An executive summary for managers and executive readers can be found at the end of this article

Advertising vs sales promotion: a brand management perspectiveGeorge S. Low Jakki J. MohrAssistant Professor of Marketing, M.J. Neeley School of Business, Texas Christian University, Fort Worth, Texas, USA Associate Professor of Marketing, School of Business Administration, University of Montana, Missoula, Montana, USA

Keywords Brands, Advertising, Sales promotion, Decision making Abstract Brand managers in packaged goods firms are under pressure to increase or maintain high sales promotion spending at the expense of media advertising. This study investigates the antecedents and outcomes of brand managers' advertising and sales promotion budget allocations by adopting a bounded rationality perspective. Based on survey data collected from 165 brand managers in the USA, higher advertising (vs sales promotion) allocations are associated with: single, relatively high priced brands in the early phases of the product life cycle; and more experienced brand managers who are subject to less retail influence. Also, brands with higher budget allocations to advertising, relative to sales promotion, tend to have more favorable consumer attitudes, stronger brand equity, and higher market share increases and profits. Managerial implications and areas for future study are discussed.

The addictive power of promotion is such that manufacturers must devote ever larger proportions of their marketing budgets to this ``short-term fix'' and ever smaller proportions to the long-term health of their brands (Kahn and McAlister, 1997, p. 20).

Risks of high spending

Research showing evidence of the risks of high sales promotion spending is starting to appear (e.g. Mela et al., 1997; Papatla and Krishnamurthi, 1996), as managers in many grocery products firms try to reduce their mammoth sales promotion budgets. Procter & Gamble led the way by cutting trade promotion spending dramatically and adopting an everyday-low-price strategy (Reitman, 1992). P&G and other companies are now trying to wean consumers off coupons (Narisetti, 1997; Schrage, 1996). Despite these and other, less-publicized efforts to cut the billions spent on sales promotions every year, manufacturers continue to allocate almost 75 per cent of their marketing communications budgets to these short-term activities (Tenser, 1996). A.C. Nielsen estimates that trade promotion spending increased to 58 percent of total advertising and sales promotion expenditures in 1995, compared with 50 per cent in 1991 (Mathews, 1996). It is surprising that brand managers continue to allocate such a large proportion of their marketing budgets to sales promotion at the expense of advertising even as the potential problems associated with this strategy are becoming more widely known.The authors gratefully acknowledge the financial support from the Marketing Science Institute, the College of Business at the University of Colorado-Boulder, and the Charles Tandy American Enterprise Center at Texas Christian University. In addition, they appreciate the encouragement and helpful comments of David Olson (Leo Burnett Advertising), Katherine Jocz, Rick Staelin, and Paul Root (MSI) and David Cravens (TCU).The current issue and full text archive of this journal is available at http://www.emerald-library.com

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Budget an important issue

Previous empirical research on advertising and sales promotion budgeting has examined the relationship between product and market characteristics and advertising/sales ratios (Farris, 1977; 1978; Lancaster, 1986), promotion/ sales ratios (Quelch et al., 1984), and advertising-and-promotion/sales ratios (Balasubramanian and Kumar, 1990; Fader and Lodish, 1990; Farris and Albion, 1980; Farris and Buzzell, 1979). The amount budgeted to advertising and promotion relative to sales is an important issue. The findings from this research indicate that a variety of product and market factors (such as market growth rates, market share, competitive activity, and a product's relative price) are significantly related to advertising and/or sales promotion spending levels. However, none of these studies examines the firm's relative allocation to advertising versus sales promotion. The relative allocation issue is critical for many brand managers today whose budgets are flat or declining, and who must make trade-offs in deciding how to best allocate scarce marketing communications resources. For example, according to 1998 national US media spending figures, ten of the largest packaged goods advertisers actually decreased their overall advertising spending vs 1997 (Advertising Age, 1999). These included national brand manufacturers Procter and Gamble (3.4 per cent), Philip Morris (4.1 per cent), BristolMyers Squibb (22.3 per cent), Johnson and Johnson (11.3 per cent), Mars Inc. (11 per cent), Kellogg Co. (19.7 per cent), Hershey Foods (7.4 per cent), Colgate-Palmolive (4.7 per cent), Quaker Oats Co. (5.1 per cent), and Nabisco (3.9 per cent). Mantrala et al. (1992, p. 173) suggest that sales and profit are more sensitive to the way a budget is allocated than to its overall level; they comment that ``more behavioral research on how marketing organizations approach allocation decisions as opposed to investment-level decisions is needed''. Surprisingly, this call for research on allocation decisions has gone largely unheeded. As stated earlier, most prior research on the advertising and sales promotion budget issue has focused on understanding factors that are related to the ratio of marketing communications spending to sales. In our analysis of this research, two significant issues arose. First, many extant advertising and sales promotion studies have emphasized market growth rates and market share as predictors of advertising and sales promotion spending (Balasubramanian and Kumar, 1990). Indeed, the recent series of articles on this topic (Ailawadi et al., 1994; 1997; Balasubramanian and Kumar, 1997a; 1997b) focused more on technical issues of data analysis than on substantive questions about the underlying theoretical framework and managerial issues. Lost in this dialogue is a potentially important suggestion:Efforts would be better spent searching for other variables [in addition to market share and market growth rates] that can do a better job of explaining advertisingand-promotion/sales ratios (Ailawadi et al., 1994, p. 97).

