unconscious cues

UNCONSCIOUS
CUES
AN EXPERIMENT INTO THE UNCONSCIOUS DRIVERS
OF BRAND PERCEPTION ON TWITTER
FOREWORD
As people live more of their lives online, brands find
themselves adapting to new platforms and the new
consumer expectations that come with them.
But as the marketing industry adopts these new
tactics, it’s essential we remember that keeping track
of technological change is only a means to an end.
Our job is to turn that change to the advantage of
our clients’ business. That means taking the time to
take stock. If we don’t understand how these new
platforms work, we can’t use them effectively.
And, of course, some things don’t change. People,
for instance. Our behaviour may have taken on a new
digital dimension, but our motivations and responses
to the world remain as emotional – as human – as
ever. We are social animals. Our brains process most
of the information they receive unconsciously.
Enabled by technology, but powered by people.
This has huge implications for the way people use
and respond to digital experiences. Twitter is one of
the most important digital experiences for our clients,
and for most brands, so naturally it was something we
wanted to understand more. How do people perceive
brands on Twitter? How do individual features of the
platform impact on those perceptions? How can we
measure the unconscious?
At Isobar, we run towards questions like this, and
it has been a privilege to work with Twitter on this
unique research experiment.
We hope you enjoy reading this report.
Nick Bailey
CEO & ECD, Isobar UK
UNCONSCIOUS
CUES
AN EXPERIMENT INTO THE UNCONSCIOUS DRIVERS
OF BRAND PERCEPTION ON TWITTER
4
06
15
28
INTRODUCTION
& BACKGROUND
HEADLINE RESULTS
CONCLUSIONS AND
IMPLICATIONS
09
16
30
THE ‘UNCONSCIOUS
CUES’ PROJECT
THE RESULTS IN DETAIL
FINAL THOUGHTS
5
INTRODUCTION
“IT’S WELL ESTABLISHED THAT OUR
CHOICES IN REAL WORLD SITUATIONS
ARE HEAVILY INFLUENCED BY THE
CONTEXT IN WHICH WE MAKE THEM .1”
A large body of research, built over many years
in the fields of social psychology and behavioural
science, has yielded powerful insights which aid our
understanding of the decision-making frameworks
of people in real life situations . These frameworks
are built of unconscious cues, contextual signals and
heuristics - mental short cuts that make it easier to
process the unconscious decisions we make every
day – as well as effortful, conscious decisions.
An area of particular interest within this research
is ‘Social Proofs’, a mental shortcut people use to
navigate unfamiliar real world social situations.2
It determines an appropriate mode of behaviour
for a particular social context, and is driven by an
assumption that other people have more information
or knowledge about a given situation. This mode of
thinking is characterised as ‘fast, automatic, frequent,
subconscious and stereotypic’.
We all use ‘Social Proofs’. If you are in an unfamiliar
city, deciding where to eat, but with no prior
knowledge of the quality of the restaurants, it’s likely
you would look for somewhere busy. The assumption
here is that the people inside are local and have more
knowledge about the quality of the food than you do.
Therefore, if it’s full, it must be good. The important
thing is that these evaluation processes enter our
minds automatically.
6
‘Social Proofs’ are present in digital experiences, too.
Social media platforms allow us to broadcast our lives
and choices, but also to be influenced by the lives and
choices of others. We are irresistibly drawn to what
others are doing, or what we see as popular.
But the digital world has generated another,
parallel body of behavioural evidence that aids our
understanding of decision-making. The discipline of
digital User Experience (UX) has built on practices
such as A/B and multivariate testing, developed from
direct marketing practices. These are vital tools that
test the impact of the digital experience on users,
and highlight the importance of unconscious and
contextual drivers on online behaviour.
These two fields of study complement each other.
Each has helped brands understand their customers
and create better experiences for them. Where social
psychology has helped brands understand human
behaviour; insights from UX has helped them optimise it.
Increasingly, that behaviour takes place on social
media platforms, where the user experience is
defined by unconscious cues, contextual signals and
heuristics, just as it is in the real world.
1 Tversky, Amos and Kahneman, Daniel, “Judgment under uncertainty: Heuristics and biases,” Science, 185 (1974), 1124-1131.
