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Are you
Digitally
Normal?
Digital Culture and
the Digital Normal
Index
1
Contents
Executive Summary........................................................................................................................................... 2
1. Introduction ............................................................................................................................................ 3
1.1. Digital Cultures ........................................................................................................................................ 3
1.2. Infrastructure ............................................................................................................................................ 5
1.3. Digital ‘Normal’ Index ............................................................................................................................... 6
2. Results .................................................................................................................................................... 8
2.1. The Strange Case of the United States ................................................................................................... 8
2.2. Banking on Information ............................................................................................................................ 9
2.3. Private vs. Social Entertainment ............................................................................................................ 10
2.4. The Odd One Out .................................................................................................................................. 10
3. Conclusion ........................................................................................................................................... 12
4. Appendix .............................................................................................................................................. 13
4.1. Methodology .......................................................................................................................................... 13
4.1.1. Behaviour Score(s) ................................................................................................................... 13
4.1.2. Infrastructure Score .................................................................................................................. 13
4.2. Sources .................................................................................................................................................. 13
4.2.1. Mindreader ................................................................................................................................ 13
4.2.2. International Telecommunications Union (ITU) ........................................................................ 14
4.2.3. Net Index .................................................................................................................................. 14
4.2.4. comScore .................................................................................................................................. 14
4.2.5. World Bank ............................................................................................................................... 14
4.3. Further information ................................................................................................................................ 14
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Executive Summary
The fragmentation of media platforms has made thinking about the internet as one homogenous entity
hopelessly simplistic. At the same time, differing levels of infrastructure makes comparing behaviour between
countries difficult.
This research project aims at exploring how internet usage and behaviour link to infrastructure, how countries
are developing and how the internet is perceived and utilised across the world. Mindshare presents a new
approach for thinking about the internet in more varied terms, while maintaining a simple, usable framework
for planners and marketers.
Using Mindreader, Mindshare’s proprietary planning survey, statistical analysis reveals four globally consistent
groups of behaviours, each relating to the motivation behind the behaviours themselves. These are
Information; Self-Expression & Communication; Transaction; and Entertainment. Understanding how these
factors relate to each offers a window, not only into how the internet is used by people across the world, but
how it is perceived by the culture as a whole.
Comparisons between these groups of behaviour and infrastructure consistently reveal u-shaped
relationships, with infrastructure leading to higher behaviour when it is either very low (early adopter bias) or
very high (high societal investment). These patterns are used to generate benchmarks for a ‘typical’ country:
i.e. what is ‘normal’ for each degree of infrastructure.
To make differences easier to identify, the Digital Normal Index is presented for each motivation in each
country. This score sets the ‘normal’ benchmark at 100 and reports the proportional distance from this
benchmark. This provides a context to reveal each country’s digital profile in more detail, providing a rich vein
of insights into how people use online media across the globe, and how different cultures are represented
online.
This Digital Culture framework provides a vast potential for insight into different countries and their varying
digital landscapes. The findings reported here include the entertaining nature of traditionally social activities in
the US; the nature of, and motivations behind, online banking across the world; differences between private
and social entertainment activities; and the true impact of Internet infrastructure on Transaction motivated
behaviour.
The research presented here forms a powerful tool for Mindshare to understand what motivates consumer
behaviour. This understanding can help planners make communications relevant to the context, and allows
Mindshare to target messages quickly, and adapt them to suit the occasion.
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1. Introduction
In May 2013, according to comScore, over 841 million people across the world visited Facebook on a PC or
laptop. Between them they made over 24 billion visits (each lasting an average of 13 minutes), and viewed
408 billion pages.
But consider. Those figures account for all pages under the Facebook umbrella, including Instagram. Over the
course of the month, the average user viewed 485 different pages. Today, Facebook means many different
things to different people: it is a platform for self-expression, a way to keep in touch with friends, a source of
information and news and, with Facebook Marketplace, even a way to buy things.
Facebook is not alone. It echoes trends seen across the whole web: portals no longer cater for single niches,
but inhabit multiple areas, serving many different, even contradictory, needs.
It should come as no surprise then, that thinking about the internet as one homogenous medium is out-dated
and overly simplistic.
