This segment is not currently engaged with the arts. They prefer informal leisure activities like watching sports on TV and spending time at their local pub. The arts are an unfamiliar concept for this group and need to be positioned as a casual leisure opportunity, such as craft activities. Outreach at pubs, sports clubs, and through local media may be effective ways to engage this segment.
2. About our segmentation research
Arts Council England’s segmentation analysis is based on an analysis of the patterns of arts
engagement and attitudes towards the arts, drawn from Taking Part, a large-scale national survey of
cultural engagement.
2011 has seen us update our original segmentation work from 2008*, using the most recent Taking
Part and Target Group Index (TGI) data to provide refreshed profiles. This was conducted in three
stages:
• Replication using the latest Taking Part data
– of the 13 arts consumer segments identified
in the 2008 segmentation analysis
• Linking of the consumers segments
within TGI survey data from 2009/10
• Use of Taking Part and TGI data to profile
the 13 segments, providing information on
socio-demographic characteristics, lifestyle
habits, media profiles, digital behaviour,
and attitudes
* www.artscouncil.org.uk/arts-audiences-insight-2008
02 Arts audiences: insight
3. Why segmentation research is important for the arts
Segmentation is relevant to the arts because:
• not all people are the same, or share the same
attitudes, opinions and motivations about the arts
• people’s differing attitudes, opinions and motivations
shape behaviour: it can show how and why people are
likely to engage with the arts
• from a marketing perspective, a person from
one segment can be responsive to one
approach, while the same approach can be wholly
inappropriate for a person from another segment
03 Arts audiences: insight
4. Why our research is important
Our approach to segmentation has three key features:
• it covers all English adults, not just a particular audience group – this
enables artists and arts organisations to understand their current audiences within the
context of wider patterns of arts engagement, and to think about potential
future audiences
• it starts with the arts – existing population-wide segmentation tools (e.g. ACORN
and Mosaic)* are based largely on the on the socio-demographic characteristics of
different groups, while this segmentation is based on patterns of arts engagement and
attitudes towards the arts. It therefore provides a tailored, more effective tool for arts
marketing in particular, allowing us to explore socio-demographic and other lifestyle
factors in the context of people’s artistic lives, not vice versa
• it looks across patterns of arts attendance and
participation – the events people go to see as well as the
activities they take part in at home or with friends
* Geodemographic classifications of consumer types developed by CACI (ACORN) and Experian (Mosaic).
04 Arts audiences: insight
5. How the segmentation research might be used
This segmentation provides insight into why and how different kinds of
people engage with the arts in England.
It can help any organisation working to increase arts engagement to
identify target segments and develop tailored engagement strategies
and marketing campaigns.
• it increases collective knowledge about how people
in England engage with the arts – putting individual projects into
context
• it develops potential new strategies for increasing
arts engagement and expanding audiences
• it informs marketing of existing arts opportunities
05 Arts audiences: insight
7. Re-cap of the original segmentation method
Group 1 Group 2 Group 3 Neither
Attend/ Participate attend nor
participate only participate
cluster analysis of Taking divided into 3 cluster analysis of Taking
Part data based on types subgroups based Part data based on
of events on age (16–29, background and barriers
attended, frequency of 30–59, 60+) towards attendance and
attendance, participation in participation – resulting in
arts activities, reasons for 4 clusters
engaging and desire to do
more – resulting in 6
clusters
The 10 clusters and 3 subgroups identified in this process are the 13 segments
07 Arts audiences: insight
8. Linking methodology in original segmentation
Data fusion
Creates a modelled match between similar
between Taking Part
respondents on each survey so that all
and TGI datasets
variables can be donated from one survey to
another
Variable Variable
Attendance at ballet TV viewing
Taking Part TGI
Age Social attitudes
respondent respondent
Fusion
Reason for attending Favourite brands
08 Arts audiences: insight
9. Linking methodology in update to profiles
After re-creating the 13 segments in Taking Part...
Discriminant analysis to
create a linking The algorithm predicts a single variable (i.e.
algorithm between TGI segment membership) using only TGI data
data and segments
Variable Segment
Urban arts
TV viewing eclectic
TGI Fun, fashion and
Social attitudes friends
respondent
Algorithm Time-poor
Favourite brands assigning TGI dreamers
respondent to a
segment
09 Arts audiences: insight
10. Key findings
The analysis identified 13 distinct arts consumer segments among English adults.
The percentages show the estimated proportion of English adults in each segment.
010 Arts audiences: insight