Description
Communication and promotion decisions are a fundamental part of retailer customer experience management strategy. In this review paper, we address two key questions from a retailer's perspective: (1) what have we learned from prior research about promotion, advertising, and other forms of communication and (2) what major issues should future research in this area address..
Journal of Retailing 85 (1, 2009) 42–55
Communication and Promotion Decisions in Retailing:
A Review and Directions for Future Research
Kusum L. Ailawadi
a,?
, J.P. Beauchamp
b
, Naveen Donthu
c
,
Dinesh K. Gauri
d
, Venkatesh Shankar
e
a
Tuck School of Business at Dartmouth, 100 Tuck Hall, Dartmouth College, Hanover, NH 03755, United States
b
Information Resources Inc., United States
c
Georgia State University, Atlanta, GA, United States
d
Syracuse University, Syracuse, NY, United States
e
Mays Business School, Texas A&M University, College Station, TX, United States
Abstract
Communication and promotion decisions are a fundamental part of retailer customer experience management strategy. In this review paper,
we address two key questions from a retailer’s perspective: (1) what have we learned from prior research about promotion, advertising, and other
forms of communication and (2) what major issues should future research in this area address. In addressing these questions, we propose and
follow a framework that captures the interrelationships among manufacturer and retailer communication and promotion decisions and retailer
performance. We examine these questions under four major topics: determination and allocation of promotion budget, trade promotions, consumer
promotions and communication and promotion through the new media. Our review offers several useful insights and identi?es many fruitful topics
and questions for future research.
© 2008 New York University. Published by Elsevier Inc. All rights reserved.
Keywords: Communication; Promotion; Advertising; New media: Resource allocation; Trade promotion; Consumer promotion; Accounting; Legal issues
Introduction
Communication and promotion decisions are a critical ele-
ment of retailer customer experience management strategy.
There is an extensive literature on marketing communication
and promotion, consisting of both analytical and empirical mod-
els. Several useful reviews summarize what we know about this
very broad and important area, primarily from a manufacturer’s
standpoint (e.g., Neslin 2006; Stewart and Kamins 2002). Our
objective in this article is to examine one slice of this large body
of research as it relates to retailers. We address the following
questions froma retailer’s perspective: (1) what have we learned
from the past decade of research about promotion, advertising,
and other forms of communication and (2) what major issues
should future research in this area address? Given the expertise
of the authors and the context in which much of the research
on this topic has been done, our primary focus is the consumer
?
Corresponding author. Tel.: +1 603 646 2845; fax: +1 603 646 1308.
E-mail address: [email protected] (K.L. Ailawadi).
packaged goods (CPG) industry, although we include ?ndings
from other retail contexts, wherever relevant.
The conceptual framework that guides our discussion is pro-
vided in Figure 1. The main theme of the framework is that
manufacturer decisions on communication and promotion in?u-
ence retailer decisions and vice versa, and both sets of decisions
determine retailer performance. Further, there is a feedback
effect from retailer performance back to retailer and manufac-
turer decisions as both parties make their communication and
promotionbudget andallocationdecisions basedonthe expected
performance impact.
The left hand side of the framework depicts the key marketing
communication variables under the control of the manufac-
turer and the retailer. Although the manufacturer’s perspective
is not the focus of our article, we include it to the extent that
manufacturer decisions in?uence and are in?uenced by retailer
decisions. Manufacturer decision variables can be categorized
as pull or push (Olver and Farris 1989; Shankar 2008a). The
brand manufacturer’s pull decisions (e.g., advertising, coupons)
can in?uence the retailer’s decisions on the regular price, feature
advertising, display, and price cut for the brand. The manufac-
0022-4359/$ – see front matter © 2008 New York University. Published by Elsevier Inc. All rights reserved.
doi:10.1016/j.jretai.2008.11.002
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 43
Figure 1. Conceptual framework.
turer’s push decisions such as wholesale price, trade promotions,
and sales force efforts also in?uence the retailer’s decisions.
The retailer’s decisions include those on price, price pro-
motions, traditional non-price support like feature advertising
and displays, and other in-store communications such as TVs,
shelf talkers, and shopping cart advertising that are now com-
monly bundled under the phrase “shopper marketing” (Grocery
Management Association 2007). Clearly, these decisions are
in?uenced (and often funded) by manufacturer decisions, and
they determine the retailer’s performance. Although pricing per
se is not within the scope of our review, we include it in our
frameworktore?ect the fact that retailers (andmanufacturers) do
or at least should coordinate and jointly determine their regular
price and price promotion decisions.
The right hand side of the framework summarizes key mea-
sures of performance that are relevant to a retailer (for more
details, see the article on retailer metrics in this special issue).
The metrics range from levels and growth rate of penetration,
traf?c, and sales to levels and growth rate of gross and net pro?t.
Most of these can be measured at the brand, category, store,
and customer levels. Typically, category and store level met-
rics have been most relevant to retailers. While manufacturers
care most about their brand performance, retailers are interested
in individual brands only to the extent that some brands offer
higher margins than others (e.g., private label versus national
brands, Ailawadi and Harlam 2004; Sethuraman 2006), have
higher promotion lifts than others (e.g., high share or high
equity brands, Ailawadi et al. 2006; Slotegraaf and Pauwels
2008), or are more effective at driving store performance (e.g.,
loss leaders, Gauri, Talukdar, and Ratchford 2008) and attract-
ing and retaining high value customers (Chien, George, and
McAlister 2001; Shankar and Krishnamurthi 2008). Increas-
ingly, retailers are also ?nding it useful to focus attention on the
value that individual customers or groups of customers bring
to the retailer (Kumar, Shah, and Venkatesan 2006), and the
impact that groups traditionally considered undesirable, such as
extreme cherry pickers, have on the retailer’s pro?t (Fox and
Hoch 2005; Gauri, Sudhir, and Talukdar 2008). There is also an
important distinction between short and long-term performance
since communication variables can differ signi?cantly in their
short and long-term effectiveness (Mela, Gupta, and Lehmann
1997).
We use the above framework as a roadmap for our synthesis
of literature and directions for further research with emphasis
in the following areas: trade promotions, consumer promotions,
communication and promotion through the newmedia, and bud-
get determination and allocation. Before doing so, we want to
reiterate the differences between manufacturer and retailer per-
spectives, which occur along three main dimensions: objectives,
tools, and outcome measures. As shown in Table 1, the manu-
facturer’s objectives are to maximize company, category and
brand pro?ts, while the retailer’s objectives are to maximize
chain, store, category, private label, and customer pro?ts. Man-
ufacturer tools include brand advertising, consumer and trade
promotions, public relations and sales force, whereas retailer
tools include store and private label advertising, feature adver-
tising, store coupons, and loyalty program. A manufacturer is
primarily interested in the performance of its brands, while the
retailer is more interested in its performance at the category and
the store levels (see van Heerde and Neslin 2008 for greater
44 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
Table 1
Differences between manufacturer and retailer perspectives on communication and promotion.
Dimension Manufacturer Retailer
Objective Maximize company, category and brand pro?ts Maximize corporate, chain, store, category, private label,
and customer pro?ts
Tools Brand advertising, consumer promotion, trade
promotion, sales force, public relations
Store and private label advertising, feature advertising,
store coupons, loyalty card, public relations
Outcome measures Sales, market share, margin, pro?t, ROI, brand
equity, shareholder value
Store traf?c, sales/square foot, store share, pro?t, store
satisfaction, share of wallet
details on manufacturer versus retailer perspectives in the con-
text of promotion effects).
Trade promotions
In the U.S. CPGindustry, trade promotions constitute approx-
imately 60% of the total marketing budget (Trade Promotion
Report 2005), and CPG companies spend more than $75 billion
on trade promotions annually (Drèze and Bell 2003). The mag-
nitude of this number becomes apparent when we compare it
with the total money spent on advertising, which is around $37
billion (Advertising Age 2007). The amount of money spent on
trade promotions demands that we understand the phenomenon
of trade promotion and evaluate its effectiveness.
Several analytical models of trade promotions exist in the
marketing literature, spanning more than two decades, that pro-
vide rich normative insights into why trade promotions exist, the
impact of retailer forward buying, and the brand, retailer, and
consumer factors that should in?uence retailer pass-through of
trade promotions. Until recently, however, empirical work was
limited to a small number of studies examining a small num-
ber of speci?c trade deals offered to a retailer (Armstrong 1991;
Chevalier and Curhan 1976; Curhan and Kopp 1987; Walters
1989).
The reasons for the paucity of empirical work on trade promo-
tions are twofold. First, trade promotions are often considered
by managers as a “cost of doing business,” (Kopp and Greyser
1987) which leads them to not consider it as worthy of investi-
gation. Second, trade promotion data are notoriously hard to
collect, as companies consider trade promotion strategies as
trade secrets and therefore, are unwilling to share them with
researchers. However, the last few years have seen an upsurge
in empirical work on trade promotions and their pass-through
and have provided some important lessons, which we summarize
below.
Different types of trade promotion funds
Until the early nineties, trade promotion funds were largely
in the form of off-invoice discounts for speci?c items in spe-
ci?c time periods. Since then, however, manufacturers have been
moving towards “pay for performance” deals which include bill-
backs and scan-backs but also lump sumcooperative advertising
allowances and development funds (see Cannondale Associates
1996 versus 2000). This move was driven largely by the need
to curb forward buying by retailers. Retailers are likely to pre-
fer unconditional discounts (see Drèze and Bell 2003 for an
analytical proof) while manufacturers prefer deals linked to per-
formance (e.g., price reductions, non-price support, and sales
volume). Gomez, Rao, andMcLaughlin(2007) report that accru-
als, scan-backs, and bill-backs account for over 60% of the total
trade promotion budget, while off-invoice allowances account
for 25.9%. They also ?nd that the relative market power of
retailers versus manufacturers in?uences the size of the bud-
get and the percentage allocated to pay-for-performance versus
off-invoice deals. For instance, the manufacturer’s total bud-
get is lower when it has strong equity as measured by its price
premium. In contrast, the total budget is higher and a greater
portion of that budget is allocated to off-invoice deals for high
sales retailers. The major implication of these different types
of funds is that they are not tied to speci?c items and speci?c
time periods, so both analytical and empirical models need to
account for the fact that weekly changes in per unit wholesale
versus retail prices of individual items or brands may no longer
be the best way to represent pass-through.
Individual versus aggregate pass-through
Empirical research shows that the median pass-through rate
for a manufacturer is less than 100%. There is convergent valid-
ityfor a medianrate of 65–75%across studies byBesanko, Dubé,
and Gupta (2005), Pauwels (2007), and Ailawadi and Harlam
(forthcoming). However, this rate does not necessarily mean
that the retailer pockets the rest of the trade promotion funding.
Ailawadi and Harlam (forthcoming) report that, in aggregate,
promotion spending by the retailer in their study is more than
100% of the total trade promotion funding it receives. Indeed,
the distribution of individual pass-through rates is positively
skewed; most manufacturers receive pass-throughs well below
100%, but a small number enjoy pass-through rates much greater
than 100% and some manufacturers even receive promotion
spending without providing any funding.
Variations in pass-through across categories and
manufacturers
Retailers pass through a larger percentage of trade promo-
tion funds obtained from high share manufacturers. This result
is supported by all three studies on pass-through. Higher priced
manufacturers and larger categories also get higher pass-through
(Ailawadi andHarlamforthcoming; Pauwels 2007). There is less
convergence among the studies on whether retailer pass-through
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 45
for private labels is higher or lower than for national brands.
Besanko, Dubé, and Gupta (2005) report that pass-through is
lower for private label while Ailawadi andHarlam(forthcoming)
?nd that it is higher. Pauwels’ (2007) result is directionally con-
sistent with Ailawadi and Harlam, but the effect falls short of
signi?cance.
Cross pass-through
Analytical models of retailer decisions that are based on
category pro?t maximization suggest that cross pass-through
should exist, that is, trade promotions from one manufacturer
in a given period (often a week) should in?uence the extent
to which the retailer promotes another manufacturer’s brand in
the same period (e.g., Moorthy 2005). Empirically, however,
there is some controversy about the existence of this type of
cross pass-through. Besanko, Dubé, and Gupta (2005) document
both positive and negative cross pass-throughs, and Pauwels
(2007) reports positive cross pass-through for large brands
and negative cross pass-through for small brands. However,
McAlister (2007) refutes the existence of cross pass-through,
showingthat the number of signi?cant cross pass-througheffects
drops signi?cantly when some pooling issues in the study by
Besanko, Dubé, and Gupta (2005) are addressed. In a rejoinder,
Dubé and Gupta (2008) agree but show that allowing for cross
effects does improve overall ?t in various model speci?cations
and thus conclude that the phenomenon exists. Ailawadi and
Harlam (forthcoming), who use actual funding and promotion
spending data to compute pass-through instead of estimating
it from wholesale and retail price changes, ?nd strong evi-
dence for cross-subsidization of promotions – funding received
from manufacturers in a category is used to subsidize pri-
vate label promotions as well as promotions in other, vastly
different categories. However, they do not ?nd a signi?cant
effect of funding from one manufacturer on pass-through for
another manufacturer in the same period and the retailer deci-
sion making process they report supports McAlister’s (2007)
view that weekly cross-brand pass-through is not prevalent or
practical.
Accounting and audit issues
Although academics assume that the amount of money spent
by manufacturers on trade promotions and the amount passed
through by retailers is clear-cut and unambiguous, this is often
not the case in practice. An in-depth study of problems and
best practices in trade promotion accounting (Parvatiyar et al.
2005) reveals that trade promotions are oftennegotiatedverbally,
particularly by smaller players, and record keeping of trade pro-
motions is notoriously inadequate, leading to errors in reporting
and accounting for trade promotions. Retailers often fail to claim
the trade promotion funds they were offered; vendor invoices
sometimes do not re?ect the deals agreed up on; retailers may
mistakenly claim a trade deal more than once. This has led to
the development of a multibillion dollar post-auditing industry
whose function is to discover and try to recover ‘lost’ money for
retailers.