At Mindshare, we have been working on ways to approach thinking about the internet in more varied terms,
while still keeping the myriad possible behaviours manageable for planners and marketers.
At the same time, differing sophistication of infrastructure makes comparing behaviour between countries
difficult.
It is often assumed that users in countries with slower connections or lower broadband penetration will be less
advanced than those in countries with better services, simply because the connection available isn’t suited to
more data-intensive activities that are usually classified as ‘advanced’. We tend to think, rather unfairly, of
countries with lower internet penetration as primitive, and countries with high penetration as the trend setters.
In reality, things are not so simple. In countries where only a minority have access to the internet those who
do have access are likely to be early adopters, and so more advanced and enthusiastic than users where
access is more ubiquitous.
This research project aims to explore how internet usage and behaviour link to infrastructure, and which
countries are developing in which ways, as well as providing a framework for understanding the motivations
behind different types of online behaviour.
1.1. Digital Cultures
In order to discover dimensions underlying and motivating behaviour, detailed statistical analysis is performed
on data collected in Mindreader, a large-scale research tool with a global footprint.
Factor analysis, focusing on data collected around the frequency of 30 online activities, ranging from social
networking or keeping up with news or current affairs, right through to pornography and online gambling, is
employed to examine the inter-correlations between items and uncover any common dimensions
underpinning the item. Detailed explanation of the analysis can be found in the methodology section of the
appendix. This analysis, conducted for each country independently, consistently produces four factors, each
relating to the motivation behind the behaviours themselves.
These factors are:
Information,
Self-Expression & Communication,
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Transaction,
Entertainment.
While these motivations are, by their nature, inter-related, they reveal key differences in the mind-set of
consumers when engaging in different activities. However, as all countries are treated independently in the
analysis, the behaviours that contribute to each factor are not always the same. For instance, online banking
is, in most countries, a transaction motivated behaviour, but in some countries (e.g. Canada, USA and Italy) it
is seemingly motivated instead by a desire for information.
The changing definitions serve to cement the factors as embodying the motivations behind behaviours rather
than simply collecting the behaviours together under a common descriptive label.
As demonstrated by the Facebook example in the introduction, it should be noted that some of the behaviours
examined serve more than one need. For instance, in a large number of countries researching and comparing
products contribute to both Information and Transaction. This hybrid behaviour is understandable when
considered alongside the nature of the underlying motivations and the nature of the internet. All four factors
demonstrate cross-over with the others, though of them all, Transaction is the most independent, linking
mainly to Information rather than the other factors.
The other factors show a lot of common ground
and, while distinct as motivations, a degree of
cross-pollination between them can be
demonstrated. For example, Entertainment can be
seen to comprise of several different types of
entertainment: some have a social element, such
as dating or playing games on a social network
(which sometimes even stray into Self-Expression
& Communication, depending on the country),
others more private and personal, like gambling or
pornography, while still others appear more
informative, such as listening to podcasts or radio
shows or watching TV programmes.
This has not always been the case; the blurring of
the lines between the drivers of behaviours is a
relatively recent development. Analysis of similar
data collected in early 2010 showed a comparable factor solution, but revealed five rather than four
motivations, with Self-Expression and Communication each representing a distinct motivation, rather than
being inseparable as they are in the more recent analysis presented here.
These overlapping boundaries, along with the notion that each need-factor’s components can vary by country,
mean that quantifying the differences between countries is of the upmost importance. Understanding how
these factors relate to each other within countries offers a window not only into how the internet is used, but
how it is perceived by the culture as a whole.
If, for instance, Information appears as a dominant factor in a country, it suggests that the internet is primarily
seen as a tool for gathering information, but not necessarily as a platform for acting upon that information to
either conduct a transaction or to share it with other people. These relationships can give an important insight
into that country’s Digital Culture, revealing a natural inclination when it comes to the internet.
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That is not to say that the people in this hypothetical country do not engage in Transaction or Self-Expression
& Communication online. It reveals instead that this is not the motivation they associate with using the
internet, and so is perhaps a harder thing to motivate people to do within a marketing or media plan.
