Consumer Search

Behaviour

THURSDAY 29TH OCTOBER 2015

Introductions

Gerald Murphy

Senior Search Manager

Sandra McDill

Chief Digital Officer

Search is huge

There are more than 1 trillion annual Google searches

– 137 searches, per person

Worldometers Search Engine Land

There are over 1 trillion annual

Google searches

WHY DO WE SEARCH?

Problem

Goal

There is only so much we can predict

Income, Education and Health

• Reflective of how we engage with technologies

– More money, bigger choice of technology to choose from

• Will impact the types of products we will already have as a goal

• But have no impact on search engine use or behaviour

Age

• Younger and middle-aged searchers are very similar

– 18 to 60s

• Older spend double the amount of time on the SERP

– On average an extra 4 seconds

Age development photo: Copyright granted, reused, unmodified (TheIRHistory)

Location

• Location is increasingly a huge factor for search as Google increases its relevancy

• When a consumer adds location based search queries we have to listen to the signal that is increasingly more important

• Yet where someone is from, isn’t going to impact their search behaviour

Male searchers

• Tend to spend more time examining SERP

• 5.4 times more likely than females to inspect lower ranked results

• More linear

• View on average 3 more pages than females

• More time to enter queries

• Scan and filter results on SERP

Female searchers

• Do not scroll as much

• Less linear

• Open 2 more browser tabs for more complex searches

• Tend to repeat views of old results

• Fixate heavily on positions #2 and #3

• Prefer to read target results on paper

• Less time on SERPs

• Browse websites more deeply

…on highly ranked results?

SO WHY DO WE CLICK?

Trust bias

• Highly ranked results are trusted

• Even if these abstracts are less relevant than other abstracts

Photo: Copyright granted, reused, unmodified

Quality bias

• Searcher click decision is influenced by:

– Relevance of clicked link

– Overall quality of the other abstracts in the ranking

0

10

20

30

40

50

60

70

Google Bing Yahoo

Comparison of relevant results vs relevant descriptions

Descriptions

Results

F-shaped pattern

• We scan results in an F-shaped pattern

State of the art: Searcher behaviour

Query log analysis ‘Hold times’ of

documents Number of clicked

results Ranking of clicked

documents

Eye tracking Evaluation of eye-

movement on a computer screen

Areas of Interest (AOI)

Heat maps

(don’t produce these)

Gaze maps User studies Mapping of gaze

data to web content pages

Mapping of gaze data to the results page: ‘The Golden

Triangle’

Mapping of eye movement to

Results and Content pages: ‘The F-

shaped pattern’

Scanpaths

Heatmaps, suck !

Scanpaths

1

2 3

4 5 6

7

8 9

• 16 scanpaths

• 5.8 compressed scanpaths

• 3.2 minimal scanpaths

• We don’t always view in order of what the engine ranks

• We click on what order the engine ranks

– Trust and quality bias

Enhance CTRs: Attractive keywords

Free Online Deal Affordable Price

Low Instant Local Fundamental Professional

Compare Today Find Official Shop

Great Site Qualified Save Secure

CTRs: click-through rates

Aggregated, blended, or universal SERP

Snippet length of descriptions

• If title, URL and description were on one line each, each would receive equal attention

0 2 4 6 8 10

Short

Medium

Long

Navigational

URL

Description

Title

0 2 4 6 8

Short

Medium

Long

Informational

URL

Description

Title

Cited from Peter Morville

BEHAVIOUR PATTERNS

Search behaviours

Quit

Source: Peter Morville (Search Patterns, Design for Discovery)

Narrow

Pogosticking Thrashing

Expand Pearl Growing

Quit

• We all quit at one point but why?

– Speed?

– Information seeking process successful?

– Information seeking process unsuccessful?

Bounce Rate Pages viewed per session

Time spent on page

Click depth Cart

abandonment

Narrow

• Second most common search pattern

– Refinement

Expand

• Uncommon

– Difficult problem

People also searched for

Auto completion

Auto suggestions

Facets

Pearl Growing

• Expert searching

– Mining content and metadata

Competitor insights

Facilitate content ideas

‘Similar searches’ for

keyword research

Pogosticking

• Conversation-attribute search

• We want a rich selection of information

– Google Knowledge Graph

– PPC and SEO results

• Result sampling

– But too much is bad

Thrashing

• Anchor bias

– We think we carry out the perfect search

Mobile is huge

• Mobile browsers have increased 53% vs 2013

• Mobile Apps have increased 90% vs 2013

– This has contributed to a total increase of 77% of the total increase in time spent

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Jan-13 Jan-14 Jan-15

476,553.00 480,967.00 550,522.00

409,847.00 621,410.00 778,954.00

77,081.00 97,440.00 118,299.00

Mobile Browser

Mobile App

Desktop

http://www.comscore.com/Insights/Presentations-and-Whitepapers/2015/2015-Global-Digital-Future-in-Focus

Mobile Search

Mobile search

• Our search behaviour changes on public transport

– Stronger observation on public transport

– Momentarily passes on the street

• Not an issue

• Continue walking

• Unwanted attention quickly passes

Mobile in social situations

• 70% of searches are conducted at home or at work

• Mobile search is a social activity

– Often conducted in the presence of others

• Device type impacts mobile search

– High-end smartphones have similar patterns to desktop searchers

Advanced Search

• Engines will soon process mobile queries like PPC, whereby:

– Location

– Time of day

– Day of week

– Weather conditions

– Current activity of user

– Temporal patterns (i.e. weekday vs weekend)

• Will be factored into a mobile search

Get a responsive website

• Mobile search has overtaken desktop on Google (SEL, May 2015)

• Justify to senior management with data analysis

Search Engine Land

Data analysis

CRO and UX

Be SEO ready,

launch!

Geo data

• Discover your hotspots with data

– Top regions and cities

• Store targeting

– Paid search

– Organic search

*physical addresses are required

And use the mobile behaviour

Summary

Searchers are complex people

Goals or problems

Trust bias

Quality bias Scan ~16

SERP points

Interface design

influence

6 search behaviours

7 broad factors impacting a

search

Mobile behaviours

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Copyright © 2015 7thingsmedia LTD.

To get a copy of the presentation: Matthew.Wilkinson@7thingsmedia.com 0207 017 3199