Previous research into the effects of sound on shoppers has focused exclusively on music, usually isolating one variable at a time. This study sets out to explore the effects on shoppers’ valence, cognition and stress of alternative soundscapes, and finds that the music typically chosen in retail settings is probably not the best choice of background sound. When a generative soundscape, café noise and a music playlist are compared, music performs least well of the tested sounds. Three important new avenues for future research into retail soundscapes are opened up as a result.

1. MUSIC IS NOT A VENEER: THE EFFECTS OF MUSIC
VERSUS NON-MUSIC SOUNDSCAPES IN RETAIL
Abstract
Previous research into the effects of sound on shoppers has focused exclusively on
music, usually isolating one variable at a time. This study sets out to explore the
effects on shoppers’ valence, cognition and stress of alternative soundscapes, and
finds that the music typically chosen in retail settings is probably not the best choice
of background sound. When a generative soundscape, café noise and a music playlist
are compared, music performs least well of the tested sounds. Three important new
avenues for future research into retail soundscapes are opened up as a result.
Keywords
Retail, music, sound, noise, shopping, audio branding, soundscapes, generative sound,
background music, background sound, pop music, Muzak, valence, cognition, stress

2. Introduction
The modern retail environment
The shopping centre is a ubiquitous hub in modern life, replacing former social
nexuses such as traditional street markets and high streets with its increasingly
multifaceted offering of shopping, leisure and dining in a climate controlled, easy to
access environment. Inside this sealed space, shoppers are bombarded by sound from
many different sources, all of it bouncing around in typically poor acoustics featuring
long reverberation times. This auditory environment (we will refer to it as ‘mall
mush’) may include background music, often clashing with music emanating from
individual stores; voice announcements (VAs); hums, buzzes, squeaks and bangs
from mechanical and engineering (M&E) equipment; sound from cooking and
catering equipment and the noise of cutlery and crockery; as well as aggregated
conversation and movement noise from all the shoppers. Much of this sound is
acousmatic in nature – separated from any identifiable visual source (Hellström,
Sjösten, Hultqvist, & Dyrssen, 2011). This sets up an effect that has become known as
schizophonia (Schafer, 1977) where our aural experience is not directly related to our
visual experience: the two senses become in some way dislocated.
Sound and shopping
Most spaces contain complex soundscapes that change over time. In a shopping centre
the soundscape is typically created by four factors: the acoustics of the space; the
combined noise sources in play at any given moment; the quality and quantity of the
sound system, which was often designed only for life safety; and finally any content
that is played through the sound system – usually some form of lively pop music,
sometimes with additional VAs. These four factors combine to create the mall mush
described above: a largely undifferentiated wash of noise, typically at an average
sound pressure level of 60-70 decibels.
Architects rarely consider the auditory experience of the spaces they design. This is
not surprising as they are trained to be almost entirely ocular: in the five years of a
typical degree, they can spend as little as one day studying sound1
. Nevertheless, the
sound of each space has profound effects on the people occupying it. Treasure (2011)
distinguishes four classes of effect: physiological (hormone secretions, heart rate,
breathing etc); psychological (emotions and moods); cognitive (ability to process
information); and behavioural (usually movement away from undesired sound). He
emphasises that most of these effects typically occur at a non-conscious level, because
most people in urban environments are habituated to suppressing their consciousness
of the noise around them. Despite this it is clear that ‘our inherent ability to hear space
is integral to our relationship to our environment, our perceptions of its physical
nature and how it makes us feel’ (Blesser & Slater, 2007). In addition, ‘research has
found significant relationships between emotional states and time spent in stores,
propensity to make a purchase, and satisfaction with shopping times’ (Yalch &
Spangenberg, 2000). Sound affects emotions, and these affect shopping behaviour.
The goal of shopping centres is to influence people to buy, so it would seem logical
that each of the these carefully designed spaces should create an atmosphere which is
1
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3. congruent with the brand or values of the particular mall, and which encourages
people to stay longer. This last factor, known as ‘dwell time’ to the retail community,
is usually directly correlated with increased sales (the longer we stay in a retail space,
the more we spend) – and intuitively also serves as a proxy measure of customer
satisfaction, since if people stay longer in a space, we can also reasonably deduce that
they are enjoying themselves more. However, there is no tradition of intentional
soundscape design in shopping centres. Most combine poor acoustics, plentiful M&E
noise, low quality sound systems and generic, fast-paced, vocal pop music (often
clashing with individual retailers’ own sound systems) to create a soundscape that is
more likely to debilitate and fatigue than nourish and delight.
The tendency of retailers to overstimulate shoppers and thus actually reduce dwell
time – exactly the opposite of their desired result – is now becoming documented,
especially around Christmas. It is becoming clear that too much seasonal stimulus
creates fatigue and stress, while ‘moderation in festive decor leads consumers to
spend more and to like the retailer more’ (Puccinelli, 2011).
Music and shopping
Music is one very common way in which retailers overstimulate shoppers.
Research into the effects of music on people began in the 1940s with the efforts of the
Muzak Corporation, founded in 1934, which used tempo-profiled musical playlists to
affect arousal and improve productivity in factory workers. Muzak called this process
Stimulus Progression and patented it (Trex, 2011). Today, background, or piped,
music has become commonplace, even ubiquitous, in public spaces such as bars,
hotels, restaurants, shops and malls.
Most retailers now appear to hold the view that music is the best auditory shopping
environment, regardless of the nature of the space, the demographics and
psychographics of the shoppers, the quality of the sound system or the background
noise into which the music is being delivered. So pervasive is this view that music has
been described as ‘the key ambient condition of the servicescape.’ (Bitner, 1992).
The effect of music on people’s behaviour in shopping centre environments is
relatively well researched. It is clear that there is an effect: ‘different background
music and structural components… (sound level, tempo, tonality) affect consumer’s
behaviour’ (JC, Vaillant, & Gelinas-Chebat, 2001).
However, music is a complex sound, usually played into a complex existing
soundscape, so there are many variables in play. Tempo, volume, familiarity with the
content, liking of the content and genre all have their own effects, so most studies
have focused on isolating one of these variables and tracking its specific effect. These
effects appear to operate through a variety of mechanisms, some of which
undoubtedly affect one another: arousal, stress levels, entrainment, association,
distraction, time perception and subjective valence (pleasantness) have all been
researched, matching them against different variables in musical content, such as
tempo, volume, familiarity, liking and genre.
Many of these mechanisms are two-edged swords: often, the outcome of adjusting the
variable in question seems to depend on the situation and the intensity of the input.
For example, Kellaris suggests that ‘playing the right music has a lot of commercially