2 Sherif, M. (1935) A study of some social factors in perception, Archives of Psychology, 27(187)
3 Daniel Kahneman (25 October 2011), Thinking, Fast and Slow, Macmillan ISBN 987-1-4299-6935-2
AT ISOBAR, WE BELIEVE THESE MENTAL SHORTCUTS ARE INFLUENCING PEOPLE’S BEHAVIOUR AND WE WANTED TO FIND
OUT WHAT THIS MEANS FOR BRANDS. WITH THIS IN MIND, WE HAVE CONDUCTED A SERIES OF EXPERIMENTS TO MEASURE
THE IMPACT THAT UNCONSCIOUS INDICATORS HAVE ON BRAND PERCEPTION. SPECIFICALLY, WE HAVE ASSESSED THE
INFLUENCE OF DIFFERENT CUES WITHIN SOCIAL MEDIA AND THE DIFFERENCE THEY MAKE TO PEOPLE’S PROPENSITY TO
TRUST, RECOMMEND AND PURCHASE BRANDS.
THE PILOT EXPERIMENT:
Understanding the value of a social community
In 2013 Isobar collaborated with behavioural researchers at the University of Cambridge to design a controlled lab
experiment. We wanted to test what impact the size of a brand’s social community had on perception of
that brand.
We created a fictional furniture brand called Ashwood Furnishings to test whether the size of the community
might act as an unconscious cue to generate Social Proof. Each respondent was shown one of 12 different
mocked-up brand visuals. The only difference was the size of the brand’s social media following. Respondents
were asked to rank the brand in terms of interest, trust, consideration, preference, advocacy and value.
The influence is unconscious and immediate, in the
same way that cues in the real world are. The greater
the number of fans, the higher the brand perception
overall, though the results suggested this effect
was subject to diminishing marginal returns (see
schematic graph).
With this experiment we had seen that very small
cues had a significant effect. But the results raised
questions. What about social media experiences
with multiple unconscious cues? Could we design an
experiment that allowed us to test for other forms of
social proof?
BRAND PERCEPTION
“THE FINDINGS DEMONSTRATED THAT THE SIZE OF THE
COMMUNITY HAS A STATISTICALLY SIGNIFICANT AND
POSITIVE IMPACT ON BRAND PERCEPTION”
SIZE OF COMMUNITY
To answer these questions, we wanted to work
with Twitter.
4 The academic partners from Cambridge were Joe Gladstone and Jon Jachimowicz
5 The full, detailed methodology and results can be read here – ‘The Science of Social: An Experiment in Influence’
7
THE TWITTER-ISOBAR
UNCONSCIOUS CUES PROJECT
Why Twitter?
There are two main reasons for wanting to explore a
brand’s Twitter presence, one behavioural and
one business.
Testing each of these variables in isolation, as well as
testing the impact of the relationship between them,
would provide a wealth of insight.
From a behavioural perspective, Twitter offers
multiple unconscious cues that we could explore
to understand the impact of Social Proof. Each cue
carries assumptions that could give rise to different
user responses.
From a business perspective, brands have moved
quickly to embrace Twitter, in many different ways.
Some brands use social as a way to more closely
engage through entertainment, or by being an active
participant in the conversations users have with each
other. Others provide customer service, or seek to
extend their direct sales function.
1. The number of ‘Followers’: this is the
equivalent to the size of community on
social media.
2. The number of tweets the brand has sent:
how active are they on the platform
3. The number of accounts the brand follows: how connected the brand is, and how much they mirror the activity of a ‘human’ Twitter user
4. The copy contained in the brand’s short
biography: the kind of brand it is
5. The impact of a ‘promoted’ stamp on individual tweets: how is the brand perceived as a business
or marketing entity
8
It’s not always been clear how to measure the
impact of these different approaches, and there has
been little rigorous research into how to use social
platforms most effectively in pursuit of these ends.
Understanding the influence of unconscious cues
on different brand perceptions – such as ‘Trust’,
‘Recommendation’ and ‘Purchase Intent’ – and how
these differ across different audiences can help
businesses to use social platforms most effectively.
METHODOLOGY
TO ENSURE THAT RESEARCH WAS DONE TO THE
HIGHEST STANDARDS, IT WAS DESIGNED AND RUN IN
COLLABORATION WITH THE UNIVERSITY OF CAMBRIDGE.
The static panel experiment:
Variables & stimuli:
We recruited an online panel to measure individuals’
perceptions of a brand’s Twitter pages across various
conditions. As a ‘between subjects’ experiment,
respondents believed they were participating in
a market research survey. Respondents were
presented with a brand page that was experimentally
manipulated to show different values of a range of
different indicators. They were asked to rate the page,
answering questions that explored their ‘likelihood to
buy’ and their ‘brand perception’. These questions
used validated scales from academic literature on
Consumer Behaviour.
We identified five key variables that we believed had
the most potential for influencing brand perception
on Twitter.