The process of discovering, investigating, con?rming, and
resolving a post-audit recovery claim involves not only the
post-auditors, but the sales and marketing personnel as well as
accounting departments at both the retailer and vendor ?rms. It
often strains relationships between the vendor ?rmand the retail
?rm, as well as between the accounting and sales/marketing per-
sonnel within each ?rm. While the retail buyer and the vendor
salesperson want to maintain a positive relationship, the post-
audit activity and the process of verifying each other’s claims
strains their relationships. And, while accounting personnel look
at post-audit activity as legitimate revenue generation activity,
the marketing and sales personnel view it as a diversion from
their main function. In summary, trade promotions lead to errors,
errors lead to post-audit activity and post-audit activity strains
relationships, especially when it takes place after a signi?cant
delay.
When a claim is resolved the vendor ?rm and the retail ?rm
have to adjust their accounting books. Adjustments are nowesti-
mated to be about 1% of annual sales and may occur as late
as 12–24 months after the transaction (Parvatiyar et al. 2005).
This practice raises ethical and legal questions. The industry is
worried that it may trigger a violation of the Sarbanes/Oxley
act because accounting books need to be adjusted after they
have been initially certi?ed. While the retail industry is acutely
aware of this situation, there is no academic research on these
institutional accounting, auditing, and legal aspects of trade pro-
motions.
Another important aspect of trade promotions has to do with
how promotion spending is treated in ?nancial statements. In
late 2001, new rules developed by the Financial Accounting
Standards Board (FASB) went into effect, whereby companies
are required to deduct price discounts given to retailers and
consumers from revenue rather than reporting them as mar-
keting expenses (Schultz 2002). This was expected to reduce
CPG companies’ promotion spending in the form of price
discounts (e.g., off-invoice and bill-back discounts to retail-
ers, coupons to consumers). However, since the FASB rules
make a distinction between pure price discounts and other
promotion spending such as payments for co-op advertising
and in-store events, it was also expected that CPG ?rms’
would shift more spending towards “shopper marketing” (Neff
2002), a term that has been recently coined to represent mar-
keting activities that can in?uence consumer behavior at the
point of purchase in the store. These accounting rule changes
have justi?ably attracted plenty of attention in the business
press, but academic research on its implications has been
scarce.
Future research directions
The above review suggests several directions for further
research. First, we need to account for different types of trade
promotion funding in empirical analyses of trade promotion and
study the allocation decisions, pass-through, and performance of
these different types. Because the new FASB accounting rules
for promotional spending are likely to have had an effect on not
only the total trade promotion spending by CPG companies but
46 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
also on the mix of different types of funding, research is also
warranted on their impact.
Second, it is important to study variations in budgeting and
pass-through across manufacturers and across retailers given
that the characteristics of both the parties determine these deci-
sions. What manufacturer and retailer characteristics are more
in?uential in determining pass-through rates? How can retail-
ers better manage pass through rates? Retailers pass-through
more of high share manufacturers’ funding, but is this an opti-
mal strategy? After all, high share products have higher baseline
sales, which can make promotions less pro?table for retailers
(McAlister 1986; Tellis and Zufryden 1995; van Heerde and
Neslin 2008).
Third, irrespective of whether retailers currently engage in
cross pass-through or not, research is needed to determine
whether it would be an optimal strategy, not just from a weekly
category pro?t maximization viewpoint (e.g., Moorthy 2005),
but also after accounting for its operational complexity and its
potential negative impact on manufacturer–retailer relationships
and future trade promotion funding.
Fourth, analytical and structural models of these decisions
need to incorporate the changed institutional reality of howtrade
promotions are designed, negotiated, and passed through. They
also need to formalize the role of the relative bargaining power
of manufacturers and retailers, which appears to be a central
factor in the amount and type of trade promotions funding as
well as in the extent of pass-through.
Fifth, we need to distinguish between regular price changes
and promotions in empirical and analytical models of pass-
through because both consumer response and managerial
decision-making are different for the two decisions (e.g., Dubé
and Gupta 2008; McAlister 2008; Shankar and Krishnamurthi
1996). Sixth, the focus of empirical research has been on the
retailer’s pass-through in the formof price promotions. But, non-
price merchandising support variables such as displays, shelf
talkers, and extra shelf space are also important to manufactur-
ers. Future research should study the impact of manufacturer
funding on such non-price support activities of their brands by
retailers.
Finally, there is a sore need for research on the impact of trade
promotions negotiations and post-audit activity on the relation-
ships between manufacturers and retailers. Justice theory and
equity theory in an agency framework are potential avenues
to investigate these issues. This area is also interesting as it
involves cross functional relationships. The marketing, sales,
purchase, accounting, and ?nance departments of vendor and
retail organizations are involved in trade promotion activities,
whereas research on trade promotions has largely ignored the
involvement of ?nance and accounting functional areas.
Consumer promotions
Consumer promotions are an important element of competi-
tive dynamics in retail markets with retailers using a myriad of
promotion techniques to attract consumers. Some of the most
commonly used techniques are the typical price promotions,
“loss leader” promotions (deep discount deals), feature adver-
tising (store ?yers), and in-store displays. According to the
Promotion Marketing Association, the total promotion spending
across all product categories in the USA reached $429 billion
(about 3.65% of the GDP) in 2004. Given the widespread use
of retail promotions and the magnitude of the dollars spent on
them, managers and academicians have a great interest in under-
standing how consumers react to such promotions and how that
affects retailers’ performance (Bodapati 1999; Raghubir, Inman,
and Grande 2004). We summarize belowsome of the most recent
empirical ?ndings in the promotions area as they relate to retailer
decision making and performance.
The sales promotion bump and its decomposition
The immediate increase in a promoted item’s sales when it
is put on promotion is substantial. Meta-analyses by Bijmolt,
van Heerde, and Pieters (2005) and Pan and Shankar (2008)
put the average short-term promotional price elasticity at ?2.62
and ?2.55, respectively. Of course, the entire promotional sales
bump is not incremental either for the retailer or for the man-
ufacturer whose product is being promoted. Beginning with
Gupta (1988), much attention has been paid to decomposing
this sales bump. Recent years have seen a renewed emphasis on
this subject as researchers have moved from decomposition of
promotion elasticity (e.g., Gupta 1988) to decomposition of unit
sales (e.g., van Heerde, Gupta, and Wittink 2003). One major
empirical ?nding from van Heerde and colleagues is that the
brandswitchingfractionof the promotionis signi?cantlysmaller
than previously thought. The estimates of brand switching com-
ponent in studies published after 2002 are around 30–45% (e.g.,
Sun 2005; Sun, Neslin, and Narasimhan 2003; van Heerde,
Gupta, and Wittink 2003; van Heerde, Lee?ang, and Wittink
2004), versus earlier estimates of around 80%(e.g., Bell, Chiang
and Padmanabhan 1999; Chiang 1991; Chintagunta 1993; Gupta
1988). van Heerde and Neslin 2008 provide a good discussion of
the methodological reasons for this downward trend in estimates
of the brand switching fraction.
Almost all of this research takes the manufacturer’s perspec-
tive in decomposing the sales bump. However, as discussed by
van Heerde and Gupta (2006), Ailawadi et al. (2006), and van
Heerde and Neslin (2008), the components of the promotional
bump that are incremental for the retailer and are quite differ-
ent from the ones that are incremental for the manufacturer. In
particular, while both parties bene?t from promotion induced
increases in consumption, manufacturers do not bene?t from
store-switching and retailers do not bene?t from brand switch-
ing (unless, of course, there are margin differences). Using data
from the U.S. drug store chain CVS, Ailawadi et al. (2006) esti-
mate the promotion bump and decompose it from the retailer’s
perspective. They ?nd that, on average, 45% of the bump is
due to switching within the store, 10% is due to accelerating
or “pulling forward” future purchases in the store, and 45% is
incremental sales for the retailer.
“Halo” and store-traf?c effects of promotion
A retailer hopes that promotions not only increase sales of
the promoted items but also attract more consumers into the
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 47
store because, once consumers are in the store, they are likely to
also buy products other than those on promotion. Ailawadi et al.
(2006) provide some insights into the ability of promotions in
one category to in?uence sales in other categories in the store.
They ?nd that, on average, there is a signi?cant positive ‘halo
effect’ of promotions – for every unit of gross promotion lift,
0.16 unit of some other product is purchased elsewhere in the
store.
One particularly popular strategy used by retailers is the
“loss leader” promotion strategy (Drèze 1995; Walters and
MacKenzie 1988), which assumes that promotions on some
products are particularly effective in driving store traf?c. The
loss leader strategy is distinct from other retailer price promo-
tion strategies in that the prices for the selected loss leader items
are set at or below retailers’ respective marginal costs. Retail-
ers consciously incur loss or earn no pro?t on these items, in
the hope that deep discounts on the loss leaders will lead to
increased store traf?c, and, since there are economies of scale
in shopping, once at the store, customers will buy other items in
addition to the loss leaders. So, the expectation from theoreti-
cal models is that the negative contribution from the loss-leader
items bought by the customers will be more than offset by the
pro?t generated from the sale of non-loss-leader items to them
(Bliss and Christopher 1988; Hess and Gerstner 1987; Lal and
Matutes 1994; Rao and Syam 2001).
However, empirical evidence for the effectiveness of loss
leader promotions is limited. Walters and Rinne (1986) showed
that certain portfolios of products promoted as loss leaders have
a greater impact on store traf?c, store sales and deal sales than
other product portfolios, with no signi?cant impact on retailer
pro?ts. Walters and MacKenzie (1988) also found a signi?cant
impact of loss leaders on store traf?c and store sales, but only
two (out of eight) of their categories had signi?cant effects on
store pro?ts – one positive and one negative. Both studies use
fairly simple models with a dummy variable for loss leaders.
Gauri, Talukdar, and Ratchford (2008) conduct a more
sophisticated econometric analysis that accounts for the breadth
and depth of loss leader promotions, using scanner data from 24
stores. They ?nd that loss leader promotions not only increase
store traf?c and average spending, but they also lead to higher
net pro?t contribution for the promoting stores. In fact, they
?nd that there are marked differences across product categories
in their relative effectiveness as loss leaders in boosting store
pro?t stores could generate more pro?ts from if they chose loss
leader categories optimally. In sum, the empirical evidence that
exists does suggest that loss leader promotions are effective.
Consumer price search behavior
To evaluate the impact of price promotions on store per-
formance and to determine whether or not the promotions are
attracting pro?table consumers, a retailer needs to understand
how different consumers respond to price promotions. Con-
sumers may search for deals along both the spatial (across stores)
and temporal dimensions (across time). Several papers have
studiedspatial price searchingrocerymarkets usingeither actual
purchase or survey data (e.g., Carlson and Gieseke 1983; Fox
and Hoch 2005; Putrevu and Ratchford 1997), and a parallel
empirical literature has focused on the temporal dimension of
search, investigating consumer response to promotions through
stockpiling, purchase acceleration and purchase delays (e.g.,
Mela, Jedidi, andBowman1998; Neslin, Henderson, andQuelch
1985).
Gauri, Sudhir, and Talukdar (2008) consider the effect of
both spatial and temporal dimensions of price search on the
pro?tability of price promotions. Gauri and colleagues ?nd that
households that claim to search spatio-temporally avail about
75% of the available savings on average, while those that claim
not to systematically search on either dimension avail about 50%
of the available savings. This suggests that “cherry pickers” do
not get much more in savings than non-cherry pickers. As far as
the size and pro?t impact of the cherry-picking segment is con-
cerned, Fox and Hoch (2005) characterize approximately 8%
of the households in their sample as cherry pickers and show
that these households selectively use secondary stores on cherry
picking trips to disproportionately purchase promoted items.
Talukdar, Gauri, and Grewal (2008) ?nd that on an average only
about 1.5% of households contribute a net negative pro?t to the
store over a 1-year period and extreme cherry picking behavior
gets manifested only with respect to the secondary stores of the
consumers. They also ?nd that an inverse-U relationship exists
between consumers’ opportunity cost of cross-store price search
and their likelihood of exhibiting ECP behavior. In summary, it
appears that neither the size of the cherry picking segment nor
its negative impact on retailer pro?ts is as high as is generally
believed.
Short term and long-term impact of promotions
As noted earlier, Ailawadi et al. (2006) ?nd that, on average
45% of the promotion bump is incremental for the retailer in
their study. However, they also ?nd that, once costs and reduced
promotional margins are taken into account, over 50% of pro-
motions are not pro?table for the retailer. Across 460 product
categories over a 4-year period, Nijs et al. (2001) ?nd that in
58% of the cases there is a positive effect of promotions on
category sales (increases in category sales should bene?t both
manufacturers and retailers). Srinivasan et al. (2004) also ?nd
that though promotions have a predominantly positive impact
on manufacturer revenues, their impact on retailer revenue and
margin is mixed, even after accounting for cross-category and
store-traf?c effects. In particular, they report that retailer rev-
enue elasticities are higher for brands with frequent and shallow
promotions, for impulse products, and in categories with a low
degree of brand proliferation. And retailer margin elasticities
are higher for promotions of small-share brands and for brands
with infrequent and shallow promotions. Overall, therefore, not
all promotions have a positive revenue impact for retailers, and
the pro?t impact, in the few cases where it has been studied, is
decidedly mixed.
As far as long-term effects of promotions are concerned,
much of the work has been done from the manufacturer’s per-
spective. Mela, Gupta, and Lehmann (1997) ?nd that consumers
become more price and promotion sensitive in their brand choice
48 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
decisions over time because of reducedadvertisingandincreased
promotions. Mela, Jedidi, and Bowman (1998) conclude that the
increased long-term exposure of households to promotions has
increased their tendency to “lie in wait” for especially good pro-
motions. Kopalle, Mela, and Marsh (1999) ?nd that increased
promotions have three negative dynamic effects – reduce base-
line sales, increase price sensitivity, and diminish the ability of
the promoted brand to take share from competitors. Substantial
evidence has been accumulated using time series VARX mod-
els that promotions have no “permanent” effects (e.g., Pauwels,
Hanssens, and Siddarth 2002; Steenkamp et al. 2005).