4. beneficial effects… it tends to pull the customers’ attention, distracting them in a way
that lowers their sales resistance’ (Niehaus, 2013) – while Pucinelli’s research
suggests that too much external stimulus creates stress and reduces sales, and other
research has shown that the use of music considered too loud by customers results in
reduced dwell time (Milliman, 1982).
Another example of contradictory hypotheses appears in the area of arousal. The
seminal work by Berlyne (1960) suggested that people prefer to be mildly aroused by
‘collative’ stimuli (those involving comparison with expectation or past experience)
as distinct from psychophysical (for example volume of music) or ecological (relating
to past experiences of reward or punishment). This theory seems to be the main driver
in the music piping industry where the prevailing mode is to play up-tempo,
stimulating music. However, other research has shown that slowing people down can
create higher sales: when slower tempo background music was played in a
supermarket, sales increased by 38% (Milliman, 1982), while, ‘low tempo music
increased money spent on food and drink at a restaurant’ (Milliman, 1986).
To make the picture even more complex, the reported effects of music may also be
dependent on individual variables such as age, gender and personality type: for
example, ‘people who tend to make unplanned purchases spend even more freely
when shopping in the presence of background music… [while] contemplative
shoppers buy slightly less than usual when music is playing’ (Dingfelder, 2005).
The standard practice of playing chart hits or favourite oldies may be
counterproductive for other reasons than tempo: when listening to familiar music,
shoppers were found to shop less, yet perceive themselves as shopping longer (Yalch
& Spangenberg, 2000). And piped music in general has many detractors: a 1998 NOP
survey carried out for the Royal National Institute for Deaf People (now Action on
Hearing Loss) found that 38% of the general public find piped music annoying, rising
to 45% of 45-54 year olds (NOP 1998). Yet it does seem clear that relevant situational
music can affect product choice, especially when the shopper is undecided. For
example, the choice between French and German wine was dramatically affected by
the playing of French or German music at the point of sale (North, A.C., Hargreaves,
D. J., McKendrick, J.,1997).
By isolating and considering just one variable at a time, the current body of research
on music ignores the key issue that ‘music on top of noise is just more noise’
(Treasure, 2013), which may be the reason for the negative views found by NOP in
the survey quoted above. So far, there has been little discussion of the effect of music
in situ (for example against a background of mall mush) – or of the effects of sound
other than recorded music. Experiments in other fields into the behavioural effects of
non-music sound indicate that positive outcomes are possible: for example, a
soundscape of birdsong and other natural sounds made school pupils more alert and
better able to concentrate after their lunch break (Winterman, 2013). Birdsong has
also been used in a quiet lounge in Schiphol Airport where ‘people can relax before
their flight… the airport was voted the third best in the world at the World Airport
Awards and last year 95% of passengers rated it as good or excellent’ (Winterman,
2013). And the use of natural sounds during surgery has been shown to increase the
acceptability of the experience of anaesthesia (Tsuchiya, et al., 2003).
Generative soundscapes