We decided to use this methodology, adapted from
behavioral and experimental economics, as it can
help uncover the cues that trigger unconscious
changes in brand perception. Often when using
traditional research methodologies, such as surveys,
respondents sometimes post-rationalise their
responses, particularly to questions about external
influences on their choices. People often do not
readily admit to being influenced by things beyond
their control. Moreover, very often people are simply
not aware that they are being influenced by certain
things, or if they are, they find it very hard to judge
the extent to which external cues have an impact on
their behaviour.
The tone of voice of the copy in the brand biography
They were:
The number of followers a brand has
The number of accounts a brand follows
The number of tweets a brand has sent out
The presence of a ‘promoted’ stamp on individual tweets
We measured the impact of each of these variables
in isolation while holding the other variables constant.
Building on the success of our pilot experiment, we
created another fictional brand: Resident, a unisex
clothing brand in the style of ASOS or TopShop. By
creating a fake brand we were able to control for
biases in people’s experiences or perceptions of
existing brands so that we could be sure that the
effects being measured were driven by only the
change in variables. Benchmarks for each variable
number were set by looking at the numbers of
‘tweets’, ‘followers’ and ‘following’ that similar brands
have on their real Twitter brand pages.
9
@RESIDENTLTD
OUR FLORAL PENCIL SKIRT HAS BEEN GIVEN THE GOLD SEAL
OF APPROVAL BY @GLAMOURMAGUK
Promoted by ResidentLTD
10
IN TOTAL THE EXPERIMENT
USED 21 DIFFERENT STIMULI
SPLIT ACROSS THREE DIFFERENT
AREAS OF EXPERIMENTATION.
01.Three different versions of biographical copy
were written to reflect a ‘funny’ tone, ‘serious’ tone
and ‘responsible’ tone.6
02. We tested each of the ‘numeric’ variables –
followers, following and tweets – across four different
levels; very low, low, high, very high. Each variable
had its own benchmark at each level, set by looking
at the numbers on real brand’s Twitter profiles.
#FUNNY
“LET’S FACE IT, WE ALL LIKE A
BURGER, THAT’S WHY RESIDENT
JEANS ARE SUPER-STRETCH.
@RESIDENTLTD, SUPPORTING
YOUR EATING HABITS SINCE 1992”
03. We tested the extent to which a promoted
‘logo’ on an individual tweet changed perception by
writing three different tweets - one showing ‘industry
acceptance’ of the brand, another highlighting a
popular industry event, and one with a competition
mehcanic. For each of these tweets we had two
versions, one with a promoted logo and
one without.
#RESPONSIBLE
“HERE @RESIDENTLTD, 10% OF
OUR PROFITS GO TO A NOMINATED
CHARITY EACH YEAR! FOLLOW US
FOR ALL FASHION UPDATES OR
TWEET US FOR QUERIES.”
6 There were original seven different biographical copies.
Each of these were tested on Mechanical Turk with a random panel to make sure they could be identified clearly and differently as ‘funny’, ‘responsible’ and ‘serious’
#SERIOUS
“FOUNDED IN 1992 BY DESIGNER
AMY MONROE, WE HAVE GROWN
INTO A LEADING FASHION CHAIN.
OUR VALUES ARE SIMPLICITY,
VERSATILITY AND TRUST.”
11
For this experimental treatment, all numbers were held constant at their ‘average’ level and only the biography
copy changed.
VERY HIGH
FOLLOWERS
FOLLOWING
TWEETS
HIGH
LOW
2.7M
636,000
12,122 4,477
155,000 7,823
7,573
1,056
845
VERY LOW
358
268
343
In this part of the research, the variable we were testing (i.e. Followers, following or tweets) was changed as in
the table above, while the other two variables were held constant at their ‘high’ levels. For example, while the
number of Followers was changing, following and tweets were held constant at 4,477 and 7,823 respectively.
By doing this we could control for interaction effects and can be sure that changes in brand perception are driven
by changes in each of the variables alone.
“OUR FLORAL PENCIL SKIRT HAS
BEEN GIVEN THE GOLD SEAL
OF APPROVAL BY
@GLAMOURMAGUK”
Industry acceptance
We recruited 4,511 Twitter users from an online
panel by asking a screener question upfront. Those
who claimed to use Twitter, out of a range of social
and digital platforms, went through to the study.
Each participant was randomly shown only one
piece of stimulus. The experimental design was
between subjects and approximately 215-220
individual respondents saw each piece of stimulus.
12
“OUR #STREETSTYLE EDIT
FROM #LFW IS NOW UP ONLINE!