There is less research on the long-term effects of promotions
from the retailer’s perspective, but the few studies on this issue
showthat they are not signi?cant. For instance, Nijs et al. (2001)
?nd that in 98% of the cases there is no permanent effect of pro-
motions on category sales. Consistent with this result, Srinivasan
et al. (2004) ?nd that there are no permanent effects of promotion
on either the revenue or margin of retailers.
Effects of different types of promotions
The vast majority of research on promotions involves price
promotions with or without accompanying features or displays.
We now have a fairly good understanding of the magnitude of
price promotion elasticities, with and without features and dis-
plays (e.g., Bijmolt, van Heerde, and Pieters 2005; Narasimhan,
Neslin, and Sen 1996; Pan and Shankar 2008). The consensus
is that elasticities can increase several fold in the presence of
features and/or displays.
There is some newworkonthe effectiveness of various design
elements of retailers’ weekly promotional ?yers. Gijsbrechts,
Campo, and Goossens (2003) examine howcomposition charac-
teristics of the ?yer affect store traf?c and sales. Not surprisingly,
they ?nd that ?yers featuring deeper discounts are more effective
in driving traf?c and sales. They also show that total ?yer size
does not seem to matter, but ?yers featuring a larger proportion
of food and private label promotions, and ?yers featuring spe-
cialty categories like wines and delicatessen on the cover page
are more effective in generating store traf?c and store sales.
Pieters, Wedel, and Zhang (2007) use eye-tracking technol-
ogy to understand how attention to the ads on a ?yer page is
affected by the surface size of ?ve design elements – brand,
text, pictorial, price, and promotion. They ?nd that the total sur-
face size of a feature ad has a strong effect on attention, the
size of the pictorial element has the largest effect and the size
of the text element has little to no effect. They also present a
method for optimizing these design elements and ?nd that the
optimal layout differs for manufacturer brands, private label, and
unbranded products. In particular, the pictorial, price, and brand
elements should be most prominent for the ?rst; price and brand
elements should be most prominent for the second; and price
and pictorial elements should be most prominent for the third.
Thus, new research is providing some useful guidelines for how
retailers should design their weekly store ?yers.
There has also been some interesting work on the effec-
tiveness of different types of promotions such as promotions
with quantity limits, multiple unit promotions, and bonus packs.
Inman, Peter, and Raghubir (1997) ?nd that the presence of a
restriction (e.g., purchase limit, purchase precondition, or time
limit) serves to accentuate deal value and acts as a “promoter”
of promotions. Across four studies, they demonstrate the robust-
ness of a “restriction effect” whereby more stringent restrictions
are effective at signaling value, thereby increasing the restricted
brand’s choice probability. Wansink, Hoch, and Kent (1998)
examine quantity limits froma different perspective. They focus
on consumers’ purchase quantity decision and the psychological
process underlying it. Across ?ve studies, they ?nd evidence of
an anchoring and adjustment effect whereby average purchase
quantity increases in the presence of a quantity limit. Manning
and Sprott (2007) study the effect of multiple unit price promo-
tions (e.g., 2 for $2; 8 for $8) on consumers’ quantity purchase
intentions. They ?nd a positive effect only when the multiple
quantity anchor speci?ed is high (e.g., 8 or 20, not 2 or 4), sug-
gesting that the anchoring works but only at high levels, and
only for frequently consumed products.
In sum, there are important behavioral mechanisms at play in
limit and multiple unit promotions, with contingency effects that
need more study. Furthermore, these papers have, to some extent
found evidence of opposing effects. On the one hand, Inman et
al. (1997) suggest that purchase incidence declines as the quan-
tity limit increases. On the other hand, Wansink et al. suggest
that average purchase quantity increases with the limit. Because
total sales equal the number of shoppers buying the brand times
the average purchase quantity per shopper, further research is
needed to determine the shape of the unit sales-quantity limit
relationship.
Finally, Hardesty and Bearden (2003), using three exper-
imental studies, investigate the effects of promotion price
discounts relative to those of bonus packs across promotional
bene?t levels. Their results suggest that price discounts and
bonus packs are valued similarly for both low and moderate
promotional bene?t levels, but price discounts are preferred to
bonus packs when promotional bene?t levels are high.
Promotion framing
A large body of behavioral research demonstrates that the
manner in which a deal is framed in?uences consumer per-
ception of the deal value, purchase intent, and search intent.
Framing refers to how the deal price is communicated to the
consumer, for example, whether an external reference price is
provided, whether the deal is in dollar or percentage terms, and
whether prices of competing products or other contextual infor-
mation are provided. The major implication from this research
stream for retailers is that deals should be carefully framed
because small modi?cations in wording and the information
provided can have a signi?cant impact on the effectiveness and
ef?ciency of the deal. While it is beyond the scope of this arti-
cle to report on the ?ndings of individual articles, we wish
to highlight two meta-analyses on the subject. Compeau and
Grewal’s (1998) meta-analysis concludes that the mere pres-
ence of an advertised reference price increases the consumer’s
internal reference price and the perceived value of the deal and
reduces their intentions to search for a better deal. They also ?nd
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 49
that these effects are stronger for higher advertised reference
prices.
Krishna et al.’s (2002) meta-analysis offers interesting
insights into the impact of multiple factors on perceived deal
savings. They ?nd that among deal characteristics, (a) the deal
percentage increases perceived savings over and above the dol-
lar amount of the deal; (b) the more the savings on a bundle
of items over and above savings on individual items, the higher
the perceived savings; and (c) the more the number of items
in the bundle, the smaller the perceived savings. Further, they
?nd that among situational factors, perceived savings are higher
when (a) the deal is included in an advertisement; (b) it is on a
national brand relative to a private label or generic brand; and
(c) when it is offered by a specialty store or supermarket relative
to a discount or department store. Finally, they ?nd that among
price presentation factors, (a) small plausible deals increase per-
ceived savings more than large, implausible deals; (b) using
regular price as an external reference price increases perceived
savings although the presence of an MSRP (manufacturer sug-
gested retail price) does not; (c) objective deals (with speci?c
savings) increase perceived savings more than tensile ones (sav-
ings of x% or more); and (d) a within-store frame (current price
vs. regular price) is more effective than a between-store frame
(own price vs. competing store’s price).
Price promotion coordination
Pricing and promotion are often studied almost in isolation
of each other. Indeed, pricing and promotion decisions are made
by different managers in different departments in some retail
chains. This practice increases the possibility of sub-optimal
decisions on both fronts. Work by Bolton and Shankar (2003),
Shankar and Bolton (2004) and Bolton, Montoya, and Shankar
(2007) show the nature and extent of the relationships between
retailer pricing and promotion decisions that have useful impli-
cations for retailer promotion strategy.
Bolton and Shankar (2003) showthat retailers practice a num-
ber of price-promotional strategies beyondthe commonlyknown
Hi-Lopricingandeverydaylowpricing(EDLP) strategies. AHi-
Lo (EDLP) pricing strategy is typically associated with a higher
(lower) deal elasticity but a lower (higher) regular price elas-
ticity (Shankar and Krishnamurthi 1996). Bolton and Shankar
(2003) ?nd that retailer pricing and promotion strategies are
based on combinations of four underlying dimensions: relative
price, price variation, deal intensity and deal support and that
at the brand-store level, retailers practice ?ve pricing strategies:
exclusive, moderately promotional, Hi-Lo, EDLP, and aggres-
sive pricing strategies. Their results also show that the most
prevalent pricing strategy is characterized by average relative
brand price, low price variation, medium promotion intensity,
and medium deal support. Shankar and Bolton (2004) ?nd that
competitor factors such as frequency of promotions and price
level, retail chain factors such as size and positioning and cat-
egory factors such as storability and necessity explain most of
the variance in retailers’ price promotion coordination decisions.
Among these, competitor factors explain the bulk (62%) of the
variation in retailer price promotion coordination.
Bolton, Montoya, andShankar (2007) argue that price promo-
tion coordination is a key driver of retailer pro?tability. Retailers
need to better coordinate the prices and promotions of brands not
only within a category, but also across categories. Furthermore,
retailers should coordinate prices and promotions across differ-
ent shopping formats. For example, a retailer such as Wal-Mart
may have regular Wal-Mart, Wal-Mart supercenter, and Neigh-
borhood Markets stores not too far from one another. They can
improve their corporate pro?ts by planning and coordinating
the prices and promotions across brands, categories and store
formats. Gauri, Trivedi, and Grewal (2008) emphasize that the
price promotion strategy (EDLP, HiLo and Hybrid) and format
strategy (Supermarket, Supercenter and Limited Assortment)
are two key elements of the overall retail strategy of the stores.
They consider both these strategies in a single framework and
?nd that consideration of any one strategy in isolation fails to
depict a complete picture, and the strategic implications change
signi?cantly when both the price promotion and format strate-
gies are studied in combination. Taken together, the studies on
pricing and promotion suggest that retailers can improve the
effectiveness of promotions by coordinating them with pricing
decisions. They can use the knowledge and understanding of
the determinants of price promotion strategy and coordination
to improve their pro?tability.
National brand vs. private label promotions
National brands and private labels may differ in promo-
tion effectiveness and the differences in their effectiveness
have important implications for retailer promotion strategy. The
effects of promotions of a national brand and private label/store
brand on the sales of each other are asymmetric. When high-
price tier brands promote, theydrawmore shoppers fromusers of
low-price tier brands than vice versa (Blattberg and Wisneswki
1989). Extending this logic to national and store brands, which
typically are in high-price tier and low-price tier, respectively,
we can conclude that promotions of national brands are more
effective than those of store brands.
Indeed, much analytical work suggests that private labels
should not be promoted (see Sethuraman 2006), but empiri-
cal evidence suggests that retailers do promote private label
(Shankar and Krishnamurthi 2008). The ?ndings of Ailawadi
et al. (2006) provide one explanation for this practice – even
though the unit sales impact of promotion is smaller for pri-
vate labels than for national brands, the pro?t impact may be
higher for private labels due to the higher retail margins on pri-
vate labels. Shankar and Krishnamurthi (2008) develop a model
of optimal retailer decisions on regular price, deal depth, and
frequency of deals for both national and store brands under
the goal of category pro?t maximization based on store level
data for stores with two different pricing policy/format posi-
tioning, EDLP and Hi-Lo. Their analytical and empirical results
show that large national brands should be regular priced highest
and promoted less often with shallow deal discounts relative to
other brands within each EDLP and Hi-Lo store; small national
brands should be regular priced at a moderate level and pro-
moted at a moderate (high) frequency relative to other brands
50 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
with deeper discounts than large national brands within each
EDLP (Hi-Lo) store; and store brands should be regular priced
lowest and promoted at a low-moderate (high) frequency with
deep (low-moderate) discounts within each EDLP(Hi-Lo) store.
Future research directions
As discussed earlier, much of the work on decomposing the
sales bump takes the perspective of the manufacturer. More
research is needed from the retailer’s perspective. This work
should be done for different retail formats and for different types
of promotions.
Despite the importance of studying the pro?t impact of pro-
motions, due to lack of publicly available cost data, most of the
past empirical work has focused on the volume impact of pro-
motions. The few recent studies that have considered the pro?t
impact of promotions show that it can be quite different from
sales impact, so more research is needed in this area.
The effectiveness of promotions of national brands has
been extensively studied. More research, however, is needed
to understand the motivations for private label promotions and
their effectiveness. Promotional pass-through decisions for store
brands is one topic on which not much is known. Further-
more, channel blurring—the phenomenon in which consumers
are moving their purchases of a product category from chan-
nels traditionally associated with that category (e.g., grocery) to
alternative channels (e.g., mass, club, extreme value/dollar) and
in which retailers from one channel are selling items tradition-
ally associated with other channels (Luchs, Inman, and Shankar
2007)—is reorienting the promotional landscape as store and
channel switching are becoming important consequences of pro-
motion.
Another area in which future research would be useful is the
performance impact of loss leader promotions across categories,
SKUs and brands. More research is needed to identify the most
effective loss leader brands and categories fromthe point of view
of driving not just store traf?c and sales, but also store pro?t.
It would also be interesting to explore the existence of possible
asymmetric effects at various levels, for example, loss leader
promotions on soda may affect chips sales more than the chips
sales affect soda category (e.g., Bezawada et al. forthcoming).
More work is needed to identify win–win promotions for
both manufacturers and retailers. The extent to which promotion
increases category consumption is bene?cial for both parties
and we now have a good understanding of how to model the
impact of promotion on consumption (e.g., Ailawadi and Neslin
1998) and also how this effect varies across categories (e.g.,
Bell, Chiang, Padmanabhan 1999; Nijs et al. 2001). However,
we also need to bring together the divergent perspectives of the
manufacturer and the retailer on the brand versus store issue.
A promising area of work is the effort to link brand equity
to store equity. Chien, George, and McAlister (2001) provide
a useful conceptual framework and methodology for identify-
ing brands that attract a retailer’s most valuable customers, and
McAlister, George, and Chien (2008) examine the pro?tability
of consumers attracted to promotions of different brands. Not
only does such research try to bring together manufacturer and
retailer perspectives, it makes an important move from brand
and category pro?t to store and customer pro?t.
More research is needed on the value of jointly coordinating
price and promotion and on decision models which facilitate
price promotion coordination, especially with the emergence
of shopper marketing. Shopper marketing is getting signi?cant
attention in the business press as both manufacturers and retail-
ers recognize the importance of in?uences during what senior
marketers at P&G have called “the ?rst moment of truth.” As
manufacturers work with retailers to in?uence the consumer’s
experience at the ?rst moment of truth, they must develop
win–win shopper marketing strategies with retailers. This is
an opportune time for researchers to review the different shop-
per marketing strategies that are being tested and evaluate their
effectiveness. New technologies such as RFIDs, cameras, and
videos on shopping carts and in other locations in the store offer
strong potential to study shopper marketing in great detail.
Shopper marketing includes activities such as in-store layout,
aisle and display management strategies. These activities have
important effects on the sales of items in a store. Bezawada et al.
(forthcoming) showthat the cross-category effects of aisle place-
ment are asymmetric across categories. In an empirical analysis
of aisle and display placements of beverages and salty snacks,
they ?nd that the salty snacks have a greater effect on the sales
of carbonated beverages than vice versa. Research on shopper
marketing is still in its infancy and more studies are needed to
more accurately assess its impact on consumer purchases.