5. Generative sound is not recorded. It is played live by a computer program based on
probabilistic algorithms, so that patterns rarely repeat. Generative music has been
around since the 1990s, when it was championed by Brian Eno, working with Tim
and Pete Cole’s Koan program (Eno, 1996). More recently, The Sound Agency has
developed an industrial strength generative sound system called the Ambifier™ (The
Sound Agency, 2014) to deliver custom-designed, generative soundscapes into retail
and other commercial settings. These soundscapes are designed not to be listened to,
but to act as aural wallpaper, creating a pleasing ambience without calling for
attention or being associated with a particular artist, genre or event in a shopper’s past.
In the main in retail settings, these soundscapes are designed to reduce stress and slow
people down, increasing dwell time and reducing fatigue as a result. To the best of our
knowledge, no research has ever tested the effects of a designed generative
soundscape compared to music.
Hypothesis
Based on the above, our aim was to test the potential of a designed generative
soundscape for facilitating desirable states in shoppers, comparing this new type of
sound to music and one other familiar sonic environment – that of a café. Using an
enhanced circumplex model of affect (Russell, 1980) with three dimensions instead of
the usual two, the three dimensions being arousal (stressed to relaxed), valence
(negative to positive) and cognition (confused to clear) we suggest that an ideal
shopping state would be relaxed, positive and clear, and we hypothesise that the
designed generative soundscape will be more effective in facilitating this state than
either pop music or the café soundscape.
Method
Design
The experiment used related samples with one independent and three dependent
variables. The independent variable had five forms: baseline; pop music; café sound;
generative soundscape; and auralisation suite. The dependent variables were self-
reported ratings for stressed/relaxed, confused/clear and positive/negative on a seven-
point scale.
Participants
There were 100 participants, with 50 men and 50 women. The participants’ ages
ranged from 20 to 74 with a mean age of 42.38 (SD = 14.13). All the participants
were staff, students or visitors of Edinburgh Napier University. Participants were a
convenience sample recruited personally by the second author. We have no reason to
believe the sample differs from any typical shopping centre’s customer base, either in
age or demographic.
Apparatus and Materials
A MacBook Pro laptop computer was used to play pre-recorded stereo audio files
through a pair of Genelec 8030A loudspeakers in an auralisation suite (a specially
designed listening room). Three 16 bit, 44.1 kHz stereo wav files, each just over five