OVERALL THE BUZZ WORDS ARE
#RELAXED #COLOURBLOCK
#CLEAN”
London Fashion Week (LFW)
“ENTER BY 4PM GMT SUNDAY,
WE’LL DM 1 RANDOM WINNER
WHO’LL WIN UP TO £500 & A
GOOGLE CHROMEBOOK”
Competition
Two response scales
To gauge levels of brand perception, each respondent was asked the same seven questions, each on a seven
point Likert Scale.7 These were:
Q3.1 PLEASE RATE THE TWITTER PAGE ON THE FOLLOWING 7-POINT BIPOLAR SCALE: WHERE 1 IS GOOD, AND 7 IS BAD
Q3.2 PLEASE RATE THE TWITTER PAGE ON THE FOLLOWING 7-POINT BIPOLAR SCALE: WHERE 1 IS FAVOURABLE AND 7 IS UNFAVOURABLE
Q3.3 PLEASE RATE THE TWITTER PAGE ON THE FOLLOWING 7-POINT BIPOLAR SCALE: WHERE 1 IS PLEASANT AND 7 IS UNPLEASANT
Q2.1 I HAVE A STRONG INTEREST IN RESIDENT (PLEASE RANK THE FOLLOWING STATEMENTS ABOUT RESIDENT USING A SCALE WHERE
1 = STRONGLY DISAGREE AND 7 = STRONGLY AGREE.)
Q2.2 I TRUST RESIDENT (PLEASE RANK THE FOLLOWING STATEMENTS ABOUT RESIDENT USING A SCALE WHERE
1 = STRONGLY DISAGREE AND 7=STRONGLY AGREE.)
Q2.3 I LIKE THE IDEA OF BUYING A PRODUCT OR SERVICE FROM RESIDENT (PLEASE RANK THE FOLLOWING STATEMENTS ABOUT RESIDENT USING A
SCALE WHERE 1 = STRONGLY DISAGREE AND 7 = STRONGLY AGREE. )
Q2.4 I WOULD RECOMMEND RESIDENT TO A FRIEND (PLEASE RANK THE FOLLOWING STATEMENTS ABOUT RESIDENT USING A SCALE WHERE
1 = STRONGLY DISAGREE AND 7 = STRONGLY AGREE. )
Using these questions we were able to create
two different scales. Questions 3.1 to 3.3 were
aggregated to create a ‘Likeability’ scale.
Questions 2.1 to 2.4 were aggregated to
create a ‘Consideration’ scale.
scale measures more reflective responses. Questions
around trust, purchases intent and advocacy demand
a greater level of thought and a consideration about
future actions, rather than just a reflexive feeling of
‘likeability’.
We focused on these two scales as each indicates
a slightly different behavioural response. The
‘Likeability’ scale measures responses that are more
instinctive and momentary, such as if they thought the
profile was ‘Good’ or ‘Favorable’. The ‘Consideration’
The questions that make up the ‘Consideration’ scale
are also far more associated with traditional measures
of brand perception and therefore may give a better
indication of how likely someone is to engage with the
brand on a commercial level.
IN SUMMARY, THE UNCONSCIOUS
CUES EXPERIMENT CONSISTED OF
THREE KEY ELEMENTS:
• An online panel being shown stimulus about a fictional brand’s Twitter profile
• Variable stimulus to explore the dynamics of multiple unconscious cues that form the Twitter user experience
• Two response scales to measure the impact of the cues on respondents’ propensity to like and consider the brand
7 Likert, Rensis (1932). “A Technique for the Measurement of Attitudes”.Archives of Psychology 140: 1–55.
13
THE RESULTS
Our findings fall into three major areas.
1. Unconscious cues on Twitter
profile pages do have a significant
impact on people’s perception of
the brand.
The cues impact both response scales – likeability
and consideration are both influenced by elements
of the Twitter user experience. This impact varies depending on the cue and across the range of variables
within that cue.
2. ‘Likability’ doesn’t always
correlate with ‘Consideration’.
Stimulus that positively influenced people’s propensity
to like a brand didn’t necessarily positively influence
people’s propensity to consider the brand. In other
words, brand’s likeability score does not predict its
consideration score. In fact, there are occasions
where the two scores are inversely correlated.
14
3. Unconscious cues influence
different audiences in different ways
Responses to cues vary across demographics and type
of respondent. As all responses were unconscious, this
suggests that respondents were interpreting the stimuli
in accordance with existing perceptions. Individuals
attached their own meaning to what they were shown.
We will now explore the findings in detail. In the results
section below all percentages quoted represent the
proportion of people selecting a score of five or above
for a given question or group of questions on the two
seven point scales. This represents the percentage of
people who scored 5 and above. Differences of 5% or
above are considered statistically significant.
THE RESULTS IN DETAIL
1. Unconscious cues on Twitter profile pages do have a significant
impact on people’s perception of the brand.