Additional research that directly connects consumer shop-
ping, price search, and deal response behavior to the
effectiveness of promotions for the retailer is needed. For exam-
ple, the insights gained from analysis of cherry picking patterns
across stores would be useful in developing a structural model
of store competition that accounts for the fact that consumers
choose stores on the basis of their baskets of purchases and
can choose from either inter-temporal or cross-store cherry
picking patterns. As another instance, researchers have stud-
ied how consumers respond to different types of promotions,
the behavioral mechanisms that might underlie their response,
and the contingencies under which some promotion designs
are more effective than others. A review article that pulls
together these consumer-level learnings and provides an integra-
tive framework for conceptualizing different promotion types
and their effects would be helpful to retailers and researchers
alike.
Communication and promotion through the new media
New/unmeasured media such as the Web, email, blog, video,
other social media, and mobile continue grow in usage and
popularity, but not much is known about their effectiveness,
making allocation to such media an important but challeng-
ing task (Shankar and Hollinger 2007). Although most CPG
manufacturers still spend the vast majority of their marketing
budgets on traditional media, their allocation to new media is
steadily increasing. For example, Procter & Gamble, the lead-
ing consumer goods marketing spender, hiked its spending on
unmeasured media in 2006 by roughly 15%over 2005 compared
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 51
to an increase of only 3.9%in measured media in the same period
(Advertising Age 2007). The media mix for its major brands now
includes greater allocation to in-store (shopper marketing), the
Internet, and other unmeasured media (Tode 2007).
Retailer implications of new media
From a retailer standpoint, manufacturer reallocation toward
new media has important implications. First, the money allo-
cated to trade and consumer promotions may change from the
past. Second, greater investments in shopper marketing means
stronger retailer focus on in-store decisions. Third, many online
retailers need to coordinate their newmedia promotion decisions
with those of the relevant manufacturers.
Retailers themselves have started to use the new media in
different ways. Many retailers use email extensively to alert
shoppers about new products, promotions, and store openings.
Some even offer coupons for downloading at their web sites.
For example, Kroger allows a shopper to go to its Web site
(http://shortcuts.com/?promo=kroger) and download manufac-
turer coupons onto her/his loyalty card, saving the need to
identify and clip coupons. These coupons will be automati-
cally redeemed when the shopper checks the relevant items out
with her/his loyalty card at a Kroger store. Other retailers are
using different forms of social media (Bustos 2008). American
Eagle has Facebook applications, while retailers like Wal-Mart
and Target have Facebook sponsored groups. Urban out?tters
has MySpace pages, 1-800-Flowers has second life e-stores,
Buy.com, Radioshack, and Overstock.com have Youtube/Video
podcasts, and Of?cemax, Burger King and Taco Bell have viral
micro sites.
A study of 300 Internet and multichannel retailers revealed
that the growth in consumer usage of the new media witnessed
a shift in allocation of efforts from the ubiquitous free ship-
ping promotion to more personalized promotions and live chat
(Webtrends 2006). Retailers surveyed by the study ranked e-mail
marketing as the most important demand-generation activity for
holidaysuccess, followedbysearchengine marketingandsearch
engine optimization.
Research on retailer efforts in the new media is limited, but
substantial work has been done on consumer purchase behav-
ior online versus of?ine. It shows that online shoppers are more
convenience-conscious (Degeratu, Rangaswamy, and Wu 2000)
and more brand loyal than of?ine shoppers (Danaher, Wilson,
and Davis 2003; Shankar, Smith, and Rangaswamy 2003). They
are more price sensitive when there is inadequate non-price
information on the website (Degeratu et al. 2000). However, in
the presence of non-price information, for example, on brand,
quality, and product features, consumers are less price sensi-
tive online than of?ine (Alba et al. 1997; Lynch and Ariely
2000; Shankar, Rangaswamy, and Pusateri 2001). These dif-
ferences suggest that retailers should use different types of
price promotions online versus of?ine. The online medium also
offers greater potential for customized promotions targeted to
individual consumers (Kannan and Kopalle 2001). Zhang and
Krishnamurthi’s (2004) decision-support model for customiz-
ing online promotions provides recommendations on when, how
much, and to whom to promote and may signi?cantly improve
promotion effectiveness over current practice. Zhang and Wedel
(forthcoming) show that the incremental pay-off to manufac-
turers from offering individual-level customized promotions
relative to segment level or mass market level customized pro-
motions is small, especially in of?ine stores. However, they do
not consider the perspective of the retailer in their analysis, so
we do not know whether personalized online promotions offer
retailer bene?ts such as improved customer loyalty or greater
store traf?c.
Future research directions
Given the nascent and growing newmedia landscape, a num-
ber of research questions remain unanswered. First, how do
the effects of communication and promotion differ between the
traditional and the new media? Shankar and Hollinger (2007)
suggest that traditional media communication is largely intru-
sive, whereas communication and promotion through the new
media needs to be more non-intrusive or user-demanded. This
argument suggests that promotion through the new media is
likely to be more effective than that through the traditional
media. However, several challenges, including measurement
issues, audience reach, and content of promotion relating to the
social media remain (Winer forthcoming).
Second, how should retailers formulate their Internet promo-
tion strategy? Given that consumers increasingly use multiple
channels (Kushwaha and Shankar 2008), how should retailers
communicate and promote to consumers? Should a retailer fea-
ture the local weekly promotions on its Web site and proactively
email its consumers in its opt-in email list? While this strategy
may get the consumers to visit the store often, it might also
highlight and offer more discounts to the loyal shoppers, who
would have otherwise bought the items at regular prices. Care-
ful empirical analysis is needed to answer these questions. The
online medium also opens other promotional avenues for retail-
ers such as electronic coupons and deal forums (Gopal et al.
2006). More research is needed to guide retailers on whether,
when, and how to best exploit these opportunities.
Third, retailers and manufacturers need better models of
relative allocation of marketing budget toward traditional and
new media. Such models should incorporate interaction effects
between the two types of media and the different media vehicles
that constitute these media.
Fourth, howshould retailers leverage the social media promo-
tion efforts of brand manufacturers? Many brand manufacturers
have their own social media that include community sites, corpo-
rate blogs and video sites. How can a retailer bene?t from these
efforts? An average retailer deals with hundreds of brand man-
ufacturers or suppliers, so with which manufacturers should a
retailers partner on its social media efforts? Research addressing
these questions would be useful to academics and practitioners
alike.
Fifth, should retailers set up their own social networks? If so,
what should their strategy be and how should they coordinate or
manage the network? How should they allocate their marketing
efforts between their own network and the networks of their
52 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
partner vendors? Future research could address these questions
as well.
Communication and promotion budget determination and
allocation
Determining the communication and promotion budget and
allocating that budget across different promotional tools are
important marketing decisions, particularly for manufacturers,
who spend considerable money on promoting their brands. From
a retailer’s viewpoint, manufacturer spending decisions on con-
sumer and trade promotions are critical as they affect their
pricing and promotional policies. We review these decisions
brie?y (for a detailed review of these decisions from a man-
ufacturer standpoint, see Shankar 2008a).
Brand manufacturers set their communication and promotion
budgets based on one or more the following methods: objective
and task, competitive parity, percentage change from previous
year, and percentage of sales methods (Kotler and Keller 2009).
Once the budget is decided, a brand manger decides whether to
pursue a predominantly pull or push strategy. The pull strategy is
aimed at communicating directly to the end consumers to induce
them to seek the brand at the retail store, while the push strat-
egy is based on offering incentives to the channel intermediaries
such as retailers to actively sell the brand to the end consumers
(Kotler and Keller 2009). The pull strategy is built around pro-
motional tools such as advertising and consumer promotions,
whereas the push strategy is centered on tools such as trade pro-
motions and sales force. When a brand follows a pull strategy,
it spends the majority of its promotional budget on advertising
and consumer promotions, but when it pursues a push strategy,
it expends its promotional budget mostly on trade promotions
and sales force (Shankar 2008b). The brand manager further
allocates the brand’s promotional budget within each promo-
tional tool. For example, within advertising, the manufacturer
allocates spending between traditional media (e.g., TV, print,
radio) and new media (e.g., the Web, email, blog, social media,
mobile media).
Manufacturers allocate marketing budgets to different pro-
motional tools on the basis of relative competitive elasticities
(Shankar 2008a). For most CPG?rms, the bulk of the marketing
budget goes to advertising and sales promotion (consumer and
trade promotion). Over the past two decades, the allocation for
CPG ?rms has shifted from advertising toward sales promotion
due to three key reasons: increasing consumer decision-making
at the point of purchase, the rise of retailer power, and the
fragmentation of mass media communication vehicles (Shankar
2008a). Today, most CPG manufacturers spend approximately
two-thirds to three-fourths of their overall marketing dollars
on sales promotion. This shift is mainly because the ratio
of sales promotion elasticity to advertising elasticity is high.
Meta-analyses of advertising elasticities (Assmus, Farley, and
Lehmann 1984) and promotional elasticities (Pan and Shankar
2008) suggest that the median short-term advertising, carryover
advertising, and promotional elasticities are 0.22, 0.47, and 2.55,
respectively. Furthermore, the median deal elasticity is 4.45 (Pan
and Shankar 2008), underlying the growing allocation toward
sales promotion. These elasticities, however, capture only the
short-term effects and do not re?ect the accepted notion that
while advertising’s positive effects are realized primarily over
the long-term, promotions’ positive effects are re?ected predom-
inantly in the short-term (Dekimpe and Hanssens 1999). Also,
these advertising elasticities may underestimate advertising
effectiveness because they do not capture second order effects
whereby heavily advertised brands are more likely to get broader
as well as deeper distribution (Farris and Reibstein 2000).
An understanding of advertising and promotion elasticities
and how manufacturers allocate budgets to advertising and dif-
ferent promotions tools is important froma retailer’s perspective
for at least two reasons. First, since much if not all of a retailer’s
promotion spending comes directly from manufacturers’ trade
promotion funds, manufacturer budgets directly affect retailer
budgets. Second, there is a strong conceptual argument that there
is synergy between manufacturer advertising and retail promo-
tion effectiveness (Farris, Olver, and de Kluyver 1989; Olver
and Farris 1989). If so, retailers need to take these synergies
into account in determining their own budgets.
Future research directions
Moving forward, we need research on several issues. First, we
need more models of pull and push strategies that allow interac-
tion or synergistic effects of pull and push elements (e.g., Naik,
Raman, and Winer 2005). Amethodological issue in developing
such models is multicollinearity which occurs when elements
of push and pull strategies are highly correlated, precluding the
estimation of synergistic effects.
Second, more research is needed on the return on investment
(ROI) of communication and promotional budgets and cam-
paigns, especially for retailers. As we have noted above, work
on budgeting and allocation has been done almost solely from
the manufacturer’s viewpoint. But many retailers also spend
a signi?cant portion of their marketing budget on advertising,
apart from traditional promotion spending. We need descriptive
research on how they make these budget decisions in practice
as well as normative and optimization models to prescribe how
they should make these decisions.
Third, empirical support for the synergy between manufac-
turer advertising and retail promotion effectiveness is limited
and not particularly consistent. Sethuraman and Tellis (2002)
?nd a positive relationship between category advertising and
retail promotions but Mela, Gupta, andLehmann(1997) andNijs
et al. (2001) ?nd that advertising intensity reduces the effective-
ness of price promotions. Resolution of this issue is important if
retailers are to appropriately account for manufacturer advertis-
ing in their own promotion budgeting decisions. Similarly, the
cross-effects of advertising and promotion of different brands
on one another are important in determining retailers’ optimal
prices and promotions.
Other avenues for future research
There are several other important issues that need research
attention. First, not much is known about differences in the effec-
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 53
tiveness of communication and promotion of the same product
across multiple countries. More retailers are going global these
days. Retailers such as Carrefour and Metro derive a major-
ity of revenues and pro?ts from outside the countries in which
they are headquartered. Wal-Mart is increasingly looking for
overseas expansion and growth. Because an effective commu-
nication and promotion strategy in one country may not always
work in another country, cross-national research on promotion
effectiveness is desirable.
Second, we need a deeper understanding of how the effec-
tiveness of advertising and promotion differs across the different
stages of the product life cycle. While prior research (e.g., Farris
and Buzzell 1979; Shankar 2008b) suggests that manufacturers
allocate more budget to the more elastic marketing instrument
over the life cycle, not much is known froma retailer perspective.
How should a retailer allocate resources toward store coupons,
feature advertising, and other in-store efforts for products that
are in different life cycle stages?
Third, manufacturers and retailers would be bene?ted by a
better knowledge of the execution issues involving promotion.
Manufacturers, retailers, and third party information vendors
spend considerable amount of time measuring promotions and
auditingin-store executionof promotions andrelatedevents. The
timeliness of these activities is critically important to obtaining
clean data and to ensuring that promotions are executed accord-
ing to plan. Accuracy in three dimensions of execution is critical:
delivery of required all commodity volume (ACV), execution
of promotional activities according to the promotion calendar,
and alignment of in-store placement of items with planograms.
An in-depth analysis of these issues would offer useful exe-
cution guidelines to retailers, manufacturers and relevant third
parties.
Conclusion
Communication and promotion decisions form the heart
of retailer customer experience management strategy. In this
review, we have addressed two key questions from a retailer’s
perspective: (1) what have we learned from prior research
about promotion, advertising, and other forms of communica-
tion and (2) what major issues should future research in this area
address. In addressing these questions, we followed a frame-
work that captures the interrelationships among manufacturer
and retailer communication and promotion decisions and retailer
performance. We examined these questions under four major
topics: determination and allocation of promotion budget, trade
promotions, consumer promotions and communication and pro-
motion through the newmedia. Our reviewreveals several useful
insights from prior research and identi?es many fruitful topics
and questions for future research.
Acknowledgements
The genesis of this article is in the Thought Leadership
Conference on Customer Experience Management in Retail-
ing organized at Babson College in April 2008. The authors
thank the conference co-chairs, Dhruv Grewal, V. Kumar, and
Michael Levy and the other conference participants for their
helpful comments and suggestions.