6. minutes in duration, were supplied by the first author. They comprised: one music
mix designed to be typical of the kind of pop used in malls; one recording of café
sound; and one sample from a generative soundscape specifically designed by The
Sound Agency for use in a shopping mall.
The music file was a mix of the following tracks: Gangnam Style (PSY); Facemelt
(Rita Ora); R.I.P. (Rita Ora); Hot Right Now (Rita Ora); You da One (Rihanna); DNA
(Little Mix); Wings (Little Mix).
A set of printed instructions asked each participant “to rate how you feel using the
scales listed below”.
Procedure
Participants took part in the experiment individually, and were not provided with any
form of inducement. They sat in an auralisation suite facing the loudspeakers. The
researcher sat next to the participants on the floor. After providing informed consent,
participants read the instructions in their own time from a printed sheet of paper. The
instructions informed the participants that they would be asked to listen to three five-
minute audio recordings. The instructions also specified that at “five different points
in the experiment you will be asked to rate how you feel using the scales listed below.”
The experimental session began once the participant understood what they had to do,
and all of their questions had been answered. In order to identify a baseline, as well as
to ensure that participants clearly understood the scales, the participants were asked to
rate how they felt at present. Each audio file was then played for four minutes at
approximately 65 dBA to match the noise level in a typical retail environment, and
participants were asked to rate their feelings while they were still listening to the
relevant audio file. A randomised sequence was used to reduce the order effect for
both the questions and the audio file sequence. In order to monitor the effect that the
procedure might have on responses, participants were asked to remain in the
auralisation suite for a further four minutes before providing a fifth and final rating.
Participants were then asked if they had any questions about the study, and all
questions were answered.
Results
In terms of reliability Chronbach’s Alpha was calculated for all 100 participants’
responses at 0.824, which is a figure considered to show very good reliability in
psychometric testing (Kraemer, 2013). When comparing the baseline ratings with the
auralisation suite there was only an average difference -0.07 on a 7-point scale. It
could be argued that the experimental procedure had minimal impact upon the results.
With regards to the ratings for the three scales (stressed/relaxed, confused/clear,
negative/positive) there was an identifiable difference (see Figure 1). The mean
values for the generative audio file were all above 5, whereas the café values were all
above 4 and the music were all above 3. This meant that when comparing the
generative sound file to the baseline the participants were more relaxed by 0.89, with
almost no difference to confused/clear (0.01) and negative/positive (0.08). In contrast
the music sound file elicited a response of less relaxed (-1.53), less clear (-1.5) and
less positive (-1.39). There was a similar response to the café sound file, less relaxed
(-1.09), less clear (-1.06) and less positive (-1.37).

7. Figure 1: Mean values
In terms of gender there was only minimal variation in the mean values, with an
average variation of only 0.02 on a 7-point scale. However, age did have a greater
impact upon the responses. The 20-24 age group reported an average difference of 3
on the stressed/relaxed scale between the generative recording and the café, whereas
the 65-74 group only reported a difference of 1.6 (see Figure 2). In a similar manner
the 20-24 group reported a 0.21 increase between the music and the café, in contrast
the 55-64 group described an average decrease of -0.95. There was less of a
difference when it came to comparing the generative recording to the music recording,
the greatest difference was again the 20-24 group with 2.79, and the smallest
difference was 2.2 for both the 45-54 and 65-74 groups.
Figure 2: Stressed/relaxed mean responses according to age.
0.00#
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confused/clear#
nega8ve/posi8ve#
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8. There was less overall variation when rating confused/clear (see Figure 3). The 20-24
group reported a difference of 2.21 between the generative file and the café file, in
contrast the 35-44 only reported a minimal difference of 0.22. The 20-24 group
recorded an only minimal difference between music and the café at 0.21, although the
55-64 group recorded -0.95. When comparing the generative to the music the 45-54
reported the highest difference at 1.85, and the 65-74 group reported the lowest at 0.8.
Figure 3: Confused/clear mean responses according to age.
There was even less variation with the negative/positive scale. The 25-34 group
reported a difference of 1.95 when the responses for the generative and café are
compared, in contrast the difference was only 1 for the 45-54 group. For the
music/café comparison the 20-24 year olds indicated a difference of 0.71, whereas the
55-64 year olds described a difference of -0.52. The 65-74 group reported the highest
difference between the generative and the music at 2.2, with the 45-54 reporting the
lowest at 1.2.
0.00#
1.00#
2.00#
3.00#
4.00#
5.00#
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20+24#
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45+54#
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Café#
Music#
Genera9ve#