Two significant issues

Our review of the relevant literature suggests that research is needed on variables which are actionable by management, since market share and growth, for the most part, are not. Commenting on past research on advertising and promotion budgeting decisions, Stewart (1996) called for the inclusion of more decision-making variables such as stage of the product life cycle. Stewart further suggested that the firm- and SBU-level PIMS and Compustat data used in previous studies lead to potentially misleading conclusions the appropriate unit of analysis should be the brand. A second crucial issue in understanding brand-level advertising and sales promotion budgets is the fact that the perspective of the people who make the allocation decision brand managers has mostly been left out of prior390 JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000

research. An understanding of the factors that influence brand managers' decision-making processes as they balance a complex set of decision variables in allocating marketing communications budgets would be an important research contribution. In addition, their perceptions of outcomes arising from the relative allocation are also important, given the current trend for greater marketing communications efficiency and accountability. Research gap It is apparent that a research gap exists concerning brand managers' perceptions of relevant antecedents and outcomes of advertising and sales promotion budget allocation decisions. To address this issue, we examine the advertising and sales promotion allocation decision from the perspective of brand managers. We predict the relationship between important product/ market and organizational/decision-maker characteristics and the relative budget allocation to advertising and sales promotion at the brand level. In addition, we extend prior research by exploring the brand-level consequences of the relative allocation between advertising and sales promotion, such as market share and profits. We first develop the conceptual foundations and hypotheses for the study. Next, we explain our research method and data collection efforts. Finally, we present the empirical results and discuss their implications for marketing practice and future research. Conceptual foundations and hypotheses There are at least two theoretical approaches to studying resource allocation decisions. The first is the classical economics view of decision-makers as rational utility maximizers who allocate resources subject to a budget constraint and uncontrollable market conditions such as competition, market share and sales response functions (cf. Samuelson, 1970, Ch. 22). This approach to studying resource allocations, based primarily on historical data, has led to the development of powerful, prescriptive, analytical techniques and models which focus on decision outcomes. The second of the two theoretical approaches to studying resource allocation decisions was initiated by March and Simon (1958), who argued that decision-makers will not always seek the best possible solution, but will search until a reasonable solution is found. This descriptive, bounded rationality approach acknowledges that managers use their own biased judgment to make decisions, and are influenced by the realities of organizational life (Mintzberg, 1978). This approach has the potential to help us better understand the real-world, seemingly irrational behavior of decision-makers who continue to allocate large proportions of scarce marketing resources to sales promotions despite the widespread desire to reduce such short-term spending. Accordingly, we selected bounded rationality as the theoretical perspective for this study (for a more detailed discussion of the contemporary theoretical perspectives on strategic decision making, see Mintzberg et al., 1998). Important decision variables Advertising vs sales promotion budget allocation The advertising vs sales promotion budget allocation is defined as the relative budget amount allocated to advertising compared to the budget amount allocated to sales promotions (consumer and trade). This variable captures the relative emphasis on long-term brand-building activities (advertising) compared to short-term sales incentives (sales promotions) in the brand's marketing communications mix (cf. Zenor et al., 1998). Because advertising increases full-margin sales while sales promotion decreases unit margins, these two tools are direct substitutes and therefore are traded off in budgeting decisions (Tellis, 1998, p. 427), particularly when budgets are flat or decreasing and costs are increasing. Since advertising and sales promotion391

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can be used to achieve similar marketing objectives in different ways, managers are faced with a difficult decision when allocating funds between them. We relied on past qualitative and exploratory descriptive research (e.g. Low and Mohr, 1999; Strang, 1980; Robinson and Luck, 1964) to help us select important decision variables. We also reviewed research that helped us predict the outcomes of the advertising and sales promotion budget allocation. The supporting logic for the predicted antecedent and outcome relationships follows. Consumer demand and competitive intensity Product/market antecedent hypotheses Stage of the brand's product life cycle. The stage of the product life cycle for a brand captures consumer demand and competitive intensity in the marketplace (Catry and Chevalier, 1974). In the two early stages of a product's life cycle (introduction and growth), advertising is used to inform consumers about features and benefits, to strategically position a brand, and to build awareness. Previous research (Farris, 1977) found that advertising spending was positively related to the introduction and growth stages of the product life cycle, and negatively related to the maturity stage. During the mature phase of the product life cycle, intense competition can also lead managers to shift funds away from advertising and into promotions as they attempt to take market share from competitors (Sethuraman and Tellis, 1991). Hence, we predict that: H1: In the latter stages of the product life cycle (maturity) compared to the earlier stages of the product life cycle (introduction and growth), brand managers allocate less of the marketing communications budget to advertising relative to sales promotion. Branding strategy Brand type. Brand type refers to the branding strategy used by a company for a specific product line. Single or individual brands have unique brand names, whereas family brands share a brand name with other product lines in the same company (Aaker, 1996, Ch. 8). The brand type used in planning advertising and sales promotions may affect budget allocations. Consider, for example, Kraft General Foods' decision to feature the Kraft family brand (e.g. Kraft cheeses, Kraft salad dressings) or single brands (e.g. Bull's Eye barbecue sauce) in their Olympic Games sponsorship campaign (Friedmann, 1992). Family (or corporate) brands (i.e. Dole fresh fruit, Dole fruit juices, and Dole dried fruit) may be more efficient to advertise than single (or individual) product brands (i.e. Crest toothpaste and Tide detergent). Advertising a family brand (which identifies the name of a group of products, perhaps some in very different product categories) may require a proportionately smaller allocation to advertising than a single product brand, which may require more advertising to support its unique brand message, image, and identity. Aaker (1996) states:A corporate brand that is applied to many products also provides economies of scale and scope in creating visibility and awareness, since the cost involved is spread over multiple products and categories. Further, the name is exposed wherever these products are advertised or sold. Multiple products therefore translate directly into more exposure for the brand name (p. 117).