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doc_611609984.pdf
Communication and promotion decisions are a fundamental part of retailer customer experience management strategy. In this review paper, we address two key questions from a retailer's perspective: (1) what have we learned from prior research about promotion, advertising, and other forms of communication and (2) what major issues should future research in this area address..
Journal of Retailing 85 (1, 2009) 42–55
Communication and Promotion Decisions in Retailing:
A Review and Directions for Future Research
Kusum L. Ailawadi
a,?
, J.P. Beauchamp
b
, Naveen Donthu
c
,
Dinesh K. Gauri
d
, Venkatesh Shankar
e
a
Tuck School of Business at Dartmouth, 100 Tuck Hall, Dartmouth College, Hanover, NH 03755, United States
b
Information Resources Inc., United States
c
Georgia State University, Atlanta, GA, United States
d
Syracuse University, Syracuse, NY, United States
e
Mays Business School, Texas A&M University, College Station, TX, United States
Abstract
Communication and promotion decisions are a fundamental part of retailer customer experience management strategy. In this review paper,
we address two key questions from a retailer’s perspective: (1) what have we learned from prior research about promotion, advertising, and other
forms of communication and (2) what major issues should future research in this area address. In addressing these questions, we propose and
follow a framework that captures the interrelationships among manufacturer and retailer communication and promotion decisions and retailer
performance. We examine these questions under four major topics: determination and allocation of promotion budget, trade promotions, consumer
promotions and communication and promotion through the new media. Our review offers several useful insights and identi?es many fruitful topics
and questions for future research.
© 2008 New York University. Published by Elsevier Inc. All rights reserved.
Keywords: Communication; Promotion; Advertising; New media: Resource allocation; Trade promotion; Consumer promotion; Accounting; Legal issues
Introduction
Communication and promotion decisions are a critical ele-
ment of retailer customer experience management strategy.
There is an extensive literature on marketing communication
and promotion, consisting of both analytical and empirical mod-
els. Several useful reviews summarize what we know about this
very broad and important area, primarily from a manufacturer’s
standpoint (e.g., Neslin 2006; Stewart and Kamins 2002). Our
objective in this article is to examine one slice of this large body
of research as it relates to retailers. We address the following
questions froma retailer’s perspective: (1) what have we learned
from the past decade of research about promotion, advertising,
and other forms of communication and (2) what major issues
should future research in this area address? Given the expertise
of the authors and the context in which much of the research
on this topic has been done, our primary focus is the consumer
?
Corresponding author. Tel.: +1 603 646 2845; fax: +1 603 646 1308.
E-mail address: [email protected] (K.L. Ailawadi).
packaged goods (CPG) industry, although we include ?ndings
from other retail contexts, wherever relevant.
The conceptual framework that guides our discussion is pro-
vided in Figure 1. The main theme of the framework is that
manufacturer decisions on communication and promotion in?u-
ence retailer decisions and vice versa, and both sets of decisions
determine retailer performance. Further, there is a feedback
effect from retailer performance back to retailer and manufac-
turer decisions as both parties make their communication and
promotionbudget andallocationdecisions basedonthe expected
performance impact.
The left hand side of the framework depicts the key marketing
communication variables under the control of the manufac-
turer and the retailer. Although the manufacturer’s perspective
is not the focus of our article, we include it to the extent that
manufacturer decisions in?uence and are in?uenced by retailer
decisions. Manufacturer decision variables can be categorized
as pull or push (Olver and Farris 1989; Shankar 2008a). The
brand manufacturer’s pull decisions (e.g., advertising, coupons)
can in?uence the retailer’s decisions on the regular price, feature
advertising, display, and price cut for the brand. The manufac-
0022-4359/$ – see front matter © 2008 New York University. Published by Elsevier Inc. All rights reserved.
doi:10.1016/j.jretai.2008.11.002
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 43
Figure 1. Conceptual framework.
turer’s push decisions such as wholesale price, trade promotions,
and sales force efforts also in?uence the retailer’s decisions.
The retailer’s decisions include those on price, price pro-
motions, traditional non-price support like feature advertising
and displays, and other in-store communications such as TVs,
shelf talkers, and shopping cart advertising that are now com-
monly bundled under the phrase “shopper marketing” (Grocery
Management Association 2007). Clearly, these decisions are
in?uenced (and often funded) by manufacturer decisions, and
they determine the retailer’s performance. Although pricing per
se is not within the scope of our review, we include it in our
frameworktore?ect the fact that retailers (andmanufacturers) do
or at least should coordinate and jointly determine their regular
price and price promotion decisions.
The right hand side of the framework summarizes key mea-
sures of performance that are relevant to a retailer (for more
details, see the article on retailer metrics in this special issue).
The metrics range from levels and growth rate of penetration,
traf?c, and sales to levels and growth rate of gross and net pro?t.
Most of these can be measured at the brand, category, store,
and customer levels. Typically, category and store level met-
rics have been most relevant to retailers. While manufacturers
care most about their brand performance, retailers are interested
in individual brands only to the extent that some brands offer
higher margins than others (e.g., private label versus national
brands, Ailawadi and Harlam 2004; Sethuraman 2006), have
higher promotion lifts than others (e.g., high share or high
equity brands, Ailawadi et al. 2006; Slotegraaf and Pauwels
2008), or are more effective at driving store performance (e.g.,
loss leaders, Gauri, Talukdar, and Ratchford 2008) and attract-
ing and retaining high value customers (Chien, George, and
McAlister 2001; Shankar and Krishnamurthi 2008). Increas-
ingly, retailers are also ?nding it useful to focus attention on the
value that individual customers or groups of customers bring
to the retailer (Kumar, Shah, and Venkatesan 2006), and the
impact that groups traditionally considered undesirable, such as
extreme cherry pickers, have on the retailer’s pro?t (Fox and
Hoch 2005; Gauri, Sudhir, and Talukdar 2008). There is also an
important distinction between short and long-term performance
since communication variables can differ signi?cantly in their
short and long-term effectiveness (Mela, Gupta, and Lehmann
1997).
We use the above framework as a roadmap for our synthesis
of literature and directions for further research with emphasis
in the following areas: trade promotions, consumer promotions,
communication and promotion through the newmedia, and bud-
get determination and allocation. Before doing so, we want to
reiterate the differences between manufacturer and retailer per-
spectives, which occur along three main dimensions: objectives,
tools, and outcome measures. As shown in Table 1, the manu-
facturer’s objectives are to maximize company, category and
brand pro?ts, while the retailer’s objectives are to maximize
chain, store, category, private label, and customer pro?ts. Man-
ufacturer tools include brand advertising, consumer and trade
promotions, public relations and sales force, whereas retailer
tools include store and private label advertising, feature adver-
tising, store coupons, and loyalty program. A manufacturer is
primarily interested in the performance of its brands, while the
retailer is more interested in its performance at the category and
the store levels (see van Heerde and Neslin 2008 for greater
44 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
Table 1
Differences between manufacturer and retailer perspectives on communication and promotion.
Dimension Manufacturer Retailer
Objective Maximize company, category and brand pro?ts Maximize corporate, chain, store, category, private label,
and customer pro?ts
Tools Brand advertising, consumer promotion, trade
promotion, sales force, public relations
Store and private label advertising, feature advertising,
store coupons, loyalty card, public relations
Outcome measures Sales, market share, margin, pro?t, ROI, brand
equity, shareholder value
Store traf?c, sales/square foot, store share, pro?t, store
satisfaction, share of wallet
details on manufacturer versus retailer perspectives in the con-
text of promotion effects).
Trade promotions
In the U.S. CPGindustry, trade promotions constitute approx-
imately 60% of the total marketing budget (Trade Promotion
Report 2005), and CPG companies spend more than $75 billion
on trade promotions annually (Drèze and Bell 2003). The mag-
nitude of this number becomes apparent when we compare it
with the total money spent on advertising, which is around $37
billion (Advertising Age 2007). The amount of money spent on
trade promotions demands that we understand the phenomenon
of trade promotion and evaluate its effectiveness.
Several analytical models of trade promotions exist in the
marketing literature, spanning more than two decades, that pro-
vide rich normative insights into why trade promotions exist, the
impact of retailer forward buying, and the brand, retailer, and
consumer factors that should in?uence retailer pass-through of
trade promotions. Until recently, however, empirical work was
limited to a small number of studies examining a small num-
ber of speci?c trade deals offered to a retailer (Armstrong 1991;
Chevalier and Curhan 1976; Curhan and Kopp 1987; Walters
1989).
The reasons for the paucity of empirical work on trade promo-
tions are twofold. First, trade promotions are often considered
by managers as a “cost of doing business,” (Kopp and Greyser
1987) which leads them to not consider it as worthy of investi-
gation. Second, trade promotion data are notoriously hard to
collect, as companies consider trade promotion strategies as
trade secrets and therefore, are unwilling to share them with
researchers. However, the last few years have seen an upsurge
in empirical work on trade promotions and their pass-through
and have provided some important lessons, which we summarize
below.
Different types of trade promotion funds
Until the early nineties, trade promotion funds were largely
in the form of off-invoice discounts for speci?c items in spe-
ci?c time periods. Since then, however, manufacturers have been
moving towards “pay for performance” deals which include bill-
backs and scan-backs but also lump sumcooperative advertising
allowances and development funds (see Cannondale Associates
1996 versus 2000). This move was driven largely by the need
to curb forward buying by retailers. Retailers are likely to pre-
fer unconditional discounts (see Drèze and Bell 2003 for an
analytical proof) while manufacturers prefer deals linked to per-
formance (e.g., price reductions, non-price support, and sales
volume). Gomez, Rao, andMcLaughlin(2007) report that accru-
als, scan-backs, and bill-backs account for over 60% of the total
trade promotion budget, while off-invoice allowances account
for 25.9%. They also ?nd that the relative market power of
retailers versus manufacturers in?uences the size of the bud-
get and the percentage allocated to pay-for-performance versus
off-invoice deals. For instance, the manufacturer’s total bud-
get is lower when it has strong equity as measured by its price
premium. In contrast, the total budget is higher and a greater
portion of that budget is allocated to off-invoice deals for high
sales retailers. The major implication of these different types
of funds is that they are not tied to speci?c items and speci?c
time periods, so both analytical and empirical models need to
account for the fact that weekly changes in per unit wholesale
versus retail prices of individual items or brands may no longer
be the best way to represent pass-through.
Individual versus aggregate pass-through
Empirical research shows that the median pass-through rate
for a manufacturer is less than 100%. There is convergent valid-
ityfor a medianrate of 65–75%across studies byBesanko, Dubé,
and Gupta (2005), Pauwels (2007), and Ailawadi and Harlam
(forthcoming). However, this rate does not necessarily mean
that the retailer pockets the rest of the trade promotion funding.
Ailawadi and Harlam (forthcoming) report that, in aggregate,
promotion spending by the retailer in their study is more than
100% of the total trade promotion funding it receives. Indeed,
the distribution of individual pass-through rates is positively
skewed; most manufacturers receive pass-throughs well below
100%, but a small number enjoy pass-through rates much greater
than 100% and some manufacturers even receive promotion
spending without providing any funding.
Variations in pass-through across categories and
manufacturers
Retailers pass through a larger percentage of trade promo-
tion funds obtained from high share manufacturers. This result
is supported by all three studies on pass-through. Higher priced
manufacturers and larger categories also get higher pass-through
(Ailawadi andHarlamforthcoming; Pauwels 2007). There is less
convergence among the studies on whether retailer pass-through
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 45
for private labels is higher or lower than for national brands.
Besanko, Dubé, and Gupta (2005) report that pass-through is
lower for private label while Ailawadi andHarlam(forthcoming)
?nd that it is higher. Pauwels’ (2007) result is directionally con-
sistent with Ailawadi and Harlam, but the effect falls short of
signi?cance.
Cross pass-through
Analytical models of retailer decisions that are based on
category pro?t maximization suggest that cross pass-through
should exist, that is, trade promotions from one manufacturer
in a given period (often a week) should in?uence the extent
to which the retailer promotes another manufacturer’s brand in
the same period (e.g., Moorthy 2005). Empirically, however,
there is some controversy about the existence of this type of
cross pass-through. Besanko, Dubé, and Gupta (2005) document
both positive and negative cross pass-throughs, and Pauwels
(2007) reports positive cross pass-through for large brands
and negative cross pass-through for small brands. However,
McAlister (2007) refutes the existence of cross pass-through,
showingthat the number of signi?cant cross pass-througheffects
drops signi?cantly when some pooling issues in the study by
Besanko, Dubé, and Gupta (2005) are addressed. In a rejoinder,
Dubé and Gupta (2008) agree but show that allowing for cross
effects does improve overall ?t in various model speci?cations
and thus conclude that the phenomenon exists. Ailawadi and
Harlam (forthcoming), who use actual funding and promotion
spending data to compute pass-through instead of estimating
it from wholesale and retail price changes, ?nd strong evi-
dence for cross-subsidization of promotions – funding received
from manufacturers in a category is used to subsidize pri-
vate label promotions as well as promotions in other, vastly
different categories. However, they do not ?nd a signi?cant
effect of funding from one manufacturer on pass-through for
another manufacturer in the same period and the retailer deci-
sion making process they report supports McAlister’s (2007)
view that weekly cross-brand pass-through is not prevalent or
practical.
Accounting and audit issues
Although academics assume that the amount of money spent
by manufacturers on trade promotions and the amount passed
through by retailers is clear-cut and unambiguous, this is often
not the case in practice. An in-depth study of problems and
best practices in trade promotion accounting (Parvatiyar et al.
2005) reveals that trade promotions are oftennegotiatedverbally,
particularly by smaller players, and record keeping of trade pro-
motions is notoriously inadequate, leading to errors in reporting
and accounting for trade promotions. Retailers often fail to claim
the trade promotion funds they were offered; vendor invoices
sometimes do not re?ect the deals agreed up on; retailers may
mistakenly claim a trade deal more than once. This has led to
the development of a multibillion dollar post-auditing industry
whose function is to discover and try to recover ‘lost’ money for
retailers.
