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Behavioral Effects of Digital Signage
Digital signs have become an important new channel for communicating with
consumers in retail shopping environments. An analysis of academic and commercial
experiments reveals that in-store advertising effectiveness depends on both the
content of the message (appeal type and product category) and the context and
quality of exposure (audience need state, traffic speed and direction, message
frequency and duration). Shoppers are most responsive to messages that relate to
the task at hand and their current need state, and least responsive to traditional
brand messages.
INTRODUCTION
As media channels and audiences continue to
fragment, interest grows in bringing advertising
messages into retail stores. Recent research sug-
gests that between 30 and 40 percent of category
and brand decisions are made in store (Ogilvy-
Action, 2008), and there are many opportunities
to improve communication at the point-of-purchase.
A national survey of over 5,000 grocery shoppers
in 2008 discovered that only about half of shop-
pers believed that store shelves provided suffi-
cient product information; 34 percent believed
that the benefits and value of products were clearly
communicated, and 23 percent believed that the
benefits of new products were highlighted (Burke
and Morgan, 2008).
Manufacturers and retailers have found that
in-store marketing can affect shopper behavior
powerfully, and this potential has fueled a rapid
growth in shopper-marketing spending. A 2008
study reported that nontrade marketing activities
at the point of purchase were more likely to de-
liver a meaningful return on investment than tele-
vision, radio, print, or outdoor advertising (GMA/
Deloitte, 2008). The study also noted that more
than 60 percent of retailers and manufacturers
planned to increase spending on nontrade in-store
programs in the following year. This growth rate
was second only to investments in interactive/
web marketing and came at the expense of such
traditional media as television, radio, and bill-
boards as well as out-of store couponing and
free-standing inserts.
Although there are a variety of options for
communicating with shoppers at the point of
purchase, this article focuses on digital signage.
Digital signs are large (greater than 30 inches
diagonally) flat panel monitors that show a con-
tinuous loop of advertising and editorial mate-
rial. The signs often are positioned throughout
the store and are controlled by a centralized com-
puter server. The signs are ideal for marketing
experiments because their content can be manip-
ulated in real time, and shopper behavior can be
measured using point-of-sale scanners and/or
video cameras.
There has been very little academic research on
this topic (Burke, 2006), but manufacturers and
retailers, in collaboration with marketing-research
firms and consultants, have conducted a number
of unpublished studies. This article attempts to
summarize the empirical generalizations gleaned
from this research. (The author gratefully acknowl-
edges the support of dunnhumby, Video Mining,
and DS-IQ for contributing research findings to
this article.)
RAYMOND R. BURKE
Kelley School of
Business
Indiana University
rayburke@indiana.edu
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DOI: 10.2501/S0021849909090254 June 2009
JOURNAL OF ADVERTISING RESEARCH
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EMPIRICAL GENERALIZATIONS
Message characteristics
EG1: Shoppers are most responsive
to “news” (new items, promo-
tions, seasonal information) and
least responsive to traditional
brand messages.
Product characteristics
EG2: Shoppers are most responsive
to messages for hedonic (food
and entertainment) products.
EG3: Featured products with higher
category penetration have higher
absolute sales uplift, but lower
relative (percentage) uplift.
SUPPORTING RESEARCH
From January 2005 through June 2007,
Tesco plc, a British-based international gro-
cery and general merchandising retail
chain, tested 102 different advertising cam-
paigns on a 100-store “Tesco Screens” net-
work. Each store in the network had 40⫹
digital signs (plasma and LCD screens)
positioned in several zones throughout
the store (e.g., health and beauty care;
entertainment products; beer, wine, and
spirits). Customers viewed content di-
rectly related to the products in each zone.
The content included a mix of editorial
material (e.g., news and sports), advertise-
ments, promotional offers, and customer
information. In August 2006, dunnhumby,
a retail consulting firm, assumed respon-
sibility for Tesco Screens and conducted
research to determine the factors that drive
sales uplift and consumer awareness.
Each advertising campaign was coded
on several dimensions, including the de-
partment and category of the promoted
product, campaign length (typically two
to four weeks), message type, product
characteristics (private label or national
brand, price, frequency of purchase, ex-
pandable consumption), above-the-line ad-
vertising support, and other promotional
support (price offer, feature advertising).
The sales uplift of each campaign was
measured by comparing sales of the pro-
moted product in test (screen) and control
(nonscreen) stores during and immedi-
ately after the campaign. Sales were cap-
tured using Tesco’s Clubcard and electronic
POS data.