Economies of scale from family or corporate branding would not apply to sales promotions to the same extent as advertising, since many common sales promotions are variable costs. Accordingly, we predict that: H2: For single brands, compared to family brands, brand managers allocate proportionately more of the marketing communications budget to advertising relative to sales promotions.392 JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000

Relative price. There is supporting research evidence that the price of the brand, relative to competitors' prices, is associated with the relative allocation to advertising or sales promotion. Higher-priced products may support larger allocations to advertising (Farris and Buzzell, 1979). When a product has a high price relative to competing brands, it is likely to receive more brand-building media advertising to support its higher-price position; on the other hand, when a product has a lower relative price, it is more likely to receive a greater allocation to sales promotions. Using sales promotions too frequently may reduce consumers' reference prices, a risky consequence for high-priced brands (Sawyer and Dickson, 1984). Consumers need to be continuously reminded of a high-priced product's superior image, quality, or prestige, a task ideally achieved by spending proportionately more on advertising. This leads us to predict the following: H3: A brand's relative price is positively related to brand managers' advertising allocations relative to sales promotion allocations. Relative allocation of the budget Market share. The focus of our study is not on the budget level, but on the relative allocation of the budget to advertising compared with sales promotion. Products with a high relative market share are less likely to benefit from short-term share-building incentives such as consumer and trade promotion because such actions would produce diminishing returns their share positions are already strong and they have less to gain than low-share brands. Hence, for market leaders, long-term market share maintenance tends to be best served by allocating relatively higher proportions of communications budgets to advertising, which is an effective tool for establishing an image of leadership or dominance in a market (Aaker, 1991). Another reason that advertising may be more likely than sales promotions to produce economies of scale is that the cost of advertising at a given level is a fixed cost that can be spread across a larger number of unit sales by large market share firms. On the other hand, sales promotion is typically a variable cost, so it may be more efficient for low-share brands to use sales promotion than advertising. In fact, it can be cost-prohibitive for large-share brands to match the sales promotions of smaller-share competitors because the cost of the most common types of sales promotion is applicable to every unit sold. Therefore, we anticipate that: H4: Relative market share is positively related to brand managers' advertising budget allocations relative to sales promotion allocations. Decison-maker factors Organizational/decision-maker antecedent hypotheses In addition to the product/market factors described above, the bounded rationality perspective suggests that organizational and personal decisionmaker factors, which tend to bias decisions, also play a role in budget allocations. There are three variables which appear to be related to the relative budget allocated to advertising or sales promotion: the short- or long-term perspective encouraged in the organization, the influence of retailers, and the decision maker's experience. Short-term perspective. Short-term perspective is defined as the degree to which management in the respondent's firm emphasizes short-term goals and objectives (one year or less), and encourages short-term results (Burke, 1984). Advertising can be viewed as a relatively higher-risk/higher-return strategy than sales promotions which have an element of certainty to them and whose results are more measurable using scanner data (Zenor et al., 1998). When a firm encourages long-term decision-making that is inherentlyJOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000 393

risky, managers may be more likely to allocate proportionately more of their budget to advertising. Farris and Quelch (1987, p. 64) aptly described the biasing effect of short-term orientation on managers' budget allocation decisions:In fact, a short-term orientation, driven by top management's emphasis on quarterly results, is the cause rather than the result of promotions used to boost sales. A recent study (Quelch, Farris and Olver, 1987) indicated that 90 percent of product managers would rather spend less time on short-term promotion and more time on franchise-building advertising, but the top-rated managers were those who spent more time on promotion, indicating that senior management is rewarding a short-term orientation.

