‐TASK
RELEVANCE

LOCALISED NAVIGATION

SECTIONAL HEURISTICS IN ACTION

The H’s – Bringing Order
THEY’RE NOT JUST THERE
FOR SEARCH ENGINES.
HUMANS NEED LOGICALLY
LABELLED SECTIONS TOO

TASER THE MIXED-
UP LABELLING
SYSTEM
SCREAMING
CONFUSING
INFO

Make it easy… for
people to find things
2017
PEOPLE ARE USING
HEURISTICS -‐
PARTICULARLY SITE
SEARCH & CATEGORIES

SITE SEARCH

SITE SEARCH: FRONT AND CENTRE
Econsultancy research
reports conversion rate
doubles to 4.63% from
people who used on-site
search and found what they
were looking for
https://moz.com/blog/on-‐site-‐search

STICKY…ALWAYS THERE…
ASSISTIVE SEARCH BOX
OR IN SPECIFIC SITE
‘ZONES’

INTELLIGENT INTERNAL LINKING

TOP & BOTTOM
BREADCRUMBS TOO
FTW
ANCHORS IN BREADCRUMBS ARE
LABELS TOO
INTELLIGENT
INTERNAL LINKING

SUPPLEMENTARY CONTENT
A LIST
LABELS
ANCHORS
RELEVANCE
RELEVANCE MUST BE HIGH
TO CONTENT TO GET FULL
BENEFIT
INTELLIGENT
INTERNAL LINKING

BUILD STRONGLY CONNECTED COMPONENTS
Source: Broder, A., Kumar, R., Maghoul, F., Raghavan, P., Rajagopalan,
S., Stata, R., Tomkins, A. and Wiener, J., 2000. Graph structure in the
web. Computer networks, 33(1), pp.309-320.
BOWTIE OF THE WEB
STRONGLY
CONNECTED
COMPONENT
INTELLIGENT
INTERNAL
LINKING

GOOGLE FLIGHTS
STATIC DYNAMIC & USER RELEVANT
INTELLIGENT
INTERNAL LINKING

INTELLIGENT
INTERNAL LINKING

MANY WAYS TO FIND
ROUTES TO TARGET URLS
WITH INFO DISPLAYS
BY POSTCODE, BY TOWN,
BY COUNTY, BY FIRST
LETTER
INTELLIGENT
INTERNAL LINKING

THIS HTML
SITEMAP
SECTION
CHANGES
ON RELOAD
INTELLIGENT
INTERNAL LINKING

GB
RU
CN
GB
AU
IT
GB
ZERO
PRODUCT
PAGES
-‐ NIL
-‐ NADA
-‐ NONE
NEWS WOMENS
CATEGORIES
(PRODUCT TYPES,
INDIVIDUAL
BRANDS & A-‐Z
BRANDS)
MENS CATEGORIES
(PRODUCT TYPES, INDIVIDUAL
BRANDS & A-‐Z BRANDS)
Asos XML SITEMAP SERIES STRATEGY
FOR EACH
INTELLIGENT
INTERNAL LINKING

BE IN CONTROL
OF WHAT’S AT
THE TOP
DATA & KPI
DRIVEN
PRIORITIES

ARE REVIEWS WORTH IT?

ARTIFICIAL INTELLIGENCE &
RECOMMENDER SYSTEMS

ONLY 4
OPTIONS FOR
DRESSES

AI PRODUCT RECOMMENDER CHATBOTS
CHINESE ECOMMERCE SITE JD.COM
(JINGDONG) DRASTICALLY INCREASED
CONVERSIONS USING XIAOICE MICROSOFT
CHATBOT TO ’SUGGEST’ LIMITED PRODUCTS
TO USERS

There Are Still Several Challenges With Contextual Semantic
Search
2017Source: Keynote WSDM2017 -‐ Ricardo Baeza-‐Yates

POMERANIAN OR PANCAKE?
AI CAN’T EVEN
UNDERSTAND…
YET…

Take-Away
Most mobile device screens are 4 – 4.5”
Increasingly intelligent ‘bullseye’ heuristics in a
limited space for humans & search engines are
needed
REMEMBER
WE MAY EVEN NEED TO… TALK TO
OTHER DEPARTMENTS

Thank
You

APPENDIX

With canonicals the ‘context’ URL
(canonicalizing FROM) needs to be either
duplicative or a subset (small part) of the
superset content (bigger part including the
subset content) of the URL it is
canonicalizingTO
EXAMPLE: If canonicalizing blue shoes size 4 to blue shoes but blue shoes size 4 is not mentioned in the
blue shoes page, the content from blue shoes size 4 canonicalized from will not be included and the page
will not rank for blue shoes size 4
COMMON CANONICAL MISTAKES
BE CAREFUL
WHEN AUTO-‐
CANONICALIZING
‘FILTERS’ TO
CATEGORIES