The results exhibit this pattern across four out of the five unconscious cues. We will demonstrate these in turn.
Followers
Firstly we will look at how the number of ‘Followers’ that a brand has impacts the perception of the brand.
On both the Consideration and Likeability scales, Followers have little impact at all levels. That is to say, at all
Follower levels tested – 358 to 2.7 million – Consideration and Likeability scores on each of the scales were very
similar.
However, as Graph 1 shows, very high Follower numbers have a significant impact in how much people ‘Trust’
the brand and also how much they would ‘Like the idea of buying a product or service from the brand’.
25% of people selected five or above in terms of buying a product or service across very low, low and high
follower numbers, this increases to 30% for very high Follower numbers. The percentage of people scoring five
or above for Trust also increase by 5%, from 18% to 23%, for very high Follower numbers.
35
GRAPH 1 - NUMBER OF FOLLOWERS
% WHO SCORED 5 OR ABOVE
30
25
20
15
10
5
0
358
7,573
636,000
2,700,000
NO. OF FOLLOWERS THE BRAND HAS
I TRUST RESIDENT
LIKE THE IDEA OF BUYING A PRODUCT OR SERVICE FROM RESIDENT
15
Tone of voice of biography copy
In terms of consideration, both the ‘funny’ and the
‘serious’ biographies score highest. There is no
statistically significant difference between the two for
questions of overall consideration, recommendation,
interest and trust. The ‘responsible’ brand biography
consistently scores the lowest.
Graph 2 shows that around 13% of people scored
five or above for the ‘funny’ biography, 12% for the
‘serious’ biography, but only 8% for the ‘emotional’
biography. It may be that, as this brand is unknown,
people prefer messages that provide humour,
information about the product or heritage of the
brand rather than CSR messages. It may also be that
messages on the subject of charity do not fit well with
the brands designed image or natural audience.
GRAPH 2 - TONE OF VOICE CONSIDERATION SCALE
14
12
% WHO SCORED 5 OR ABOVE
10
8
6
4
2
0
FUNNY
CONSIDERATION SCALE
16
SERIOUS
RESPONSIBLE
THE ‘SERIOUS’ BIOGRAPHY COMES OUT ON TOP IN TERMS
OF ‘TRUST’. APPROXIMATELY 24% OF PEOPLE SCORED
FIVE AND ABOVE FOR TRUST WHEN PRESENTED WITH
THE ‘SERIOUS’ BIOGRAPHY, 20% WHEN PRESENTED
WITH THE ‘FUNNY’ BIOGRAPHY, AND LESS THAN 15%
SCORED FIVED AND ABOVE FOR TRUST WHEN THEY SEE
THE ‘RESPONSIBLE’ BIOGRAPHY.
GRAPH 3 - GRAPH TONE OF VOICE, TRUST
30
% WHO SCORED 5 OR ABOVE
25
20
15
10
5
0
FUNNY
SERIOUS
RESPONSIBLE
TRUST
17
Promoted and non-promoted tweets
Graph 4.1 is slightly different from the other charts in the report. Rather than showing percentage of those who
scored five and above it shows the average (mean) scores, out of a total of seven, for each tweet shown to
respondents. The differences represented were shown to be statistically significant at 95% confidence interval.
What the chart shows is that promoted tweets consistently drive commercial awareness metrics, specifically
trust, willingness to buy and recommendation more than non-promoted tweets across all three tweets.
This isn’t to say that promoted tweets always drive consideration but promoted tweets prepare a brands followers
for a commercial conversation with regards to those key elements of brand consideration. Consideration is driven
by content and the context of the campaign.
3.4
GRAPH 4.1 - PROMOTED VS NON PROMOTED TWEETS - TRUST IN BRAND
MEAN RESPONSE
3.3
3.2
3.1
3
INDUSTRY ACCEPTANCE
EXPOSED TO PROMOTED TWEET
3.4
LFW
COMPETITION
EXPOSED TO ORGANIC TWEET
GRAPH 4.2 - PROMOTED VS NON PROMOTED TWEETS - OPENNESS TO BUYING FROM THE BRAND
MEAN RESPONSE
3.25
3.1
2.95
2.8
INDUSTRY ACCEPTANCE
EXPOSED TO PROMOTED TWEET
18
LFW
EXPOSED TO ORGANIC TWEET
COMPETITION
3.2
GRAPH 4.2 - PROMOTED VS NON PROMOTED TWEETS - WILLINGNESS TO RECOMMEND BRAND TO A FRIEND
MEAN RESPONSE
3.1
3
2.9
2.8
INDUSTRY ACCEPTANCE
EXPOSED TO PROMOTED TWEET
LFW
COMPETITION
EXPOSED TO ORGANIC TWEET
Following
Interestingly the number of other accounts that the brand follows seems to have a strong influence on people’s
overall consideration score. As the brand follows more accounts, consideration drops steeply from a high of
around 15% at a following number of 1,056 to a low of 8% for very high following numbers (12,122).