To this end scores for each dimension for each country were created, using the results of the factor analysis
to develop an algorithm that scores each respondent on all four dimensions. This provides a score for each
country, quantifying their Digital Culture.
1.2. Infrastructure
Before considering the findings from these Digital Cultures it is important to account for practical differences
between countries. As noted in the introduction the impact that infrastructure and development has on digital
consumption is sizable, but perhaps not clear in all cases. Development of infrastructure, it could be argued,
says something about a country’s approach to the internet and its cultural importance, though the extent of
this is unclear.
To examine the relationship between infrastructure and behaviour an ‘infrastructure score’ was computed.
This score took the penetration among the population and moderated it using a measure of connection
quality, thereby balancing countries with ubiquitous low quality connections with those with uncommon but
high quality connections (detailed information on the sources used and methodology followed is in the
appendix). It should be noted that while the Digital Culture figures introduced above are effectively device
neutral, the lack of any standardised measure of connection quality on mobile devices means that the
infrastructure score is primarily a measure of the ubiquity of high-speed internet to homes, and connections
made usually with PCs or laptops.
Comparisons between this infrastructure score and the Digital Culture scores reveal consistently u-shaped
relationships, as demonstrated for Self-Expression & Communication in figure 2. Infrastructure seems to lead
to higher behaviour when it is either very low, revealing an early adopter bias among the few users who have
access, or very high, demonstrating a societal investment in internet as a whole, with highly developed
infrastructure combined with high usage. Indeed, it is only when the infrastructure is not so highly developed,
and yet still relatively strong that behaviour drops across all four factors.
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The results of this analysis for all four factors are represented in figure 3, and reveal the relationship between
each behaviour factor and infrastructure. In all cases, the most effective line at predicting the pattern reveals
the u-shaped relationship described above. It should be noted that these lines are not equally good at
describing the pattern of variables, most notably the line for Transaction. While this line follows the same
polynomial pattern, the curve is subtle and almost flat. It also has a much lower R2 figure than the others,
suggesting that digital infrastructure is not strongly related to whether people use the internet for transaction.
This idea is discussed in more detail below.
1.3. Digital ‘Normal’ Index
Given the u-shaped relationship between infrastructure and behaviour, it is necessary to adjust the behaviour
scores in order to compare countries directly. Adjusting the raw behaviour scores for the impact of
infrastructure in early adopter countries and in those with high societal investment without eliminating nuances
behind behaviours enables us to measure a country’s digital culture and glimpse their true relationship with
the internet.
The patterns in figure 3 can also be interpreted as the levels of behaviour that would be expected for any
given level of infrastructure. The trend-line provides behaviour scores for a ‘typical’ country with a given
infrastructure score, and therefore predicts what is ‘normal’ for each degree of infrastructure.
This ‘normal’ score is taken as a benchmark in each country, and the expected behaviour score (i.e. position
on the line) calculated for each country’s infrastructure score. When this expected score is compared to the
observed behaviour score, it provides a context against which to examine each country’s digital culture in
more detail.
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As this ‘normal’ line represents the best fit to the patterns of data in figure 3 there are, inevitably, countries
both above and below the line. It is the distance from the line which can be so revealing, especially when
compared across the four motivations of behaviour.
For instance, Russia scores very highly on Entertainment, appearing higher than the ‘normal’ line, while
Information falls some distance below what would be expected given Russian infrastructure. Self-Expression
& Communication and Transaction scores in Russia are much closer to what would be predicted. These
patterns suggest a strong cultural bias towards the internet as an entertainment medium rather than a
platform for gathering information.
In order to make differences easier to identify an index score is given to each motivation in each country. The
scores set the ‘normal’ benchmark at 100, and report the proportional distance from this benchmark. They
then represent the relationship between each country and the expected ‘normal’ figure, and so have been
named the Digital Normal Index.
The figures for all 33 countries are reported in table 1 and the results are discussed in more detail below.
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2. Results
The Digital Normal framework provides a wealth of insight into different countries and their digital landscape.
Presented here are a handful of stories and results extracted from the framework presented above, and
should not be read as a comprehensive list.
2.1. The Strange Case of the United States
Despite being the birthplace of social media the US is actually below the level of Self-Expression &
Communication that would be expected given its infrastructure.