Reward systems

Reward systems are frequently used as a way to encourage short- or longterm results (Anderson and Chambers, 1985). With respect to budget allocation decisions, a reward system that is oriented towards short-term performance (annual or quarterly results) compared to one that focuses on multiple-year measures, may influence brand managers to make decisions that will stimulate short-term sales. In such a situation, consumer and trade promotions are more likely to be emphasized, relative to advertising, because of their immediate, positive, impact on sales (Blattberg and Neslin, 1990). Hence: H5: A brand manager's belief that, in his or her organization, short-term results are more important than long-term results, is negatively related to advertising allocations relative to sales promotion allocations. Retail influence. We define retail influence as the degree to which retailers attempt to use their power to increase sales promotion spending by manufacturers. Grocery product retailers, whose margins are razor-thin, rely heavily on the cash and discounts from sales promotions and slotting fees to improve their profits (Kahn and McAlister, 1997). In a 1995 study by McKinsey & Company on packaged goods salesforces, the authors concluded that ``retailers are being forced to push back on manufacturers in order to maintain their own narrow margins'' (DeVincentis and Kotcher, 1995). Murry and Heide (1998), in their study of retail participation in promotion programs, found that financial incentives were more important to retailers than other factors such as corporate or personal relationships in encouraging participation in sales promotions. Retailers use their increasing size and the power of information generated via scanner technology to influence manufacturers, persuading them to divert greater amounts of their communications budgets to sales promotions (Quelch, 1983). Unwillingly, manufacturers have complied, acknowledging the fierce battle for shelfspace and merchandising activity. Consequently, we posit that retailer influence is negatively related to advertising spending, relative to sales promotion spending. H6: The degree of retailer influence is negatively related to brand managers' advertising allocations relative to sales promotion allocations.

Dependence on judgment or intuition

Decision-maker's experience. We define experience as the number of years a manager has worked for his or her employer. Experience with the current company is used rather than total career experience because we wanted to control for situations where managers may have changed employers, thereby changing industry categories, geographic locations, company procedures, and perhaps even career paths. Managers often rely on insights from past experience and their own personal intuition when making important business decisions (Fraser and Hite, 1988). Simon (1987) proposed that experiencedJOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000

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managers make decisions by relying more on their judgment or intuition, whereas inexperienced managers rely more on careful analysis. A recent study based on interviews with marketing practitioners (Bucklin and Gupta, 1998) found that the assessment of advertising effects is more difficult for managers than the assessment of sales promotion effects. Inexperienced managers may allocate more resources to sales promotions because their outcomes are more easily quantifiable; whereas experienced managers may be more confident in allocating resources to advertising. Also, the need to score short-term sales gains by using more sales promotions in order to further their career advancement would be less important to senior managers. Accordingly, we propose that: H7: A manager's experience level with his or her current company is positively related to advertising relative to sales promotion budget allocations. Firm's budget allocation decision Outcomes of advertising and sales promotion allocations We now turn our attention to the outcomes of a firm's budget allocation decision. As noted earlier, because of concerns about the consequences of allocating large proportions of communications budgets to sales promotions, we explore the relationships between advertising and sales promotion allocations and managers' perceptions of profit, market share, brand equity and consumer attitudes for their brands. In other words, does the allocation of marketing communications budgets make a difference to the outcomes of the decision? We acknowledge that the relationship between marketing communication budget allocations and outcomes is complex, not only because of the many variables that can affect outcomes, but also because of the time lag between the allocation decision and the outcomes. For example, the effects of a current advertising campaign may not be immediately apparent. We attempt to address these issues by examining the relationship between the prior year's actual budget allocation and the current year's brand outcomes. We also control for company size and market growth rate. We first review the effects of advertising and sales promotion separately, and then we discuss the likely relationships between the advertising-sales promotion budget allocation and brand performance. Advertising effects. Based on single-source data, Abraham and Lodish (1990) concluded that advertising has a greater impact on profits than either consumer or trade promotions. They also suggested that because of a number of problems associated with consumer and trade promotions, such as forward buying and the inability of many promotions to cover the profits that would have been generated with baseline sales, advertising is more profitable. This conclusion was also reached by Jones (1990, p. 148) who determined that ``manufacturers that promote heavily are deliberately exchanging profit for volume; in other words, making less profit on more sales''. The impact of advertising The impact of advertising on consumer attitudes and brand equity has been studied extensively. The power of advertising in building strong brands has been proposed by marketing practitioners (e.g. Martin, 1989) and academics (Aaker, 1991; 1996). Most advertising dollars are directed at consumers and typically are accompanied by specific objectives to improve consumer attitudes (Quelch, 1989). By building a strong position in the market, advertising allows a firm to command higher prices for its products, and thus increase profits. This rationale is borne out by studies on the effects of advertising on consumer attitudes (e.g., Alden et al., 1999; Wansink and Ray, 1996). Aaker (1991) and Shimp (1997) propose that higher relative395