GRAPH 5 - FOLLOWING
% WHO SCORED 5 OR ABOVE
20
15
10
05
0
268
1,056
4,477
12,122
NO. OF ACCOUNTS THE BRAND FOLLOWS
CONSIDERATION SCALE
19
The pattern represented on Graph 5 – scores falling as the number of accounts the brand follows increases –
is replicated across all four components of the consideration scale. Scores for trust, recommendation, interest in
and willingness to purchase from all drop off steeply at ‘very high’ following numbers.
This may be because a brand with very high ‘following’ numbers is seen as indiscriminant in their use of the
platform or that they only follow others to gain Followers themselves, a practice known as ‘Follow Back’.
Interestingly, the likability of the brand does not have the same pattern. This will be discussed in the next section.
2. ‘Likeability’ doesn’t correlate with ‘consideration’.
Often it is assumed or even expected that the ‘likeability’ of a brand should go hand-in-hand with levels of
‘consideration’. What this study has shown is that this is not always the case.
We have found that in many cases a change in one indicator will lead to an increase in likeability but a decrease
in consideration. Take graph 6 for example. This graph shows that the responsible biography scored the highest
in terms of likeability, but the lowest for consideration.
%WHO SCORED 5 OR ABOVE
GRAPH 6 - TONE OF VOICE, LIKEABILITY VS CONSIDERATION
18
16
14
12
10
8
4
2
0
FUNNY
CONSIDERATION SCALE
SERIOUS
RESPONSIBLE
LIKEABILITY
This pattern is repeated across many of the variables tested. For example, average scores for the non-promoted
tweets are 8% higher on the ‘likeability’ scale than on the ‘consideration’ scale (see Graph 7).
When we compared the average scores of the promoted vs. non-promoted tweets we found that promoted tweets
scored higher for ‘consideration’ while the non-promoted tweets scored higher for ‘likeability’.
This is perhaps because the ‘promoted’ badge is a signal that makes people automatically associate that tweet
with something commercial, generating a higher score on the ‘consideration’ scale. Organic tweets may be more
liked simply because they are received on an ‘opt-in’ basis, as the user has made a conscious choice to follow
tweets from the brand.
20
GRAPH 7 - PROMOTED VS NON-PROMOTED TWEETS (SCORING 5 AND ABOVE)
20
18
16
14
12
10
8
6
4
2
AVG. NON-PROMOTED %
AVG. PROMOTED %
CONSIDERATION SCALE
LIKEABILITY
As can be seen in graph 8 this pattern persists. The profiles with very low and very high following numbers are
the most liked but the least considered.
GRAPH 8 - FOLLOWING, CONSIDERATION VS LIKEABILITY
% WHO SCORED 5 OR ABOVE
20
15
10
5
0
268
CONSIDERATION SCALE
1,056
4,477
12,122
LIKEABILITY
21
3. Unconscious cues influence different audiences in different ways
There are some clear demographic differences across all variables and on both the likeability and the
consideration scale. Looking firstly at the scores for likeability and consideration overall – across all 21 of the
variables tested – graph 9 clearly illustrates this difference.
The graph shows the overall scores for likeability and consideration cut by the claimed level of confidence in
using the Internet; 1 being a complete novice and 7 being an expert.
GRAPH 9 - OVERALL SCORES BY CONFIDENCE IN USING THE INTERNET
%WHO SCORED 5 OR ABOVE
30
25
20
15
10
5
0
NOVICE
02
03
04
05
06
EXPERT
INTERNET USAGE CONFIDENCE
CONSIDERATION SCALE
LIKEABILITY
It shows a clear linear relationship between confidence in using the Internet and consideration scores.
This indicates that those who are most comfortable with the Internet are most likely to trust, recommend, be
interested in or be willing to buy a product or service. However, conversely those who feel that they are less confident online are least likely to score high on ‘consideration’ but most likely to score high in terms
of likeability.
22
There is also a variation in age across the two scales. Older people are more likely to score any piece of stimulus
higher on the ‘likeability’ scale compared to the ‘consideration’ scale. The age group most likely to score things
highly on the consideration scale is 25-34s. Around 18% of all 25-34s score any piece of stimulus five or higher.
This may be driven by the differences in Internet confidence across the age groups. The data shows that older
people are more likely to score themselves closer to the novice end of Internet confidence usage.