However, a glance at the same figures quoted in the introduction, but only for the US, reveals that 144 million
Americans used Facebook in May 2013 - 65% of the internet population. Clearly the behaviours enabled by
the Facebook platform are not unpopular with American users.
What is unusual is what motivates these behaviours.
In America, unlike most countries, many of these traditionally ‘social’ activities are actually driven by a desire
for entertainment – a motivation to spend a few minutes of downtime.
The definitions of each factor, presented in table 2, reveal that activities like blogging or uploading one’s own
content are actually more readily associated with Entertainment than with Self-Expression & Communication.
This difference in mind-set reveals an important distinction in how these behaviours manifest themselves and
the type of activity it reflects. For instance, someone blogging in the US does not seem to be posting content
to tell the world about themselves but for the sheer joy of writing.
A quick check of Twitter’s trends validates this idea. At the time of writing five of the top nine trending topics
(the 10th was ‘promoted’ and so ignored
1) in the US are about entertainment topics. In contrast the UK shows
four of the nine being Self-Expression and Communication, as predicted by the factor definitions. In both
countries the primary act is one of discussion with other people but the mind-set of the user, and their
motivations, are notably different.
1 #YourLifeSkills set as promoted trend across all countries where trend information was available from Twitter.com. Specific campaign
details unavailable, but market price reportedly at $200,000 (USD) per day: http://dthin.gs/WBf1YA
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This insight is a valuable one for brands and advertisers wanting to engage with consumers through this
‘social’ platform – whether the consumer is online to communicate or to be entertained alters the type of
messages that will be successful.
2.2. Banking on Information
One of the differentiating factors across the world is which activities fall into Information and which fall into
Transaction. As mentioned above all four motivations are related and, as demonstrated in the USA, Self-
Expression & Communication and Entertainment see some items flit between them. Information and
Transaction enjoy a similarly open relationship. These seem even more flexible than the other two with items
readily swapping between the two, or even sitting happily on both factors.
The usual suspects are online banking and researching products, which are very often seen loading onto both
sets of motivations. Considering the nature of researching products (i.e. finding out information in order to
complete a transaction) this is not surprising at all. It is unusual to find it contributing to only one factor.
Online banking is more of an enigma. It
seemingly belongs under the Transaction
motivation but it is sometimes motivated by a
desire for information. In the countries where it
lies solely on the Information factor (USA and
Japan), it seems that the motivation behind online
banking is not to conduct one’s affairs but simply
to discover more about the state of those affairs.
It should be noted that of all the countries where
banking falls onto the Information factor, those for
whom it only falls on that factor are very much in
the minority. More usually it sits comfortably over
both motivations, indicating that while people in
these countries go online to find information
about their finances they will then, without
breaking their stride, act upon this information to
conduct some sort of transaction (see Figure 4).
In this vein online banking can be seen to consist of two components: one of discovery and one of action. In
the large majority of countries both of these are motivated by the end goal – performing a transaction. In a
few, the second component does not form any large part of the behaviour, while in others the two actions are
distinct so the behaviour is marked by two simultaneous motivations.
This type of insight into how and why people use the internet can be invaluable for brands to understand. In
this case the obvious application is to international consumer banks. Notably when thinking about the path
consumers take through online banking applications and what it is the consumer actually wants to accomplish.
While the multiple motivations examined above make online banking an interesting case the Digital Normal
Index, and the Digital Cultures that drive it, can be used to identify what consumers are trying to achieve when
they initiate any behaviour online. This enables planners and marketers to adapt communications directly to
the mind-set of consumers when performing certain actions, helping to get closer to that grail of digital
marketing – relevance.
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2.3. Private vs. Social Entertainment
In the age of social media it is easy to forget that the internet is not a completely social medium, and there are
several activities which are, by their very nature, more personal and more private.
That is not to say that they are unpopular. comScore report nearly 42% of the global online population visited
‘XXX adult’ websites in May 2013, 9% used an online dating website, while 9% gambled or placed a bet
online.
In most countries that is all there is to the story: these activities simply form a sub-sector of the Entertainment
factor but sit comfortably alongside other activities like watching TV and video online.