9. Figure 4: Negative/positive mean responses according to age.
In general terms the generative audio file is always to the outer edge of figures 2 – 4,
which shows that higher values were reported than the music and café. Whilst this
does not show that the generative audio file had the effect of making the participants
more relaxed, more clear and more positive, it does show that when listening to the
music and café recordings the participants reported that they were less relaxed, less
clear and less positive.
Discussion
These results suggest that fast-paced pop music is not in fact the best choice in a
typical retail environment. Both the music and the café soundscape led to participants
reporting increased stress, reduced cognitive clarity and (presumably as a result)
reduced satisfaction, giving weight to the hypothesis that excess cognitive load
creates shopper stress and fatigue, and shortens dwell time (Puccinelli, 2011). All but
the youngest respondents rated music as more damaging to their cognition than café
noise. Almost all of the world’s national populations are ageing (UN, 2001), which
means that the scale of these negative effects is only likely to increase over time as
people get older, and as more shopping malls are built and play piped music – unless
those malls start to design their sound with more care.
The lively music tracks used for this study were chosen to be representative of what
The Sound Agency have found playing in many of the malls in which they have
carried out sound audits (numbering at least 20 over the past five years). It may of
course be that different, more restful genres of music (for example gentle classical
music, world music or new age music) would produce different ratings in a future
similar test.
Based on these findings, we can theorise as to the process in the real world. Music is
dense sound in cognitive terms: in general it is created with the intention of being
listened to, and it actively calls for our attention with its complex mix of tempo,
0.00#
1.00#
2.00#
3.00#
4.00#
5.00#
6.00#
7.00#
20+24#
25+34#
35+44#
45+54#
55+64#
65+74#
Café#
Music#
Genera9ve#

10. rhythm, melody, harmony, timbres, voice(s) and lyrics. When music is played as a
background sound in a context of a complex existing soundscape like mall mush, we
suggest that the result will be a conflict of interest: the music calls for attention,
demanding cognitive bandwidth in an already cognitively demanding acousmatic
environment, while the shopper is trying to concentrate on other things and thus feels
a sense of overload.
We believe that this paper opens up three important new avenues for further research
in the area of retail sound. First, our approach was not to extract and track the effects
of one isolated aspect of music, but to assess the effects of a range of alternative
soundscapes. We believe this methodology opens up a vital, yet hitherto largely
ignored, avenue for research into the effects of entire, complex, multifaceted auditory
retail environments on the people inside them. This is not to invalidate or devalue the
important research on isolated variables and their effects, but to suggest that both
forms of research are required in order to gain a holistic and complete picture of the
outcomes. The authors are now planning further research that specifically emulates
various complete auditory shopping environments, and compares the effects of each
on shoppers. Background music is never experienced in isolation, and the authors
suspect that context may prove to be at least as important as content in understanding
how various sounds in public spaces create psychophysiological effects on the
occupants of those spaces.
The second avenue is research into the effects of non-music sounds. In our study the
generative soundscape was demonstrably more successful than the music in terms of
facilitating the suggested ideal shopping state (relaxed, clear and positive). By
exclusively exploring the effects of music, previous research has ignored the potential
benefits of all the other classes and types of sound. If we are not to live and shop in a
world where every public space subscribes to the (probably mistaken) assumption that
pop music is the best background sound, then further research into the potential
benefits of other sounds is urgently required. These sounds may be natural, for
example stochastic sounds such as birdsong, rainfall, running water or wind, or they
may be artificial and designed by sonic artists or sound designers. The range is vast,
and so is the scope for research, which can build on the small but growing body of
work exploring the effects of natural sound in general, for example the recent finding
that bird sounds aid perceived attention restoration and stress recovery (Ratcliffe,
Gaterslebel and Sowden 2013).
Finally, it will also be interesting to assess the value of generative as opposed to
recorded sound, especially by exploring the effects of repetition. When recorded and
played repeatedly, even natural sound can become tiresome as recognisable patterns
become irritants, while the diminishing returns of repeating music tracks over and
over again are familiar to all. Exploring these processes in retail environments will
require another form of research into the effects of sound on shoppers, comprising
studies that take place over lengthy timescales during which participants experience
repeated exposure to various retail soundscapes, just as shoppers (and even more so,
retail workers) do in the real world.

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