Don’t canonicalize from the pages in a
paginated series to page1 in the series.
These are not duplicates and the content in
the series will not be counted.
ONLY self-‐reference the pages with
canonicals or canonicalize to page=“all”
REL=NEXT/PREV IS A DIFFERENT TYPE OF RELATIONSHIP TO
REL=CANONICAL

Don’t canonicalize from an ”index” to a
“noindex or vice-‐versa because this means
the pages are NOT the same.
The canonical will likely be ignored

If “href lang” references an alternative
which does not match a canonical link the
canonical will likely be ignored
CANONICALS CAN BE CROSS-‐DOMAIN
BUT THIS ONLY APPLIES TO GOOGLE
SEARCH ENGINE. NOT BING

If a canonical is not deemed to be valid
there is likelihood the pre-‐RFC6596
Canonical Link Relation treatment of
duplicates and near-‐duplicates will be
applied:
Such as ‘internal links’

TAKE AWAY
§ Stagnation of desktop
§ Increasingly limited space
§ Increasingly limited
attention
§ Increasingly limited time
§ Increasing competition for
prospect attention
Revisit ‘Labelling’ on global
navigation, syntax, local
navigation, internal link labelling
and count, implement internal site
search, be ‘DISTINCT’ in labels
Understand ‘heuristics’ are needed
in the absence of a well pre-‐
empted ‘best fit’ of products in a
small screen
2017
GOOD PRINCIPLES OF
INFORMATION
ARCHITECTURE

Revisit Parameter Handling & Understanding Canonicalization
“IS PARAMETER-‐HANDLING A
WAY TO HELP GOOGLE BUILD A
SET OF ‘DUSTBUSTER
CRAWLING RULES’ EARLY?”
Tell Google about your duplicate content

CONFUSING DUPLICATE, NEAR-‐
DUPLICATE (DUST) AND SIMILAR
CONTENT COULD COST YOU
DEARLY
Maybe a lot of people confuse by duplicates?
§ Be careful about canonicalizing
when unnecessary
§ Duplicate content is query and
category agnostic
§ Similar is not duplicate
§ You may still have the answers
to different queries based on a
small important difference
§ AT LEAST 4 TYPES OF
DUPLICATE CONTENT 2017

REFERENCES

References & Sources
Bown, N.J., Read, D. and Summers, B., 2003. The lure of choice. Journal of
Behavioral Decision Making, 16(4), p.297.
Mochon, D., 2013. Single-‐option aversion. Journal of Consumer
Research, 40(3), pp.555-‐566.
Fetterly, D., Manasse, M. and Najork, M., 2003. On the evolution of clusters
of near-‐duplicate web pages. Journal of Web Engineering, 2(4), pp.228-‐246.

Schwartz, B., 2004, January. The paradox of choice: Why more is less. New
York: Ecco.
Tversky, A., 1972. Elimination by aspects: A theory of choice. Psychological
review, 79(4), p.281.
Iyengar, S.S. and Lepper, M.R., 2000. When choice is demotivating: Can one
desire too much of a good thing?. Journal of personality and social
psychology, 79(6), p.995.
Mogilner, C., Rudnick, T. and Iyengar, S.S., 2008. The mere categorization
effect: How the presence of categories increases choosers' perceptions of
assortment variety and outcome satisfaction. Journal of Consumer
Research, 35(2), pp.202-‐215.

Greifeneder, R., Scheibehenne, B. and Kleber, N., 2010. Less may be more
when choosing is difficult: Choice complexity and too much choice. Acta
psychologica, 133(1), pp.45-‐50.
Langner, T. and Krengel, M., 2013. The mere categorization effect for
complex products: The moderating role of expertise and affect. Journal of
Business Research, 66(7), pp.924-‐932.
http://www.seobythesea.com/2008/02/new-‐google-‐process-‐for-‐detecting-‐
near-‐duplicate-‐content/
Pugh, W. and Henzinger, M.H., Google Inc., 2016. Detecting duplicate and
near-‐duplicate files. U.S. Patent 9,275,143.

Alonso, O., Fetterly, D. and Manasse, M., 2013, December. Duplicate news
story detection revisited. In Asia Information Retrieval Symposium (pp. 203-‐
214). Springer Berlin Heidelberg.
Dhar, R., 1997. Consumer preference for a no-‐choice option. Journal of
Consumer Research, 24(2), pp.215-‐231.
RFC 5988 – The Canonical Relation Link -‐ https://tools.ietf.org/html/rfc5988
http://rathergood.com/2016/04/04/northern-‐kittens-‐play-‐independent-‐
woman-‐as-‐covered-‐by-‐elbow/

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MOZCON 2017 WINNING WITH CHOICE & INFORMATION SYSTEMS FOR BOTH CRAWLERS & CONSUMERS