In some countries the impact of these activities is more dramatic.
In China these activities are conducted in such different mind-sets that they form a secondary factor of their
own, a more private form of entertainment. As this private factor emerges, more traditional modes of
entertainment join with the socially oriented Self-Expression & Communication factor, illuminating the
proximity of these behaviours to the social sphere in and the overwhelming importance of the social
experience in China.
This emphasises the split nature of Entertainment discussed above, in that it can be seen to be in close
proximity to the other factors. It is not only Self-Expression & Communication that attracts new items as this
relative proximity changes between countries. In China the inclusion of these more private entertainment
behaviours causes other entertainment behaviours to join the social factor, in Chile they flee to the information
factor demonstrating that, in Chile, Entertainment and Information are closer than Entertainment and Self-
Expression & Communication.
In Chile the behaviour forcing the sub-factor can actually be seen to be playing online video games with other
people – one of the more social (yet paradoxically isolated and private) entertainment behaviours,
demonstrating the differing proximity to the other Digital Cultures.
While these more adult, private or personal behaviours serve to disrupt the otherwise stable Digital Cultures
solution, it is important to note that they have been removed from the analysis. Not only because they diverge
from the theoretical framework appearing from the rest of the world but also because they display statistical
issues, such as low variance (i.e. everyone answered the same way), or low commonality with other items,
skewing the rest of the analysis. Because of these issues the behaviours are removed for statistical hygiene.
The shift in the factor solution resulting from their exclusion shines a light on the inter-relation between the
factors. This in turn adds nuance to the factors in each country, helping chart the undulations in the global
digital landscape.
2.4. The Odd One Out
As has already been noted, Transaction is one of the more isolated factors in the Digital Cultures framework
and has a much weaker relationship with infrastructure than the others. This can be seen in figure 6.
It seems that ecommerce and other online transaction based activities are not influenced dramatically by the
internet infrastructure in a country but is perhaps more affected by other factors.
This makes some sense when considered in conjunction with what the infrastructure score represents: the
combination of ubiquity and quality of internet connections in a country. When it comes to transactions there
are perhaps greater issues to consider, such as online security or the physical delivery services available.
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It is perhaps worth considering that ubiquity and quality relate mostly to Self-Expression & Communication
and Entertainment. The first relies on friends and peers also being online (i.e. ubiquity) and the second
requires large amounts of data to be streamed (i.e. connection quality/speed).
Future exploration of these ideas is needed but introducing measures of security and trust might go some way
to illuminating these issues. These go beyond the internet infrastructure measures we wanted to isolate in this
analysis and therefore are not included here.
A quick foray into old Mindreader data shows a
relatively flat relationship between levels of trust
and transaction scores. Figures from the World
Bank on the number of secure internet servers
show an equally unrevealing relationship with
Transaction.
It is interesting to note that the figures on relative
security link very closely to the infrastructure score
generated here (see figure 7). This not only lends
credence to the infrastructure measure as one of
internet development but also suggests that the
added level of detail would not necessarily improve
it. It also demonstrates that the transaction picture
is a complex one requiring more investigation to
unravel fully.
For marketers it is important to remember that the success of any ecommerce activity will not be governed by
the level of development of the internet. While there are sizable differences between countries these are not
wholly attributable to the online infrastructure. Other cultural influences play a large part in predicting the
behaviour of consumers across the world and the success of any activity, reinforcing the idea that no
behaviour occurs in isolation.
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3. Conclusion
The Digital Cultures framework forms a simple platform for looking at global online behaviour. That the tenets
of this framework are simple does not obscure the nuance between countries and it can serve to emphasise
and reveal differences between countries, or even differences between single behaviours. Crucially, it allows
planners and marketers to consider consumer behaviour while keeping sight of the overall context in which
the behaviour takes place.
Applying these Cultures to levels of infrastructure also creates an all-important ‘normal’ benchmark against
which things can be measured. This provides context for each type of behaviour, revealing patterns of
behaviour that can be analysed and interpreted against a norm.
This report demonstrates how these comparisons to normal can be used to reveal a wealth of insight into how
people use online media across the globe, and how these online ecosystems function. These insights can
range from explorations of individual countries and their own internal nuances, through to examinations of
single types of behaviour and what motivates different people to engage in them.