The database included a variety of dif-
ferent product and campaign types. Fifty
percent of the campaigns were for Tesco
branded products, 57 percent had a sea-
sonal tie-in, 57 percent were in expand-
able consumption categories, and 29
percent were for new products. In terms
of promotion, 57 percent of the cam-
paigns were for brands with a price offer,
36 percent had some level of feature ad-
vertising, and 36 percent had above-the-
line advertising support.
A comparison of the various message
types revealed that seasonal, promo-
tional, and new-product messages pro-
duced a higher percentage lift in short- to
mid-term sales than traditional brand mes-
sages (see Table 1). These in-store adver-
tising effects were in addition to any other
advertising or price effects observed across
the test and control stores. It appeared
that shoppers were most interested in mes-
sages that addressed the task at hand
(“What do I need?” “What’s on sale?”
“What’s new?”) and less responsive to
the typical brand-building messages shown
on conventional television.
A 2000 test of digital signage conducted
by Indiana University and Eddie Bauer
produced a similar result (Burke, 2006).
The study installed four digital signs in
the windows of a specialty apparel store
and tested two advertising campaigns over
a two-month period. The first month fea-
tured a new line of leather jackets that
were unique to Eddie Bauer. The second
month promoted wardrobe staples: denim
jeans at everyday prices. When new prod-
ucts were featured on the digital displays,
store traffic jumped 23 percent and sales
increased 10 percent relative to three
EMPIRICAL GENERALIZATIONS
In-store digital signage featuring “newsworthy” information (e.g., new items, seasonal
offers, promotions) has a markedly favorable impact on sales. This effect is stronger for
hedonic (food and entertainment) products.
TABLE 1
Advertising Campaign Effects as a Function of Message Type
Message Type Average £ Uplift Average % Uplift SCR
a
.............................................................................................................................................................
Tesco seasonal
b
(5) £44,040 9.6% 5.7
.............................................................................................................................................................
Tesco promo (12) £11,106 6.1% 2.2
.............................................................................................................................................................
Tesco new (6) £7,543 11.5% 1.5
.............................................................................................................................................................
Brand (24) £8,580 4.7% 1.2
.............................................................................................................................................................
a
SCR ⫽incremental retail sales in activity stores divided by campaign media cost.
b
Tesco seasonal includes Christmas, Easter, and Mother’s Day.
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matched control stores with conventional
paper signs. When wardrobe staples were
featured, however, there were no signifi-
cant differences in the traffic or sales of
the test and control stores.
The Tesco analysis also revealed signif-
icant effects of the product category on
sales lift (see Table 2). Snacks (candy, gum),
beverages (soft drinks, beer, wine, and
spirits), and entertainment items (DVDs)
had significantly higher lift than nonfood
items (dishwashing detergent, soap, ra-
zors, shampoo). Neo Media POSTV, a
Dutch company, recently reported a sim-
ilar result. In studies conducted using the
firm’s “Supermarket TV” digital signage
network, the research found an average
sales lift of 14 percent across all advertise-
ments, but a 25 percent lift for advertise-
ments for sweets and snacks. In-store
advertising for hedonic products seemed
to appeal to shoppers’ latent needs and
desires, stimulating discretionary pur-
chases, while shoppers tended to be less
responsive to advertisements for planned
purchase items.
Product category penetration also played
a role in consumer response to Tesco’s
in-store digital advertising. Promotional
messages for existing products with high
category penetration had a higher abso-
lute lift in sales; messages for new prod-
ucts (low category penetration) had a higher
relative (percentage) uplift and attracted
more customers. (Seasonal campaigns per-
formed well on both dimensions.) A sepa-
rate regression analysis revealed that a
1 percent increase in category penetration
produced a ⫹£140 increase in sales rev-
enues, but a 0.10 percent decrease in the
percentage sales lift.
MODERATING CONDITIONS
Need state of the shopper
MC1: Message receptiveness varies by
time of day and day of the week.
Quality and frequency of exposure
MC2: Shopper response is a function
of sign location, orientation, and
visibility.
MC3: Shorter messages deliver higher
lift per unit of screen time.
Scope of measurement
MC4: Advertising effects extend be-
yond the featured product, driv-
ing sales of the family of brands,
and the entire product category.
SUPPORTING RESEARCH
The results of various field experiments
suggest that the effectiveness of in-store
digital advertising may depend on sev-
eral factors, including the need state of
the shopper (MC1), the quality of mes-
sage exposure (MC2 and MC3), and the
scope of response measurement (MC4).
The supporting research for each of the
identified moderating variables is limited,
so these propositions should be treated as
hypotheses in need of further testing rather
than definitive conclusions.