The process of discovering, investigating, con?rming, and
resolving a post-audit recovery claim involves not only the
post-auditors, but the sales and marketing personnel as well as
accounting departments at both the retailer and vendor ?rms. It
often strains relationships between the vendor ?rmand the retail
?rm, as well as between the accounting and sales/marketing per-
sonnel within each ?rm. While the retail buyer and the vendor
salesperson want to maintain a positive relationship, the post-
audit activity and the process of verifying each other’s claims
strains their relationships. And, while accounting personnel look
at post-audit activity as legitimate revenue generation activity,
the marketing and sales personnel view it as a diversion from
their main function. In summary, trade promotions lead to errors,
errors lead to post-audit activity and post-audit activity strains
relationships, especially when it takes place after a signi?cant
delay.
When a claim is resolved the vendor ?rm and the retail ?rm
have to adjust their accounting books. Adjustments are nowesti-
mated to be about 1% of annual sales and may occur as late
as 12–24 months after the transaction (Parvatiyar et al. 2005).
This practice raises ethical and legal questions. The industry is
worried that it may trigger a violation of the Sarbanes/Oxley
act because accounting books need to be adjusted after they
have been initially certi?ed. While the retail industry is acutely
aware of this situation, there is no academic research on these
institutional accounting, auditing, and legal aspects of trade pro-
motions.
Another important aspect of trade promotions has to do with
how promotion spending is treated in ?nancial statements. In
late 2001, new rules developed by the Financial Accounting
Standards Board (FASB) went into effect, whereby companies
are required to deduct price discounts given to retailers and
consumers from revenue rather than reporting them as mar-
keting expenses (Schultz 2002). This was expected to reduce
CPG companies’ promotion spending in the form of price
discounts (e.g., off-invoice and bill-back discounts to retail-
ers, coupons to consumers). However, since the FASB rules
make a distinction between pure price discounts and other
promotion spending such as payments for co-op advertising
and in-store events, it was also expected that CPG ?rms’
would shift more spending towards “shopper marketing” (Neff
2002), a term that has been recently coined to represent mar-
keting activities that can in?uence consumer behavior at the
point of purchase in the store. These accounting rule changes
have justi?ably attracted plenty of attention in the business
press, but academic research on its implications has been
scarce.
Future research directions
The above review suggests several directions for further
research. First, we need to account for different types of trade
promotion funding in empirical analyses of trade promotion and
study the allocation decisions, pass-through, and performance of
these different types. Because the new FASB accounting rules
for promotional spending are likely to have had an effect on not
only the total trade promotion spending by CPG companies but
46 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
also on the mix of different types of funding, research is also
warranted on their impact.
Second, it is important to study variations in budgeting and
pass-through across manufacturers and across retailers given
that the characteristics of both the parties determine these deci-
sions. What manufacturer and retailer characteristics are more
in?uential in determining pass-through rates? How can retail-
ers better manage pass through rates? Retailers pass-through
more of high share manufacturers’ funding, but is this an opti-
mal strategy? After all, high share products have higher baseline
sales, which can make promotions less pro?table for retailers
(McAlister 1986; Tellis and Zufryden 1995; van Heerde and
Neslin 2008).
Third, irrespective of whether retailers currently engage in
cross pass-through or not, research is needed to determine
whether it would be an optimal strategy, not just from a weekly
category pro?t maximization viewpoint (e.g., Moorthy 2005),
but also after accounting for its operational complexity and its
potential negative impact on manufacturer–retailer relationships
and future trade promotion funding.
Fourth, analytical and structural models of these decisions
need to incorporate the changed institutional reality of howtrade
promotions are designed, negotiated, and passed through. They
also need to formalize the role of the relative bargaining power
of manufacturers and retailers, which appears to be a central
factor in the amount and type of trade promotions funding as
well as in the extent of pass-through.
Fifth, we need to distinguish between regular price changes
and promotions in empirical and analytical models of pass-
through because both consumer response and managerial
decision-making are different for the two decisions (e.g., Dubé
and Gupta 2008; McAlister 2008; Shankar and Krishnamurthi
1996). Sixth, the focus of empirical research has been on the
retailer’s pass-through in the formof price promotions. But, non-
price merchandising support variables such as displays, shelf
talkers, and extra shelf space are also important to manufactur-
ers. Future research should study the impact of manufacturer
funding on such non-price support activities of their brands by
retailers.
Finally, there is a sore need for research on the impact of trade
promotions negotiations and post-audit activity on the relation-
ships between manufacturers and retailers. Justice theory and
equity theory in an agency framework are potential avenues
to investigate these issues. This area is also interesting as it
involves cross functional relationships. The marketing, sales,
purchase, accounting, and ?nance departments of vendor and
retail organizations are involved in trade promotion activities,
whereas research on trade promotions has largely ignored the
involvement of ?nance and accounting functional areas.
Consumer promotions
Consumer promotions are an important element of competi-
tive dynamics in retail markets with retailers using a myriad of
promotion techniques to attract consumers. Some of the most
commonly used techniques are the typical price promotions,
“loss leader” promotions (deep discount deals), feature adver-
tising (store ?yers), and in-store displays. According to the
Promotion Marketing Association, the total promotion spending
across all product categories in the USA reached $429 billion
(about 3.65% of the GDP) in 2004. Given the widespread use
of retail promotions and the magnitude of the dollars spent on
them, managers and academicians have a great interest in under-
standing how consumers react to such promotions and how that
affects retailers’ performance (Bodapati 1999; Raghubir, Inman,
and Grande 2004). We summarize belowsome of the most recent
empirical ?ndings in the promotions area as they relate to retailer
decision making and performance.
The sales promotion bump and its decomposition
The immediate increase in a promoted item’s sales when it
is put on promotion is substantial. Meta-analyses by Bijmolt,
van Heerde, and Pieters (2005) and Pan and Shankar (2008)
put the average short-term promotional price elasticity at ?2.62
and ?2.55, respectively. Of course, the entire promotional sales
bump is not incremental either for the retailer or for the man-
ufacturer whose product is being promoted. Beginning with
Gupta (1988), much attention has been paid to decomposing
this sales bump. Recent years have seen a renewed emphasis on
this subject as researchers have moved from decomposition of
promotion elasticity (e.g., Gupta 1988) to decomposition of unit
sales (e.g., van Heerde, Gupta, and Wittink 2003). One major
empirical ?nding from van Heerde and colleagues is that the
brandswitchingfractionof the promotionis signi?cantlysmaller
than previously thought. The estimates of brand switching com-
ponent in studies published after 2002 are around 30–45% (e.g.,
Sun 2005; Sun, Neslin, and Narasimhan 2003; van Heerde,
Gupta, and Wittink 2003; van Heerde, Lee?ang, and Wittink
2004), versus earlier estimates of around 80%(e.g., Bell, Chiang
and Padmanabhan 1999; Chiang 1991; Chintagunta 1993; Gupta
1988). van Heerde and Neslin 2008 provide a good discussion of
the methodological reasons for this downward trend in estimates
of the brand switching fraction.
Almost all of this research takes the manufacturer’s perspec-
tive in decomposing the sales bump. However, as discussed by
van Heerde and Gupta (2006), Ailawadi et al. (2006), and van
Heerde and Neslin (2008), the components of the promotional
bump that are incremental for the retailer and are quite differ-
ent from the ones that are incremental for the manufacturer. In
particular, while both parties bene?t from promotion induced
increases in consumption, manufacturers do not bene?t from
store-switching and retailers do not bene?t from brand switch-
ing (unless, of course, there are margin differences). Using data
from the U.S. drug store chain CVS, Ailawadi et al. (2006) esti-
mate the promotion bump and decompose it from the retailer’s
perspective. They ?nd that, on average, 45% of the bump is
due to switching within the store, 10% is due to accelerating
or “pulling forward” future purchases in the store, and 45% is
incremental sales for the retailer.
“Halo” and store-traf?c effects of promotion
A retailer hopes that promotions not only increase sales of
the promoted items but also attract more consumers into the
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 47
store because, once consumers are in the store, they are likely to
also buy products other than those on promotion. Ailawadi et al.
(2006) provide some insights into the ability of promotions in
one category to in?uence sales in other categories in the store.
They ?nd that, on average, there is a signi?cant positive ‘halo
effect’ of promotions – for every unit of gross promotion lift,
0.16 unit of some other product is purchased elsewhere in the
store.
One particularly popular strategy used by retailers is the
“loss leader” promotion strategy (Drèze 1995; Walters and
MacKenzie 1988), which assumes that promotions on some
products are particularly effective in driving store traf?c. The
loss leader strategy is distinct from other retailer price promo-
tion strategies in that the prices for the selected loss leader items
are set at or below retailers’ respective marginal costs. Retail-
ers consciously incur loss or earn no pro?t on these items, in
the hope that deep discounts on the loss leaders will lead to
increased store traf?c, and, since there are economies of scale
in shopping, once at the store, customers will buy other items in
addition to the loss leaders. So, the expectation from theoreti-
cal models is that the negative contribution from the loss-leader
items bought by the customers will be more than offset by the
pro?t generated from the sale of non-loss-leader items to them
(Bliss and Christopher 1988; Hess and Gerstner 1987; Lal and
Matutes 1994; Rao and Syam 2001).
However, empirical evidence for the effectiveness of loss
leader promotions is limited. Walters and Rinne (1986) showed
that certain portfolios of products promoted as loss leaders have
a greater impact on store traf?c, store sales and deal sales than
other product portfolios, with no signi?cant impact on retailer
pro?ts. Walters and MacKenzie (1988) also found a signi?cant
impact of loss leaders on store traf?c and store sales, but only
two (out of eight) of their categories had signi?cant effects on
store pro?ts – one positive and one negative. Both studies use
fairly simple models with a dummy variable for loss leaders.
Gauri, Talukdar, and Ratchford (2008) conduct a more
sophisticated econometric analysis that accounts for the breadth
and depth of loss leader promotions, using scanner data from 24
stores. They ?nd that loss leader promotions not only increase
store traf?c and average spending, but they also lead to higher
net pro?t contribution for the promoting stores. In fact, they
?nd that there are marked differences across product categories
in their relative effectiveness as loss leaders in boosting store
pro?t stores could generate more pro?ts from if they chose loss
leader categories optimally. In sum, the empirical evidence that
exists does suggest that loss leader promotions are effective.
Consumer price search behavior
To evaluate the impact of price promotions on store per-
formance and to determine whether or not the promotions are
attracting pro?table consumers, a retailer needs to understand
how different consumers respond to price promotions. Con-
sumers may search for deals along both the spatial (across stores)
and temporal dimensions (across time). Several papers have
studiedspatial price searchingrocerymarkets usingeither actual
purchase or survey data (e.g., Carlson and Gieseke 1983; Fox
and Hoch 2005; Putrevu and Ratchford 1997), and a parallel
empirical literature has focused on the temporal dimension of
search, investigating consumer response to promotions through
stockpiling, purchase acceleration and purchase delays (e.g.,
Mela, Jedidi, andBowman1998; Neslin, Henderson, andQuelch
1985).
Gauri, Sudhir, and Talukdar (2008) consider the effect of
both spatial and temporal dimensions of price search on the
pro?tability of price promotions. Gauri and colleagues ?nd that
households that claim to search spatio-temporally avail about
75% of the available savings on average, while those that claim
not to systematically search on either dimension avail about 50%
of the available savings. This suggests that “cherry pickers” do
not get much more in savings than non-cherry pickers. As far as
the size and pro?t impact of the cherry-picking segment is con-
cerned, Fox and Hoch (2005) characterize approximately 8%
of the households in their sample as cherry pickers and show
that these households selectively use secondary stores on cherry
picking trips to disproportionately purchase promoted items.
Talukdar, Gauri, and Grewal (2008) ?nd that on an average only
about 1.5% of households contribute a net negative pro?t to the
store over a 1-year period and extreme cherry picking behavior
gets manifested only with respect to the secondary stores of the
consumers. They also ?nd that an inverse-U relationship exists
between consumers’ opportunity cost of cross-store price search
and their likelihood of exhibiting ECP behavior. In summary, it
appears that neither the size of the cherry picking segment nor
its negative impact on retailer pro?ts is as high as is generally
believed.
Short term and long-term impact of promotions
As noted earlier, Ailawadi et al. (2006) ?nd that, on average
45% of the promotion bump is incremental for the retailer in
their study. However, they also ?nd that, once costs and reduced
promotional margins are taken into account, over 50% of pro-
motions are not pro?table for the retailer. Across 460 product
categories over a 4-year period, Nijs et al. (2001) ?nd that in
58% of the cases there is a positive effect of promotions on
category sales (increases in category sales should bene?t both
manufacturers and retailers). Srinivasan et al. (2004) also ?nd
that though promotions have a predominantly positive impact
on manufacturer revenues, their impact on retailer revenue and
margin is mixed, even after accounting for cross-category and
store-traf?c effects. In particular, they report that retailer rev-
enue elasticities are higher for brands with frequent and shallow
promotions, for impulse products, and in categories with a low
degree of brand proliferation. And retailer margin elasticities
are higher for promotions of small-share brands and for brands
with infrequent and shallow promotions. Overall, therefore, not
all promotions have a positive revenue impact for retailers, and
the pro?t impact, in the few cases where it has been studied, is
decidedly mixed.
As far as long-term effects of promotions are concerned,
much of the work has been done from the manufacturer’s per-
spective. Mela, Gupta, and Lehmann (1997) ?nd that consumers
become more price and promotion sensitive in their brand choice
48 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
decisions over time because of reducedadvertisingandincreased
promotions. Mela, Jedidi, and Bowman (1998) conclude that the
increased long-term exposure of households to promotions has
increased their tendency to “lie in wait” for especially good pro-
motions. Kopalle, Mela, and Marsh (1999) ?nd that increased
promotions have three negative dynamic effects – reduce base-
line sales, increase price sensitivity, and diminish the ability of
the promoted brand to take share from competitors. Substantial
evidence has been accumulated using time series VARX mod-
els that promotions have no “permanent” effects (e.g., Pauwels,
Hanssens, and Siddarth 2002; Steenkamp et al. 2005).
There is less research on the long-term effects of promotions
from the retailer’s perspective, but the few studies on this issue
showthat they are not signi?cant. For instance, Nijs et al. (2001)
?nd that in 98% of the cases there is no permanent effect of pro-
motions on category sales. Consistent with this result, Srinivasan
et al. (2004) ?nd that there are no permanent effects of promotion
on either the revenue or margin of retailers.