%WHO SCORED 5 OR ABOVE
25
GRAPH 10 - CONSIDERATION AND LIKEABILITY BY AGE
20
15
10
5
0
18-24
25-34
CONSIDERATION SCALE
35-44
45-54
55-64
65+
LIKEABILITY
Looking at the demographic differences within specific variables we see that younger people – 18-34s – are
most likely to prefer higher Follower numbers (the percentage for 55-64s is high here too, but there is a low
sample size in this group when broken down to this level of granularity).
23
APPROXIMATELY 10% MORE 18-34S
SELECT FIVE OR ABOVE FOR VERY HIGH
FOLLOWER NUMBERS COMPARED TO
VERY LOW FOLLOWER NUMBERS.
GRAPH 11 - FOLLOWERS CONSIDERATION SCALE BY AGE
35
%WHO SCORED 5 OR ABOVE
20
15
10
5
0
VERY LOW
LOW
HIGH
FOLLOWER NUMBERS
18-24
24
25-34
35-44
45-54
55-64
65+
VERY HIGH
MEN ARE MORE INFLUENCED BY HIGH
FOLLOWER NUMBERS COMPARED TO
WOMEN
This may be because of confidence in interacting with the fashion sector. Women are perhaps more confident
when considering a brand such as Resident, and therefore are less likely to look for social validation in the form
of greater Follower numbers.
GRAPH 12 - FOLLOWERS CONSIDERATION SCALE BY GENDER
20
18
%WHO SCORED 5 OR ABOVE
16
14
12
8
6
4
2
0
VERY LOW
MALE
LOW
HIGH
VERY HIGH
FEMALE
25
GRAPH 13 - TONE OF VOICE OF BIOGRAPHY BY GENDER
16
14
%WHO SCORED 5 OR ABOVE
12
10
8
6
4
2
0
FUNNY
MALE
SERIOUS
RESPONSIBLE
FEMALE
WOMEN MOST PREFERRED THE
‘FUNNY’ BIOGRAPHY, BUT WERE
ALSO SLIGHTLY MORE RESPONSIVE
TO THE ‘RESPONSIBLE’ BIOGRAPHY
COMPARED TO MEN.
Younger people clearly had a preference for the ‘funny’ biography in terms of consideration while older people
preferred the ‘serious’ biography. Women most preferred the ‘funny’ biography, but were also slightly more
responsive to the ‘responsible’ biography compared to men.
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CONCLUSIONS AND IMPLICATIONS
1. Be clear on what you’re trying
to achieve
What have we found?
The scores for likeability and consideration do not
respond in the same way to changes in the variables.
This means that higher levels of likeability do not lead
to higher levels of consideration.
Why do we think it’s happening?
The questions relating to likeability can be answered
quickly and instinctively as an unconscious, emotional
response. Though still capturing an unconscious
response, consideration is a more reflective,
considered scale – respondents are being asked to
think through and predict their likely actions.
What are the implications for brands?
Think about what kind of response you are looking
to generate with your Twitter presence. What does
your brand biography say about you? Is your content
strategy more focused on building brand affinity or
on future purchase intent? Think about how you can
structure followers’ experience to emphasise the
approach and make the intended response more
likely.
2. Be clear on who you’re trying to
reach it with
What have we found?
Higher levels of Likeability correlate with older
respondents and respondents who are less
experienced in Internet and/or social media.
Consideration scores are higher amongst expert
Internet users and younger people.
Why do we think it’s happening?
Older and inexperienced Internet users have less
to compare the stimulus to as they may not have
much knowledge of online shopping or commercially
engaging with brands on Twitter. They may also be
more risk averse when it comes to consideration.
Younger and more experienced users are more
familiar with brands on Twitter and are perhaps less
easily impressed.
What are the implications for brands?
Understand the comfort levels of your audience
and which approach is most likely to nurture your
relationship with them. When it comes to less
experienced users, don’t overestimate ‘liking’
metrics and make sure you’re doing enough to build
consideration. For younger audiences, don’t be afraid
to close the deal – they’re far more comfortable with
the idea of entering into a transactional relationship.
It’s important to note that this could be a function
of our fictional brand and its category appeal. Make
sure you understand which audience segments these
behavioural approaches might apply to.
3. Strike the right tone for your
brand
What have we found?
Of the three biographies created, the ‘funny’ and
‘serious’ biographies were the most considered.
When it comes to likeability, however, the emotional
biography scored highest.
Why do we think it’s happening?
The questions on the Likeability scale make it
likely that the responsible biography is the most
immediately appealing. We think the ‘serious’
biography may lead to consideration because it is
the most informative – it appeals to a more reflective
response and consideration of how a respondent
might feel about the brand.