The first study, conducted by Video-
Mining Corp., tested the effectiveness
of digital signs in attracting consumer at-
tention to a kiosk that displayed paint
products and color samples in the main
corridor of a shopping mall. The study
used an automated video-tracking sys-
tem to record the number of shoppers
who walked past the kiosk and paused
to examine the video display screens and
products. Over the three-month test pe-
riod, the study tracked approximately
100,000 shoppers. During weekdays, the
highest levels of customer traffic oc-
curred in the afternoons (46.4 percent),
with lower counts in the morning (20.2
percent) and evening (33.3 percent). The
percentage of “engaged shoppers” (peo-
ple who stopped to look at the signs and
products), however, steadily increased
over the day—from 9.6 percent (morning)
to 12 percent (afternoon) to 14.6 percent
(evening). Weekends scored particularly
high on engagement, sometimes by a fac-
tor of 10.
These differences appeared to be due to
variations in shoppers’ goals by time of
day and day of the week. A survey of 365
mall shoppers revealed that consumers
are more task oriented when shopping
earlier on weekdays and become increas-
ingly interested in browsing and socializ-
ing with friends in the evening and on
weekends (Burke, 2006). (For example, the
TABLE 2
Advertising Campaign Effects as a Function of Product
Category
Category Average £ Uplift Average % Uplift
.............................................................................................................................................................
Beer, wine, and spirits (3) £46,850 12.9%
.............................................................................................................................................................
Entertainment (6) £25,256 9.2%
.............................................................................................................................................................
Impulse (11) £18,267 10.0%
.............................................................................................................................................................
Grocery (4) £13,280 7.1%
.............................................................................................................................................................
Household (3) £5,017 3.2%
.............................................................................................................................................................
Health, baby, and beauty (10) £2,813 0.7%
.............................................................................................................................................................
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BEHAVIORAL EFFECTS OF DIGITAL SIGNAGE
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JOURNAL OF ADVERTISING RESEARCH
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percent of self-reported browsers jumped
from 31 percent in the morning and early
afternoon to 52 percent in the evening.)
Additional research is needed to deter-
mine if these differences in browsing and
shopper engagement translate into higher
sales response to in-store advertising
messages.
A second study by VideoMining mea-
sured the effectiveness of a mall-based
digital signage network. The test was con-
ducted over a three-month period in five
designated market areas. Each mall kiosk
had two large flat panel displays on ei-
ther side that ran a loop of video material
to attract passers-by. Below the large dis-
plays were small interactive touch screens.
Once again, a computerized video track-
ing system was used to record shopper
traffic and engagement.
Approximately two million shoppers
were tracked during the measurement pe-
riod. Of the average daily traffic of 4,281
shoppers, 17.1 percent paused to look at
the displays, 5.3 percent spent more than
5 seconds examining the kiosk, and 0.42 per-
cent stopped for 1 min or more to interact
with the kiosk. While the overall levels of
attention were low, the degree of engage-
ment varied depending on the shopper’s
angle of approach and proximity to the dis-
play screens. Customers who were travel-
ing in the lanes farthest from the kiosk
(zones 1 and 2) were more likely to stop
and notice the signs, even though zones 3
and 4 had roughly the same passer-by traf-
fic, and these shoppers were physically
closer to the displays (six feet or less; see
Figure 1). It appears that shoppers in zones
1 and 2 had a better line of sight and could
view the signs for a longer period of time,
increasing engagement. In general, one
would expect that shopper response to dig-
ital signs would be a function of the qual-
ity and duration of exposure.
Two additional moderating variables
(MC3 and MC4) were identified in a study
conducted by DS-IQ, a technology com-
pany that provides shopper-response mea-
surement and campaign optimization for
in-store media networks. An advertising
campaign was run on digital signs for an
eight-week period and featured three dif-
ferent treatments: (a) a 30-s taste message,
(b) a 30-s product line message, and (c)
two 15-s advertisements [short versions
of (a) and (b)]. The play schedule was
designed so that each store acted, in part,
as its own control, and each loop had the
same amount of campaign play time: one
30-s play per loop, or two 15-s plays per
loop, with those 15-s spots separated by
other advertising content. Sales lift results
for each content treatment were normal-
ized against the amount of play time and
reflect additional sales generated solely
due to the digital media campaign run
in-store.
For this campaign, both 30-s spots drove
additional sales above control periods
(when the content did not play) by 8 to 9
percent. But running two 15-s treatments
in the same loop—doubling the opportu-
nity to see—increased sales lift by more
than 50 percent, as compared to a single
30-s spot (see Figure 2). There were also
significant halo effects, where the cam-
paign lifted sales beyond the scope of the
featured product. In this case, the family
of brands experienced a volume uplift
nearly seven times that of the featured
product; overall category lift was greater
than 11 times that of the featured product
(see Figure 3). It appears that in-store
product advertising can stimulate the con-
sideration and purchase of the entire prod-
uct category.