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spending on advertising can generate favorable consumer attitudes towards the advertised product. Increase in research activity Sales promotion effects. The increased usage of consumer promotion by marketers has been accompanied by an increase in research activity to determine the impact of such promotions. The most consistent finding is that consumer promotions increase unit sales and market share of the promoted brand (Gupta, 1988). Although these findings seem somewhat obvious, since consumer promotions typically take the form of price reductions, research has provided additional insight. For example, consumer promotion research has found that coupons have a greater impact on sales than an equivalent reduction in price (Cotton and Babb, 1978). Although the impact of consumer promotions on consumer attitudes has yet to be resolved, a number of plausible explanations have been offered for a potential negative relationship (Blattberg and Neslin, 1990). These include self-perception theory (Dodson et al., 1978), dissonance theory (Doob et al., 1969), and attribution theory (Sawyer and Dickson, 1984). The common conclusion of these authors is that the use of consumer promotions too frequently over an extended period of time may lead to less favorable consumer attitudes toward the brand. Outcomes of trade promotion An increasing number of studies are investigating the outcomes of trade promotion. Because trade promotions frequently take the form of price reductions, the result is increased unit sales and market share (Hardy, 1984). In addition, information providers such as IRI and Nielsen have used sophisticated modeling techniques and single-source data to show that trade promotions increase unit sales (Honnold, 1992). Quelch (1983) suggests that the relationship between the use of trade promotion and market share is so basic that the success of trade promotions should be measured by the resulting share increase. Managers are more likely to respond to a competitor's increased trade promotion activity compared to increased advertising activity since trade promotion has a more immediate impact on market share, an important standard for many brand managers. They rely on trade promotions because they expect to see an immediate increase in market share. Conversely, recent studies have consistently concluded that excessive use of trade promotion decreases brand loyalty, increases price sensitivity, and reduces baseline sales for a brand (Mela et al., 1997; 1998; Papatla and Krishnamurthi, 1996). These studies point to the negative potential impact of sales promotion spending on profits, consumer attitudes, and brand equity. Effects of relative allocation to advertising vs sales promotion. Based on the review of the individual effects of advertising and sales promotion discussed above, we expect that when budgets are allocated so that relatively more funds are spent on advertising and relatively fewer on sales promotions, consumer attitudes, brand equity, and profit will be higher, and market share will be lower compared to brands with relatively fewer funds allocated to advertising and more to sales promotion. Accordingly, we predict that: H8: High relative advertising and low relative sales promotion budget allocations are associated with perceptions of: (a) higher consumer attitudes; (b) higher brand equity; (c) lower market share; and (d) higher profit.396 JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000

Method Context and sample A survey method was selected in order to isolate brand-level budget allocations, to measure organizational and decision-maker variables, and to accurately represent the perspective of the brand manager prescribed by bounded rationality theory. Although we recognize the potential bias involved in paper and pencil measurement techniques, many of the variables in our study are, by their very nature, psychological perceptions of reality. For example, the influence of retailers in the decision process would be difficult or impossible to quantify using other methods. And, consistent with the theoretical approach adopted in this research, we wanted to tap into the perceptions of brand managers in order to understand this important allocation decision based on the position that their decisions are boundedly rational. Indeed, it is managers' perceptions of reality that determine their decision-making behavior, not reality itself (cf. Anderson et al., 1987). In addition, secondary data available from companies such as Compustat and A.C. Nielsen, or published in AdWeek or Progressive Grocer include only some of the brand-level data required in our study. For example, none of these sources provide measures of the manager's experience level, retailer influence, or brand attitudes. Brand managers as agents Hence, we focused on brand managers as agents for their brands. Our intent was to understand better the decision process factors and potential biases involved in the allocation of marketing communications budgets from their perspective. Furthermore, brand managers are the individuals in packaged goods companies most likely to know brand-level advertising and sales promotion budgets and to be familiar with the antecedents and outcomes of the allocation. We developed a national sampling frame of product/brand managers and group or category product/brand managers of packaged goods firms (consumer goods manufacturers who typically distribute products via grocery stores and mass merchandisers) in the USA using three sources. First, we screened all the names in the American Marketing Association membership directory; 50 names were identified as brand managers in consumer products firms, so we included all of these in our sample frame. Second, packaged goods member companies of the Marketing Science Institute were invited to participate in the study; 20 brand managers were identified from this source. Third, a list of 538 brand, product, group, and category managers in US packaged goods firms was purchased from a trade marketing magazine, for a total sample frame of 608 product/brand managers or group product/brand managers. Given the small number of brand managers we were able to identify, we did not randomly select a subset from this sampling frame, but included them all in our study. Enhancing response rates In order to enhance response rates for our mail survey, the techniques advocated by Dillman (1978) were followed. Personalized cover letters accompanied the questionnaire. These letters explained the purpose and importance of the study, emphasized that responses would be anonymous, and offered a summary of the results to those who included a business card. In addition, a new one dollar bill was included with each questionnaire as an incentive. Postage-paid return envelopes were enclosed to make responding easier. A follow-up mailing was sent three weeks later, consisting of a reminder letter, return envelope, and another copy of the survey. Of the 608 questionnaires sent, 120 were returned as undeliverable to the addressee, reducing the original sample to 488. Of these, 165 completed, useable397