Effects of different types of promotions
The vast majority of research on promotions involves price
promotions with or without accompanying features or displays.
We now have a fairly good understanding of the magnitude of
price promotion elasticities, with and without features and dis-
plays (e.g., Bijmolt, van Heerde, and Pieters 2005; Narasimhan,
Neslin, and Sen 1996; Pan and Shankar 2008). The consensus
is that elasticities can increase several fold in the presence of
features and/or displays.
There is some newworkonthe effectiveness of various design
elements of retailers’ weekly promotional ?yers. Gijsbrechts,
Campo, and Goossens (2003) examine howcomposition charac-
teristics of the ?yer affect store traf?c and sales. Not surprisingly,
they ?nd that ?yers featuring deeper discounts are more effective
in driving traf?c and sales. They also show that total ?yer size
does not seem to matter, but ?yers featuring a larger proportion
of food and private label promotions, and ?yers featuring spe-
cialty categories like wines and delicatessen on the cover page
are more effective in generating store traf?c and store sales.
Pieters, Wedel, and Zhang (2007) use eye-tracking technol-
ogy to understand how attention to the ads on a ?yer page is
affected by the surface size of ?ve design elements – brand,
text, pictorial, price, and promotion. They ?nd that the total sur-
face size of a feature ad has a strong effect on attention, the
size of the pictorial element has the largest effect and the size
of the text element has little to no effect. They also present a
method for optimizing these design elements and ?nd that the
optimal layout differs for manufacturer brands, private label, and
unbranded products. In particular, the pictorial, price, and brand
elements should be most prominent for the ?rst; price and brand
elements should be most prominent for the second; and price
and pictorial elements should be most prominent for the third.
Thus, new research is providing some useful guidelines for how
retailers should design their weekly store ?yers.
There has also been some interesting work on the effec-
tiveness of different types of promotions such as promotions
with quantity limits, multiple unit promotions, and bonus packs.
Inman, Peter, and Raghubir (1997) ?nd that the presence of a
restriction (e.g., purchase limit, purchase precondition, or time
limit) serves to accentuate deal value and acts as a “promoter”
of promotions. Across four studies, they demonstrate the robust-
ness of a “restriction effect” whereby more stringent restrictions
are effective at signaling value, thereby increasing the restricted
brand’s choice probability. Wansink, Hoch, and Kent (1998)
examine quantity limits froma different perspective. They focus
on consumers’ purchase quantity decision and the psychological
process underlying it. Across ?ve studies, they ?nd evidence of
an anchoring and adjustment effect whereby average purchase
quantity increases in the presence of a quantity limit. Manning
and Sprott (2007) study the effect of multiple unit price promo-
tions (e.g., 2 for $2; 8 for $8) on consumers’ quantity purchase
intentions. They ?nd a positive effect only when the multiple
quantity anchor speci?ed is high (e.g., 8 or 20, not 2 or 4), sug-
gesting that the anchoring works but only at high levels, and
only for frequently consumed products.
In sum, there are important behavioral mechanisms at play in
limit and multiple unit promotions, with contingency effects that
need more study. Furthermore, these papers have, to some extent
found evidence of opposing effects. On the one hand, Inman et
al. (1997) suggest that purchase incidence declines as the quan-
tity limit increases. On the other hand, Wansink et al. suggest
that average purchase quantity increases with the limit. Because
total sales equal the number of shoppers buying the brand times
the average purchase quantity per shopper, further research is
needed to determine the shape of the unit sales-quantity limit
relationship.
Finally, Hardesty and Bearden (2003), using three exper-
imental studies, investigate the effects of promotion price
discounts relative to those of bonus packs across promotional
bene?t levels. Their results suggest that price discounts and
bonus packs are valued similarly for both low and moderate
promotional bene?t levels, but price discounts are preferred to
bonus packs when promotional bene?t levels are high.
Promotion framing
A large body of behavioral research demonstrates that the
manner in which a deal is framed in?uences consumer per-
ception of the deal value, purchase intent, and search intent.
Framing refers to how the deal price is communicated to the
consumer, for example, whether an external reference price is
provided, whether the deal is in dollar or percentage terms, and
whether prices of competing products or other contextual infor-
mation are provided. The major implication from this research
stream for retailers is that deals should be carefully framed
because small modi?cations in wording and the information
provided can have a signi?cant impact on the effectiveness and
ef?ciency of the deal. While it is beyond the scope of this arti-
cle to report on the ?ndings of individual articles, we wish
to highlight two meta-analyses on the subject. Compeau and
Grewal’s (1998) meta-analysis concludes that the mere pres-
ence of an advertised reference price increases the consumer’s
internal reference price and the perceived value of the deal and
reduces their intentions to search for a better deal. They also ?nd
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 49
that these effects are stronger for higher advertised reference
prices.
Krishna et al.’s (2002) meta-analysis offers interesting
insights into the impact of multiple factors on perceived deal
savings. They ?nd that among deal characteristics, (a) the deal
percentage increases perceived savings over and above the dol-
lar amount of the deal; (b) the more the savings on a bundle
of items over and above savings on individual items, the higher
the perceived savings; and (c) the more the number of items
in the bundle, the smaller the perceived savings. Further, they
?nd that among situational factors, perceived savings are higher
when (a) the deal is included in an advertisement; (b) it is on a
national brand relative to a private label or generic brand; and
(c) when it is offered by a specialty store or supermarket relative
to a discount or department store. Finally, they ?nd that among
price presentation factors, (a) small plausible deals increase per-
ceived savings more than large, implausible deals; (b) using
regular price as an external reference price increases perceived
savings although the presence of an MSRP (manufacturer sug-
gested retail price) does not; (c) objective deals (with speci?c
savings) increase perceived savings more than tensile ones (sav-
ings of x% or more); and (d) a within-store frame (current price
vs. regular price) is more effective than a between-store frame
(own price vs. competing store’s price).
Price promotion coordination
Pricing and promotion are often studied almost in isolation
of each other. Indeed, pricing and promotion decisions are made
by different managers in different departments in some retail
chains. This practice increases the possibility of sub-optimal
decisions on both fronts. Work by Bolton and Shankar (2003),
Shankar and Bolton (2004) and Bolton, Montoya, and Shankar
(2007) show the nature and extent of the relationships between
retailer pricing and promotion decisions that have useful impli-
cations for retailer promotion strategy.
Bolton and Shankar (2003) showthat retailers practice a num-
ber of price-promotional strategies beyondthe commonlyknown
Hi-Lopricingandeverydaylowpricing(EDLP) strategies. AHi-
Lo (EDLP) pricing strategy is typically associated with a higher
(lower) deal elasticity but a lower (higher) regular price elas-
ticity (Shankar and Krishnamurthi 1996). Bolton and Shankar
(2003) ?nd that retailer pricing and promotion strategies are
based on combinations of four underlying dimensions: relative
price, price variation, deal intensity and deal support and that
at the brand-store level, retailers practice ?ve pricing strategies:
exclusive, moderately promotional, Hi-Lo, EDLP, and aggres-
sive pricing strategies. Their results also show that the most
prevalent pricing strategy is characterized by average relative
brand price, low price variation, medium promotion intensity,
and medium deal support. Shankar and Bolton (2004) ?nd that
competitor factors such as frequency of promotions and price
level, retail chain factors such as size and positioning and cat-
egory factors such as storability and necessity explain most of
the variance in retailers’ price promotion coordination decisions.
Among these, competitor factors explain the bulk (62%) of the
variation in retailer price promotion coordination.
Bolton, Montoya, andShankar (2007) argue that price promo-
tion coordination is a key driver of retailer pro?tability. Retailers
need to better coordinate the prices and promotions of brands not
only within a category, but also across categories. Furthermore,
retailers should coordinate prices and promotions across differ-
ent shopping formats. For example, a retailer such as Wal-Mart
may have regular Wal-Mart, Wal-Mart supercenter, and Neigh-
borhood Markets stores not too far from one another. They can
improve their corporate pro?ts by planning and coordinating
the prices and promotions across brands, categories and store
formats. Gauri, Trivedi, and Grewal (2008) emphasize that the
price promotion strategy (EDLP, HiLo and Hybrid) and format
strategy (Supermarket, Supercenter and Limited Assortment)
are two key elements of the overall retail strategy of the stores.
They consider both these strategies in a single framework and
?nd that consideration of any one strategy in isolation fails to
depict a complete picture, and the strategic implications change
signi?cantly when both the price promotion and format strate-
gies are studied in combination. Taken together, the studies on
pricing and promotion suggest that retailers can improve the
effectiveness of promotions by coordinating them with pricing
decisions. They can use the knowledge and understanding of
the determinants of price promotion strategy and coordination
to improve their pro?tability.
National brand vs. private label promotions
National brands and private labels may differ in promo-
tion effectiveness and the differences in their effectiveness
have important implications for retailer promotion strategy. The
effects of promotions of a national brand and private label/store
brand on the sales of each other are asymmetric. When high-
price tier brands promote, theydrawmore shoppers fromusers of
low-price tier brands than vice versa (Blattberg and Wisneswki
1989). Extending this logic to national and store brands, which
typically are in high-price tier and low-price tier, respectively,
we can conclude that promotions of national brands are more
effective than those of store brands.
Indeed, much analytical work suggests that private labels
should not be promoted (see Sethuraman 2006), but empiri-
cal evidence suggests that retailers do promote private label
(Shankar and Krishnamurthi 2008). The ?ndings of Ailawadi
et al. (2006) provide one explanation for this practice – even
though the unit sales impact of promotion is smaller for pri-
vate labels than for national brands, the pro?t impact may be
higher for private labels due to the higher retail margins on pri-
vate labels. Shankar and Krishnamurthi (2008) develop a model
of optimal retailer decisions on regular price, deal depth, and
frequency of deals for both national and store brands under
the goal of category pro?t maximization based on store level
data for stores with two different pricing policy/format posi-
tioning, EDLP and Hi-Lo. Their analytical and empirical results
show that large national brands should be regular priced highest
and promoted less often with shallow deal discounts relative to
other brands within each EDLP and Hi-Lo store; small national
brands should be regular priced at a moderate level and pro-
moted at a moderate (high) frequency relative to other brands
50 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
with deeper discounts than large national brands within each
EDLP (Hi-Lo) store; and store brands should be regular priced
lowest and promoted at a low-moderate (high) frequency with
deep (low-moderate) discounts within each EDLP(Hi-Lo) store.
Future research directions
As discussed earlier, much of the work on decomposing the
sales bump takes the perspective of the manufacturer. More
research is needed from the retailer’s perspective. This work
should be done for different retail formats and for different types
of promotions.
Despite the importance of studying the pro?t impact of pro-
motions, due to lack of publicly available cost data, most of the
past empirical work has focused on the volume impact of pro-
motions. The few recent studies that have considered the pro?t
impact of promotions show that it can be quite different from
sales impact, so more research is needed in this area.
The effectiveness of promotions of national brands has
been extensively studied. More research, however, is needed
to understand the motivations for private label promotions and
their effectiveness. Promotional pass-through decisions for store
brands is one topic on which not much is known. Further-
more, channel blurring—the phenomenon in which consumers
are moving their purchases of a product category from chan-
nels traditionally associated with that category (e.g., grocery) to
alternative channels (e.g., mass, club, extreme value/dollar) and
in which retailers from one channel are selling items tradition-
ally associated with other channels (Luchs, Inman, and Shankar
2007)—is reorienting the promotional landscape as store and
channel switching are becoming important consequences of pro-
motion.
Another area in which future research would be useful is the
performance impact of loss leader promotions across categories,
SKUs and brands. More research is needed to identify the most
effective loss leader brands and categories fromthe point of view
of driving not just store traf?c and sales, but also store pro?t.
It would also be interesting to explore the existence of possible
asymmetric effects at various levels, for example, loss leader
promotions on soda may affect chips sales more than the chips
sales affect soda category (e.g., Bezawada et al. forthcoming).
More work is needed to identify win–win promotions for
both manufacturers and retailers. The extent to which promotion
increases category consumption is bene?cial for both parties
and we now have a good understanding of how to model the
impact of promotion on consumption (e.g., Ailawadi and Neslin
1998) and also how this effect varies across categories (e.g.,
Bell, Chiang, Padmanabhan 1999; Nijs et al. 2001). However,
we also need to bring together the divergent perspectives of the
manufacturer and the retailer on the brand versus store issue.
A promising area of work is the effort to link brand equity
to store equity. Chien, George, and McAlister (2001) provide
a useful conceptual framework and methodology for identify-
ing brands that attract a retailer’s most valuable customers, and
McAlister, George, and Chien (2008) examine the pro?tability
of consumers attracted to promotions of different brands. Not
only does such research try to bring together manufacturer and
retailer perspectives, it makes an important move from brand
and category pro?t to store and customer pro?t.
More research is needed on the value of jointly coordinating
price and promotion and on decision models which facilitate
price promotion coordination, especially with the emergence
of shopper marketing. Shopper marketing is getting signi?cant
attention in the business press as both manufacturers and retail-
ers recognize the importance of in?uences during what senior
marketers at P&G have called “the ?rst moment of truth.” As
manufacturers work with retailers to in?uence the consumer’s
experience at the ?rst moment of truth, they must develop
win–win shopper marketing strategies with retailers. This is
an opportune time for researchers to review the different shop-
per marketing strategies that are being tested and evaluate their
effectiveness. New technologies such as RFIDs, cameras, and
videos on shopping carts and in other locations in the store offer
strong potential to study shopper marketing in great detail.
Shopper marketing includes activities such as in-store layout,
aisle and display management strategies. These activities have
important effects on the sales of items in a store. Bezawada et al.
(forthcoming) showthat the cross-category effects of aisle place-
ment are asymmetric across categories. In an empirical analysis
of aisle and display placements of beverages and salty snacks,
they ?nd that the salty snacks have a greater effect on the sales
of carbonated beverages than vice versa. Research on shopper
marketing is still in its infancy and more studies are needed to
more accurately assess its impact on consumer purchases.