MANAGERIAL IMPLICATIONS
The research revealed that in-store adver-
tising effectiveness depends on both the
content of the message (appeal type and
product category), and the context and
quality of exposure (audience need state,
traffic speed and direction, message fre-
quency and duration). Shoppers were
most responsive to messages that relate
Figure 1 Shopper Traffic and Engagement as a Function of
Relative Sign Position
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JOURNAL OF ADVERTISING RESEARCH
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to the task at hand, and the right mes-
sage can drive incremental sales of 5 to
25 percent. The findings suggested that
digital signage is not like at-home tele-
vision advertising. Instead, it is more
like conventional point-of-purchase dis-
plays, where a simple, direct, and rele-
vant message produces the greatest
response. Dunnhumby’s Joel Hop-wood
noted, “You can forget about the idea
that the audience is going to put any-
thing like the cognitive effort they put
into a 30-second TV spot when they’re
in-store” (Page, 2007).
An advantage of in-store advertising
for developing empirical generalizations
is the temporal and physical proximity of
choice: it is possible to manipulate the
presentation and content of advertising
messages and measure the direct effect on
shopper attention and sales. Note that
this tends to favor short-term communi-
cation goals, such as stimulating product
trial and incremental sales. It is also im-
portant to track shopper perceptions and
behavior over the longer term to capture
the effects of these in-store campaigns on
brand equity, customer satisfaction, and
loyalty.
The dynamics of in-store advertising
suggest that it would be beneficial to
continuously monitor the effectiveness of
messages and adjust the schedule of
programming accordingly. Different ad-
vertisements tend to “wear in” and “wear
out” (increase or decrease their effective-
ness) over different periods of time. There
is no guarantee that the four-week adver-
tising flights that are typically used on
retail networks would be ideal for all
advertisements. For example, DS-IQ re-
ported that an advertising campaign
for a confection product saw a steady
increase in unit sales lift through the
fifth week of the campaign, but that a
juice campaign reached its maximum
potential during the third week of
advertising.
There are several other potentially im-
portant variables that may moderate
consumer response to in-store advertis-
ing. When shoppers are exposed to
digital signs, they usually are involved
in another primary activity (navigating,
searching, choosing, checking out), and
Figure 2 The Effects of Advertising Content and
Duration/Frequency on Sales Lift
Figure 3 Halo Effects of Featured Product Advertising
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the type of task may affect their message
receptiveness. For example, shoppers wait-
ing for an order to be filled at the deli
may be more attentive to new-product
or usage information than people navi-
gating through the aisles. Other variables
that may affect response include the lev-
els of physical and visual clutter in retail
stores, display interactivity (e.g., using
touch-screens or mobile devices), user-
generated content (e.g., from surveys), and
dynamic personalization (e.g., using video
recognition of shopper demographics to
target messages). These present a num-
ber of promising opportunities for future
research.
................................................................................................
R
AYMOND
R. B
URKE
is the E. W. Kelley Professor of
Business Administration at Indiana University’s Kelley
School of Business and founding director of the
School’s Customer Interface Laboratory, a state-of-the-
art facility for investigating how customers interact
with new retailing technologies and the in-store envi-
ronment. His research focuses on understanding the
influence of point-of-purchase factors on consumer
shopping behavior. Dr. Burke has also served on the
faculties of the Harvard Business School and the
University of Pennsylvania’s Wharton School. His ar ti-
cles have appeared in several major journals, includ-
ing the Harvard Business Review, the Journal of
Consumer Research, the Journal of Marketing, and
Marketing Science.
REFERENCES
Burke, Raymond R. “The Third Wave of Mar-
keting Intelligence.” In Retailing in the 21st Cen-
tury: Current and Future Trends, Manfred Krafft
and Murali Mantrala, eds. Berlin: Springer, 2006.
–——, and Neil A. Morgan. “The Shoppabil-
ity Report: Benchmarking Retail Store and Cat-
egory Performance.” Paper presented at the
In-Store Marketing Summit, Chicago, IL, April
18, 2008.
GMA/Deloitte. “Delivering the Promise of
Shopper Marketing: Mastering Execution for
Competitive Advantage.” Report sponsored by
the Grocery Manufacturers Association (GMA)
and Deloitte Consulting LLP, 2008.
OgilvyAction. “Shopper Decisions Made In-
Store.” White paper. New York, 2008.
Page, Barnaby. “Dunnhumby Renames Tesco
TV, Rethinks Approach to Content.” Aka.tv,
July 29, 2007.
Shoppers were most responsive to messages that
relate to the task at hand, and the right message can
drive incremental sales of 5 to 25 percent.
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