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surveys were returned, for a response rate of 33.8 percent. An assessment of nonresponse bias indicated no significant differences between early and late respondents on several key variables, including firm size, current market share, and years of experience (Armstrong and Overton, 1977). Managerial decisionmaking perspective In order to qualify our respondents, we asked them to report their level of responsibility for making advertising and sales promotion budget allocations for the brand they selected (the brand for which they had the highest level of responsibility and familiarity). On a seven-point scale (anchored by 1 = none at all; 7 = complete responsibility), the mean was 5.5 (standard deviation = 1.1). In addition, 93.9 percent of respondents held a position title of brand or product manager or above (including group or product category manager and vice-president of marketing), and reported an average of 13 years of career experience. Hence, it appears that our respondents were knowledgeable about the domain of interest and able to provide the managerial decision-making perspective which was the focus of the study. Questionnaire and measure development We developed our initial questionnaire by adapting existing measures in the literature and by seeking input from senior marketing managers. A complete listing of the survey items appears in the Appendix. The draft survey was then used in a series of pre-tests that were conducted in an iterative fashion in personal interviews with an additional 20 brand managers until no further improvements to the draft survey were suggested. Our pre-tests clearly showed that many brand managers are responsible for multiple brands. Hence, we needed to focus respondents' attention on one brand as the basis for their responses to the survey. To help them focus their answers on one brand's budget allocation and related brand-level questions (product life cycle, market share, etc.), the first page of the survey booklet included the statement:When questions refer to ``your brand,'' please consistently answer these questions based on the brand or product for which you are primarily responsible. If you are responsible for more than one brand or product, choose the one brand with which you are the most familiar.

This statement was designed to avoid measurement error which may have influenced the results had we not made it clear that the basis for answering the brand-level questions was a single brand or product. Potential bias Second, given the potential bias involved in the survey research method, we took steps to ensure that the research instrument included various types of questions to minimize halo effects. Perceptual, psychological variables, such as the importance of short-term results in the firm, were measured using Likert scales. Most of the brand-level spending and performance data were measured using objective questions which asked respondents to write down actual numbers indicating market share, budget allocations, and years of experience. Existing, related research was used as a guide in constructing our survey. For example, we used the product life cycle question from the PIMS survey (Buzzell and Gale, 1987). We made an explicit trade-off in planning the questionnaire between brevity and the use of multi-item scales for appropriate variables, with the result that uni-dimensional product/market variables such as stage of the product life cycle and brand type were measured with single-item scales. However, because of their complexity and psychological nature, short-term perspective of management, perceptions of consumer attitudes, and perceptions of brand equity were measured with seven-point, multi-item Likert scales.398 JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000

Concern given to key variable

Special concern was given to the potential sensitivity of our key variable budget allocations to advertising, consumer promotion, and trade promotion and share and profit information. The first page of the survey booklet and the cover letter assured respondents of anonymity. For the budget allocation question, respondents were asked to provide their budget allocation in terms of percentages, rather than dollar amounts, for advertising, consumer promotion, and trade promotion (see Appendix). For current brand profit, respondents were asked to record their responses on a seven-point Likert scale. Two questions asked for actual market share data the market share from the prior year and current market share. We calculated the change in market share as an index number. While these measures are not as direct as they might be, senior brand managers with whom we consulted during pre-testing suggested that it might be the only way to collect sensitive financial and outcome data. This technique also attempted to capture the change in performance over time. In order to capture some of the complexity of the relationship between marketing communications budget allocations and outcomes, we included two key covariates company size and market growth rate in our tests of the outcome hypotheses. We also measured competitive intensity and initially included this key variable in our analysis, however it was not significantly related to the dependent variables, and hence, we dropped it from further analysis.

Multi-item scales assessed

Scale purification The multi-item scales were assessed for reliability and validity using confirmatory factor analysis (LISREL VII) and standard reliability analysis. The overall confirmatory factor analysis fit (each multi-item scale loading on separate latent constructs) was acceptable, with a GFI of 0.87, AGFI of 0.77, chi-square of 115.37 with 32 degrees of freedom. The coefficient alpha for short-term perspective was 0.89, for perceived consumer attitudes, 0.70, and for perceived brand equity, 0.78. Means, standard deviations, coefficient alphas, and correlations appear in Table I. Analysis and results The dependent variable of interest in our antecedent hypotheses (H1 to H7) was the percentage advertising allocation, divided by the sum of the percentage allocations to consumer and trade promotion. Respondents were asked to report the planned percentage of their brand's marketing communications budget allocated to these tools for the coming year. In this way, we attempted to identify the relationship between current characteristics of the product, market, organization, and decision-maker, and budget allocation plans for the future in essence, capturing the mix of variables considered by brand managers in formulating their brand plans for the coming year and the variables that may affect their decisions.

Relationships were tested

The relationships hypothesized in H1 to H7 were tested using multiple regression with the planned advertising vs sales promotion budget ratio as the dependent variable (as defined above), and the seven product/market and organizational/decision-maker measures entered as independent variables. Adjusted R2 = 0.15 (p < 0.01, F = 4.99, df = 7, 157). The regression results appear in Table II, and a summary of the hypotheses and their results appears in Table III. Product/market factors H1 predicted a negative relationship between stage of a brand's product life cycle and the planned allocation to advertising vs sales promotion. The

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400

Meana SD 2.02 1.34 1.00 1.00 0.18* 1.00 1.00 0.04 0.02 0.01 0.08 0.16 0.11 0.12 0.28** 0.25** 0.08 0.07 0.07 0.06 0.10 0.19* 0.20* 0.11 0.03 0.09 0.12 0.07 0.89 0.12 0.13 0.01 0.70 0.14 0.14 0.78 0.24** 0.02 0.04 0.11 0.05 0.11a

Coeff. alpha Co. size Brand type Rel. price 0.02 0.22** 1.00 0.00 0.01 0.04 1.00 0.11 0.05 0.06 0.05 0.20* 0.02 0.17 0.01 0.06 0.03 0.08 0.02 0.02 1.00 0.09

Mkt. gr. rate Stage of PLC L.Y. mkt share

ShortDec. term Retail maker persp. infl. exper.