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What are the implications for brands?
Where humour is a key part of a brand’s values
and architecture, a humorous tone with Twitter can
add value. However, it may inhibit users’ propensity
to enter into a more intimate relationship with
you. Perhaps this mirrors the shopping and offline
experience of a clothing retailer. Credibility is gained
through valuable and effective interactions – these
create expectations that may be carried into the
online experience.
This research shows that the brand biography can
be used as a tool to conduct particular types of
conversation with your audience. It is a variable
that audiences use to make judgments about the
character of the brand. When launching a brand
advertising campaign, reframing the biography in
a more human or humorous tone may help drive
likability as people discover the brand on Twitter.
Conversely, a more serious tone in the biography
would help drive commercial consideration during a
large DR campaign.
On Twitter, be clear on the kind of tone a customer
would expect you to strike, and make sure you
consistently meet those expectations.
4. Use the right tools for the job
What have we found?
Unpromoted tweets were liked more than the
promoted tweets, as we might expect. However,
promoted tweets appear to trigger a better response
on the ‘consideration’ scale. This was observed at
a population level, but the effect was even more
pronounced among more experienced users.
Why do we think it’s happening?
Users ‘opt-in’ to see unpromoted tweets, but
promoted tweets suggest credibility and scale to a
brand. Perhaps a presence on paid formats suggests
a brand being sufficiently well established to be able
to afford activity of this kind.
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What are the implications for brands?
Promoted tweets offer a chance to build credibility
and consideration. They could be particularly
useful to support a campaign focused on sales
or purchase intent.
5. Think about who and what the
users will compare you to
What have we found?
Very high numbers of Followers build levels of trust
and purchase intent. There is a gender difference,
however – women tend to be interested in lower
numbers of Followers while for men the numbers
need to be higher
Why do we think it’s happening?
We would expect to see higher levels of Followers
create a norming effect. This wouldn’t explain the
gender difference, however. Our hypothesis is that
within the fashion category, greater popularity might
not always result in increased purchase intent.
Exclusivity is a category motivator, and this might
be expected to apply more visibly to informed and
confident female respondents. Male respondents
might be expected to look for reassurance in higher
numbers and greater perceived popularity.
What are the implications for brands?
In social, it is important to balance scale with
intimacy. Our pilot experiment showed that larger
communities generated positive responses in
diminishing returns. The results of this experiment
suggest building your follower count isn’t enough on
its own to drive a brands commercial objectives on
Twitter. Category norms can also be played out on
social media so it’s important to think about these as
part of an experience that users share with everyone
else. Therefore, followers are an important part of
the equation, but as part of a wider strategy around
who you are trying to reach and how you are going to
reach them.
FINAL THOUGHTS
Many clients ask agencies, ‘what should our Twitter
strategy be?’
A high score on the ‘consideration’ scale is
characterised by:
The frustrating answer that clients sometimes receive
is, ‘it depends’.
• An audience likely to be 25-34
• With a high level of confidence using the internet
• Motivated by high follower numbers – especially men
Twitter is a public sphere, a social medium. People
use it for many different reasons. All, or just merely
most of, human life is here. It is subject to the rules of
human behaviour, just like any other area of life.
That makes it complicated. There isn’t necessarily
a single, ‘right’ way to use Twitter. Throughout this
report we have recorded the different effects that
cues had on different types of user. There are many
different drivers of perception open to brands on
Twitter. Understanding the way these drivers relate to
your brand or business challenge can help identify the
right way, based on a desired outcome.
Consider these two scenarios, developed by drawing
on the drivers that correlate most strongly with high
scores on our two different scales:
A high score on the ‘likeability’ scale is
characterised by:
• An audience of people likely to be older than 45
• With a low level of confidence using the Internet
• Not motivated by Follower numbers, apart from men, who are more likely to like a brand if it has fewer Followers
Stimulus that caused people to consider our brand
resonated with a very different audience to the
one that found the brand to be likeable. That has
significant implications for brands using the platform
to talk to everyone at the same time, or for brands
unsure of what they’re trying to achieve with their
Twitter presence.
Targeting is becoming an increasingly important part
of the Twitter experience. While brands have become
adept at creating content that resonates with their
target audience, we think the cues within the user
experience offer another more nuanced targeting
opportunity.
We hope this research offers brands the chance to
do that.
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AUTHORS
Joe Gladstone & Jon Jachimowicsz
PhD Researcher
in Behavioural Economics,
University of Cambridge Judge Business School
Nick Siantonas
Behavioural Strategist, Isobar
James Caig
Head of Strategy, Isobar
Stephen Donajgrodzki
Senior Partner, Isobar
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