Additional research that directly connects consumer shop-
ping, price search, and deal response behavior to the
effectiveness of promotions for the retailer is needed. For exam-
ple, the insights gained from analysis of cherry picking patterns
across stores would be useful in developing a structural model
of store competition that accounts for the fact that consumers
choose stores on the basis of their baskets of purchases and
can choose from either inter-temporal or cross-store cherry
picking patterns. As another instance, researchers have stud-
ied how consumers respond to different types of promotions,
the behavioral mechanisms that might underlie their response,
and the contingencies under which some promotion designs
are more effective than others. A review article that pulls
together these consumer-level learnings and provides an integra-
tive framework for conceptualizing different promotion types
and their effects would be helpful to retailers and researchers
alike.
Communication and promotion through the new media
New/unmeasured media such as the Web, email, blog, video,
other social media, and mobile continue grow in usage and
popularity, but not much is known about their effectiveness,
making allocation to such media an important but challeng-
ing task (Shankar and Hollinger 2007). Although most CPG
manufacturers still spend the vast majority of their marketing
budgets on traditional media, their allocation to new media is
steadily increasing. For example, Procter & Gamble, the lead-
ing consumer goods marketing spender, hiked its spending on
unmeasured media in 2006 by roughly 15%over 2005 compared
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 51
to an increase of only 3.9%in measured media in the same period
(Advertising Age 2007). The media mix for its major brands now
includes greater allocation to in-store (shopper marketing), the
Internet, and other unmeasured media (Tode 2007).
Retailer implications of new media
From a retailer standpoint, manufacturer reallocation toward
new media has important implications. First, the money allo-
cated to trade and consumer promotions may change from the
past. Second, greater investments in shopper marketing means
stronger retailer focus on in-store decisions. Third, many online
retailers need to coordinate their newmedia promotion decisions
with those of the relevant manufacturers.
Retailers themselves have started to use the new media in
different ways. Many retailers use email extensively to alert
shoppers about new products, promotions, and store openings.
Some even offer coupons for downloading at their web sites.
For example, Kroger allows a shopper to go to its Web site
(http://shortcuts.com/?promo=kroger) and download manufac-
turer coupons onto her/his loyalty card, saving the need to
identify and clip coupons. These coupons will be automati-
cally redeemed when the shopper checks the relevant items out
with her/his loyalty card at a Kroger store. Other retailers are
using different forms of social media (Bustos 2008). American
Eagle has Facebook applications, while retailers like Wal-Mart
and Target have Facebook sponsored groups. Urban out?tters
has MySpace pages, 1-800-Flowers has second life e-stores,
Buy.com, Radioshack, and Overstock.com have Youtube/Video
podcasts, and Of?cemax, Burger King and Taco Bell have viral
micro sites.
A study of 300 Internet and multichannel retailers revealed
that the growth in consumer usage of the new media witnessed
a shift in allocation of efforts from the ubiquitous free ship-
ping promotion to more personalized promotions and live chat
(Webtrends 2006). Retailers surveyed by the study ranked e-mail
marketing as the most important demand-generation activity for
holidaysuccess, followedbysearchengine marketingandsearch
engine optimization.
Research on retailer efforts in the new media is limited, but
substantial work has been done on consumer purchase behav-
ior online versus of?ine. It shows that online shoppers are more
convenience-conscious (Degeratu, Rangaswamy, and Wu 2000)
and more brand loyal than of?ine shoppers (Danaher, Wilson,
and Davis 2003; Shankar, Smith, and Rangaswamy 2003). They
are more price sensitive when there is inadequate non-price
information on the website (Degeratu et al. 2000). However, in
the presence of non-price information, for example, on brand,
quality, and product features, consumers are less price sensi-
tive online than of?ine (Alba et al. 1997; Lynch and Ariely
2000; Shankar, Rangaswamy, and Pusateri 2001). These dif-
ferences suggest that retailers should use different types of
price promotions online versus of?ine. The online medium also
offers greater potential for customized promotions targeted to
individual consumers (Kannan and Kopalle 2001). Zhang and
Krishnamurthi’s (2004) decision-support model for customiz-
ing online promotions provides recommendations on when, how
much, and to whom to promote and may signi?cantly improve
promotion effectiveness over current practice. Zhang and Wedel
(forthcoming) show that the incremental pay-off to manufac-
turers from offering individual-level customized promotions
relative to segment level or mass market level customized pro-
motions is small, especially in of?ine stores. However, they do
not consider the perspective of the retailer in their analysis, so
we do not know whether personalized online promotions offer
retailer bene?ts such as improved customer loyalty or greater
store traf?c.
Future research directions
Given the nascent and growing newmedia landscape, a num-
ber of research questions remain unanswered. First, how do
the effects of communication and promotion differ between the
traditional and the new media? Shankar and Hollinger (2007)
suggest that traditional media communication is largely intru-
sive, whereas communication and promotion through the new
media needs to be more non-intrusive or user-demanded. This
argument suggests that promotion through the new media is
likely to be more effective than that through the traditional
media. However, several challenges, including measurement
issues, audience reach, and content of promotion relating to the
social media remain (Winer forthcoming).
Second, how should retailers formulate their Internet promo-
tion strategy? Given that consumers increasingly use multiple
channels (Kushwaha and Shankar 2008), how should retailers
communicate and promote to consumers? Should a retailer fea-
ture the local weekly promotions on its Web site and proactively
email its consumers in its opt-in email list? While this strategy
may get the consumers to visit the store often, it might also
highlight and offer more discounts to the loyal shoppers, who
would have otherwise bought the items at regular prices. Care-
ful empirical analysis is needed to answer these questions. The
online medium also opens other promotional avenues for retail-
ers such as electronic coupons and deal forums (Gopal et al.
2006). More research is needed to guide retailers on whether,
when, and how to best exploit these opportunities.
Third, retailers and manufacturers need better models of
relative allocation of marketing budget toward traditional and
new media. Such models should incorporate interaction effects
between the two types of media and the different media vehicles
that constitute these media.
Fourth, howshould retailers leverage the social media promo-
tion efforts of brand manufacturers? Many brand manufacturers
have their own social media that include community sites, corpo-
rate blogs and video sites. How can a retailer bene?t from these
efforts? An average retailer deals with hundreds of brand man-
ufacturers or suppliers, so with which manufacturers should a
retailers partner on its social media efforts? Research addressing
these questions would be useful to academics and practitioners
alike.
Fifth, should retailers set up their own social networks? If so,
what should their strategy be and how should they coordinate or
manage the network? How should they allocate their marketing
efforts between their own network and the networks of their
52 K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55
partner vendors? Future research could address these questions
as well.
Communication and promotion budget determination and
allocation
Determining the communication and promotion budget and
allocating that budget across different promotional tools are
important marketing decisions, particularly for manufacturers,
who spend considerable money on promoting their brands. From
a retailer’s viewpoint, manufacturer spending decisions on con-
sumer and trade promotions are critical as they affect their
pricing and promotional policies. We review these decisions
brie?y (for a detailed review of these decisions from a man-
ufacturer standpoint, see Shankar 2008a).
Brand manufacturers set their communication and promotion
budgets based on one or more the following methods: objective
and task, competitive parity, percentage change from previous
year, and percentage of sales methods (Kotler and Keller 2009).
Once the budget is decided, a brand manger decides whether to
pursue a predominantly pull or push strategy. The pull strategy is
aimed at communicating directly to the end consumers to induce
them to seek the brand at the retail store, while the push strat-
egy is based on offering incentives to the channel intermediaries
such as retailers to actively sell the brand to the end consumers
(Kotler and Keller 2009). The pull strategy is built around pro-
motional tools such as advertising and consumer promotions,
whereas the push strategy is centered on tools such as trade pro-
motions and sales force. When a brand follows a pull strategy,
it spends the majority of its promotional budget on advertising
and consumer promotions, but when it pursues a push strategy,
it expends its promotional budget mostly on trade promotions
and sales force (Shankar 2008b). The brand manager further
allocates the brand’s promotional budget within each promo-
tional tool. For example, within advertising, the manufacturer
allocates spending between traditional media (e.g., TV, print,
radio) and new media (e.g., the Web, email, blog, social media,
mobile media).
Manufacturers allocate marketing budgets to different pro-
motional tools on the basis of relative competitive elasticities
(Shankar 2008a). For most CPG?rms, the bulk of the marketing
budget goes to advertising and sales promotion (consumer and
trade promotion). Over the past two decades, the allocation for
CPG ?rms has shifted from advertising toward sales promotion
due to three key reasons: increasing consumer decision-making
at the point of purchase, the rise of retailer power, and the
fragmentation of mass media communication vehicles (Shankar
2008a). Today, most CPG manufacturers spend approximately
two-thirds to three-fourths of their overall marketing dollars
on sales promotion. This shift is mainly because the ratio
of sales promotion elasticity to advertising elasticity is high.
Meta-analyses of advertising elasticities (Assmus, Farley, and
Lehmann 1984) and promotional elasticities (Pan and Shankar
2008) suggest that the median short-term advertising, carryover
advertising, and promotional elasticities are 0.22, 0.47, and 2.55,
respectively. Furthermore, the median deal elasticity is 4.45 (Pan
and Shankar 2008), underlying the growing allocation toward
sales promotion. These elasticities, however, capture only the
short-term effects and do not re?ect the accepted notion that
while advertising’s positive effects are realized primarily over
the long-term, promotions’ positive effects are re?ected predom-
inantly in the short-term (Dekimpe and Hanssens 1999). Also,
these advertising elasticities may underestimate advertising
effectiveness because they do not capture second order effects
whereby heavily advertised brands are more likely to get broader
as well as deeper distribution (Farris and Reibstein 2000).
An understanding of advertising and promotion elasticities
and how manufacturers allocate budgets to advertising and dif-
ferent promotions tools is important froma retailer’s perspective
for at least two reasons. First, since much if not all of a retailer’s
promotion spending comes directly from manufacturers’ trade
promotion funds, manufacturer budgets directly affect retailer
budgets. Second, there is a strong conceptual argument that there
is synergy between manufacturer advertising and retail promo-
tion effectiveness (Farris, Olver, and de Kluyver 1989; Olver
and Farris 1989). If so, retailers need to take these synergies
into account in determining their own budgets.
Future research directions
Moving forward, we need research on several issues. First, we
need more models of pull and push strategies that allow interac-
tion or synergistic effects of pull and push elements (e.g., Naik,
Raman, and Winer 2005). Amethodological issue in developing
such models is multicollinearity which occurs when elements
of push and pull strategies are highly correlated, precluding the
estimation of synergistic effects.
Second, more research is needed on the return on investment
(ROI) of communication and promotional budgets and cam-
paigns, especially for retailers. As we have noted above, work
on budgeting and allocation has been done almost solely from
the manufacturer’s viewpoint. But many retailers also spend
a signi?cant portion of their marketing budget on advertising,
apart from traditional promotion spending. We need descriptive
research on how they make these budget decisions in practice
as well as normative and optimization models to prescribe how
they should make these decisions.
Third, empirical support for the synergy between manufac-
turer advertising and retail promotion effectiveness is limited
and not particularly consistent. Sethuraman and Tellis (2002)
?nd a positive relationship between category advertising and
retail promotions but Mela, Gupta, andLehmann(1997) andNijs
et al. (2001) ?nd that advertising intensity reduces the effective-
ness of price promotions. Resolution of this issue is important if
retailers are to appropriately account for manufacturer advertis-
ing in their own promotion budgeting decisions. Similarly, the
cross-effects of advertising and promotion of different brands
on one another are important in determining retailers’ optimal
prices and promotions.
Other avenues for future research
There are several other important issues that need research
attention. First, not much is known about differences in the effec-
K.L. Ailawadi et al. / Journal of Retailing 85 (1, 2009) 42–55 53
tiveness of communication and promotion of the same product
across multiple countries. More retailers are going global these
days. Retailers such as Carrefour and Metro derive a major-
ity of revenues and pro?ts from outside the countries in which
they are headquartered. Wal-Mart is increasingly looking for
overseas expansion and growth. Because an effective commu-
nication and promotion strategy in one country may not always
work in another country, cross-national research on promotion
effectiveness is desirable.
Second, we need a deeper understanding of how the effec-
tiveness of advertising and promotion differs across the different
stages of the product life cycle. While prior research (e.g., Farris
and Buzzell 1979; Shankar 2008b) suggests that manufacturers
allocate more budget to the more elastic marketing instrument
over the life cycle, not much is known froma retailer perspective.
How should a retailer allocate resources toward store coupons,
feature advertising, and other in-store efforts for products that
are in different life cycle stages?
Third, manufacturers and retailers would be bene?ted by a
better knowledge of the execution issues involving promotion.
Manufacturers, retailers, and third party information vendors
spend considerable amount of time measuring promotions and
auditingin-store executionof promotions andrelatedevents. The
timeliness of these activities is critically important to obtaining
clean data and to ensuring that promotions are executed accord-
ing to plan. Accuracy in three dimensions of execution is critical:
delivery of required all commodity volume (ACV), execution
of promotional activities according to the promotion calendar,
and alignment of in-store placement of items with planograms.
An in-depth analysis of these issues would offer useful exe-
cution guidelines to retailers, manufacturers and relevant third
parties.
Conclusion
Communication and promotion decisions form the heart
of retailer customer experience management strategy. In this
review, we have addressed two key questions from a retailer’s
perspective: (1) what have we learned from prior research
about promotion, advertising, and other forms of communica-
tion and (2) what major issues should future research in this area
address. In addressing these questions, we followed a frame-
work that captures the interrelationships among manufacturer
and retailer communication and promotion decisions and retailer
performance. We examined these questions under four major
topics: determination and allocation of promotion budget, trade
promotions, consumer promotions and communication and pro-
motion through the newmedia. Our reviewreveals several useful
insights from prior research and identi?es many fruitful topics
and questions for future research.
Acknowledgements
The genesis of this article is in the Thought Leadership
Conference on Customer Experience Management in Retail-
ing organized at Babson College in April 2008. The authors
thank the conference co-chairs, Dhruv Grewal, V. Kumar, and
Michael Levy and the other conference participants for their
helpful comments and suggestions.
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