Adv. sales pro.

Adv./ alloc.

Cons. att.

Mkt. Brand share eq. change Profit

4.52 4.85 4.18 2.04 19.91 19.43 12.01 4.09 7.47 0.50 0.15 28.24 25.68 20.99 14.20 101.14 5.00 3.82 4.14 4.29 1.67 0.03 0.03 4.95 1.67 6.62

0.07 0.12 0.02 0.06 1.00 0.03 0.17* 0.17* 0.21* 0.18* 0.16* 0.01 0.08 0.07 0.02 0.21* 0.23** 0.16* 0.02 0.11 0.17* 0.14 0.01 0.08 0.15 0.14 0.09 0.18 0.02 0.08 0.10

1.00 0.19* 1.00 0.15 0.84** 1.00 0.10 0.15 0.10 0.18* 0.05 0.18* 0.17 0.21** 0.12 0.25** 0.27** 0.27** 1.00 0.38** 1.00 0.32** 0.11 0.33** 0.24**b

Covariates Company size Market growth rateb Product/market Stage of brand PLCc Brand typed Relative price L.Y. market share (%) Organizational/managerial Short-term perspectivee Retail influence Decision maker exper.f Budget allocation Adv/sales promo ratio L.Y. adv. alloc'n (%) Outcomes Consumer attitudesg Brand equityh Market share changei Profit

1.00 0.18

1.00

Notes: * p < 0.05 (two-tailed); ** p < 0.01 (two-tailed); All items on a seven-point scale, unless otherwise noted. Multi-item scales are summed as indicated; The categories for the seven-point scale were: Decreasing over 10 per cent; 6-10 per cent; 1-5 per cent; Stable no growth; Increasing 1-5 per cent; +6-10 per cent; Growing over 10 per cent; c Categorical: Introductory (n = 9); Growth (n = 77); Maturity (n = 63); Decline (n = 10); d Categorical: Family brand (n = 93); Single product brand (n = 29); Group of single product brands (n = 35); Other (n = 8); e Three items; f Number of years; g Four items; h Three items; i Index number

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Table I. Means, standard deviations, coefficient alpha and intercorrelations of variables

Variable Product/market factors Relative price Brand type (single vs family) Stage of PLC (mature vs growth) Market share Organizational/managerial factors Retailer influence Manager's experience Short-term perspective Adjusted R2 F-value Degrees of freedom Notes: * p < 0.05; ** p < 0.01 0.16* 0.19* 0.20** 0.06 0.16* 0.24** 0.02 0.15** 4.99 7,157

Table II. Beta coefficients from multiple regression analysis for antecedent hypotheses: dependent variable = advertising percentage/(consumer percentage + trade percentage)Hypothesis H1 H2 H3 H4 H5 H6 H7 H8a H8b H8c H8d Prediction Maturity of product life cycle stage 3 advertising vs sales promotion () Single brands vs family brands 3 advertising vs sales promotion (+) Relative price 3 advertising vs sales promotion (+) Relative market share 3 advertising vs sales promotion (+) Short-term focus 3 advertising vs sales promotion (+) Retailer influence 3 advertising vs sales promotion () Manager's experience 3 advertising vs sales promotion (+) Advertising vs sales promotion 3 consumer attitudes (+) Advertising vs sales promotion 3 brand equity (+) Advertising vs sales promotion 3 market share () Advertising vs sales promotion 3 profit (+) Results Supported Supported Supported Not supported Not supported Supported Supported Supported Supported Not supported (relationship in opposite direction) Supported

Table III Summary of hypotheses and results

multiple regression results indicate that brands in the later phases of the product life cycle (maturity) tend to have lower budget allocations to advertising relative to sales promotions than brands in the earlier phases of the product life cycle (introductory and growth). The beta coefficient is negative and statistically significant (b = 0.20, p < 0.01). Hence, H1 is supported. Positive relationship H2 proposed a positive relationship between brand type (family brands coded as ``1'' and single brands coded as ``2'') and the budget allocated to advertising as compared to the budget allocated to sales promotion. The regression results support this hypothesis (b = 0.19, p < 0.05). Single brands, on average, have a higher budget percentage allocated to advertising than to sales promotion compared to family brands.401