The framework illuminates what it is that defines behaviour. Entertainment and Self-Expression &
Communication quite readily relate to the overall internet infrastructure of a country and some solid
predictions can be made based on this relationship. Transaction and Information have a less comfortable
relationship with infrastructure, suggesting more cultural nuance than just availability lies behind these factors.
This is worthy of further exploration and more statistical testing. Such exploration promises rich insights into
digital media and online behaviour, such as those presented here.
The Digital Cultures and their application to the question of ‘digital normality’ form a powerful tool for
Mindshare’s planners and strategists to understand consumer behaviour and, more importantly, what
motivates that behaviour. Understanding the mind-set of people helps us develop communications
appropriate to the moment and allows Mindshare to adapt messages quickly to suit different contexts.
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4. Appendix
4.1. Methodology
4.1.1. Behaviour Scores
Measures of behaviour are generated using factor analysis on data taken from Mindreader 2011.
This survey contains a battery of online behaviours and collected frequency information for each of these.
These data are normalised for each country; they have a mean of 0 and a standard deviation of 1 (z-scores).
The factor analysis, conducted for each country and factors identified independently, uses Principle
Component Analysis and is rotated using the Oblimim rotation method. Items with low variance (such as email
and using search engines) are removed prior to the analysis for all countries and items with high co-variance
or low variance within a country are removed on a case by case basis.
It is worth noting that the factors are consistent across 33 of the 36 countries analysed. The remaining three
produce nonsensical factors that cannot be identified or be reconciled by removing items with high co-
variation or low internal variance.
To generate scores per respondent the factor loading for each item on each factor is squared (items without
strong loadings for that factor are treated as zero), and used as an item weighting. Each respondent’s answer
for each question is multiplied by this weighting and then added together giving a respondent score for that
dimension.
All scores are then averaged by country to generate a single score for each, which is used in the analysis.
4.1.2. Infrastructure Score
The infrastructure score is calculated using information from the ITU and Net Index and is constructed to be
both a measure of the population penetration and the quality of the connections that are going on.
These scores are calculated by country as follows:
% of Population who are Internet users * Average connection speed (MB/s)
A high score is gained by having ubiquitous high-speed internet rather than just high penetration.
4.2. Sources
Information used in this analysis comes from a number of different sources. The primary sources are listed
here. Only countries for which all data could be obtained are used in the final analysis.
4.2.1. Mindreader
Mindreader is a proprietary research source developed by Mindshare.
Using an online survey in countries across the world, Mindreader allows us to get a global idea of media
habits and lifestyle of digital consumers.
14
We have completed 5 waves of the study and currently cover 42 markets. Mindreader is conducted using an
online panel, with a sample of 1000 respondents in each market.
For more information, see http://mindreader.mindshareworld.com/
Data used here were collected between July and August 2011.
4.2.2. International Telecommunications Union (ITU)
As the UN specialised agency for information and communication technologies ITU is the official source for
global ICT statistics. One of its core activities is the collection, verification and harmonization of telecommunication/ICT statistics for about 200 economies worldwide. It includes data on the fixed telephone network, mobile cellular services, Internet/broadband, traffic, and prices of ICT services, as well as data collected from national statistical offices.
For more information, see http://www.itu.int/en/ITU-D/Statistics/Pages/about.aspx
4.2.3. Net Index
Net Index measures speed and quality of internet connections across the world, based mainly on compiling
anonymous data from users of Speedtest.net and Pingtest.net.
For more information, see http://www.netindex.com/about/
4.2.4. comScore
comScore provides an online audience measurement tool through a large panel of users whose behaviour is
directly recorded, providing robust behavioural data.
For more information see http://www.comscore.com/About_comScore
4.2.5. World Bank
Data on secure servers were taken from the World Bank’s data archives, and can be accessed here:
http://data.worldbank.org/indicator/IT.NET.SECR.P6. These data were charted on a logarithmic scale for ease
of interpretation in Figure 7.
4.3. Further information
For more information on this research, supporting materials or clarifications, please contact Tom Morgan