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H3 states that a brand's relative price (compared to competitors' prices) will be positively associated with the budget percentage allocated to advertising compared with sales promotions. The regression results show that the beta coefficient for a brand's relative price is positive and statistically significant (b = 0.16, p < 0.05). Thus, the higher a brand's price relative to competitors, the higher the percentage of the communications budget allocated to advertising compared with sales promotion. H3 is supported. H4 asserts that a brand's relative market share will be positively related to advertising budget allocations compared with sales promotion allocations. The regression coefficient for market share is not significant. Thus, this hypothesis is not supported. Consumer and trade promotion Organizational/managerial factors H5-H7 predicted the relationship between organizational or decision-maker factors and managers' allocations of marketing communications budgets to advertising relative to consumer and trade promotion. Table II also presents the regression results testing these hypotheses. Two of the three hypothesized relationships are supported by the data. H5 states that when senior management in the firm is perceived as being focused on short-term results, brand managers plan to allocate less of their budgets to advertising relative to sales promotion. The beta coefficient for this variable was not statistically significant. Hence, H5 is not supported. H6 posits that as retailers have more influence, brand managers allocate proportionately less of their budgets to advertising relative to consumer and trade promotion. The regression coefficient for retail influence is negative and statistically significant (b = 0.16, p < 0.05). This result shows that H6 is supported. As expected, when managers perceive retailers' influence to be strong, their marketing communications budget has a lower allocation to advertising relative to sales promotion. Decision-maker experience H7 predicted that as managers have greater experience with the company, they tend to allocate proportionately more of their budgets to advertising relative to sales promotion. The results also support this hypothesis (b = 0.24, p < 0.01). Decision-maker experience is positively related to the proportion of budgets allocated to advertising relative to sales promotion. Outcomes H8 addressed the relationships between the budget allocation and consumer attitudes, brand equity, market share change, and profit. A positive relationship was predicted between the advertising allocation and perceived consumer attitudes (H8a), brand equity (H8b), and profit (H8d), and a negative relationship was predicted between the advertising allocation and market share (H8c). In order to test these hypotheses, we used a median split based on the previous year's actual budget percentage allocated to advertising to form two groups of respondents. (Using the prior year's budget allocation with the current year's outcomes allows us to isolate the lagged relationship between prior decisions and current outcomes.) The median for the previous year's actual advertising allocation was 20 per cent. The high advertising allocation respondents (greater than 20 per cent, n = 56) had lower average sales promotion allocations, whereas the low advertising allocation respondents (less than or equal to 20 per cent, n = 57) had greater average sales promotion allocations. (The total does not equal 165 because of missing data for the multivariate analysis.) This median split402 JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000

grouping was then used as the independent variable in a MANCOVA analysis, together with the four, correlated dependent variables (consumer attitudes, brand equity, market share, and profit), and the two covariates (market growth rate and company size). The MANCOVA results appear in Table IV. Advertising vs sales promotion As these results show, the multivariate effect of the advertising allocation vs sales promotion allocation was significant (Wilk's Lambda = 0.83, F = 5.54, p < 0.001, Eta2 = 0.17), with significant univariate relationships found for each of the four dependent variables: managers' perceptions of consumer attitudes (b = 0.17, F = 9.78, p < 0.01) and brand equity (b = 0.23, F = 10.39, p < 0.01), market share (b = 0.21, F = 4.56, p < 0.05), and profit (b = 0.22, F = 10.79, p < 0.01). All four relationships are positive; however, we had predicted positive outcome relationships for all but H8c (the relationship between the relative budget allocation to advertising and market share, for which we had predicted a negative relationship). Hence, H8a, H8b and H8d are supported, but H8c is not supported. It appears that larger advertising budget allocations are associated with enhanced consumer attitudes, brand equity, profit and market share. We elaborate on these results in the next section. Discussion A primary objective of this study was to understand how bounded rationality could contribute to an increased understanding of the continued emphasis on sales promotion in the marketing communications budget allocation in the face of concerns about its harmful effects. We examined the relationships between product/market heuristics and organizational/decision-maker biases and brand managers' allocations to advertising vs sales promotion. Our study provides additional insight to the budget allocation decision process by focusing on brand-level budget allocations, and by including variables that capture the contextual realities of organizational decision-making. In addition, we extend existing research by investigating the impact of communications budget allocations on perceptions of brand outcomes. In the following sections, we discuss the key findings of our study, suggesting managerial implications, study limitations, and directions for future research. Managerial implications Why do managers continue to spend heavily on sales promotions relative to advertising, despite emerging evidence that such allocations may lead to undesirable consequences? By investigating the budget allocation decision process from the hands-on perspective of brand managers who are at the heart of the decision, our findings support the bounded rationality predictions that a combination of product/market and organizational/decision-maker factors relate to the allocation. Some of these factors are controllable by management and therefore have direct implications. Commonly used decision rules As brands progress through the product life cycle, managers plan to allocate proportionately less of their marketing communications budget to advertising, and more to consumer and trade promotions. In addition, lower relative price brands and family brands typically receive an allocation that emphasizes sales promotion relative to advertising. These product/market factors appear to be commonly used decision rules that managers rely on in making their allocation decisions. Given the preponderance of mature packaged goods brands, low price strategies, and look-alike brand extensions (Kahn and McAlister, 1997), the continued high sales promotion allocations are not surprising. Managers looking to increase advertising allocations403

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404

Multivariate effects Brand equity F Beta 0.23 0.06 0.82 0.01 0.10 7.93** 10.43** 0.09 0.11 5.04* 0.04 0.07 F Beta F 3.63** 3.13* 0.11 0.12 Eta2 Eta2 Eta2 Consumer attitudes Beta 0.07 0.09

Univariate effects outcomes Profit F 3.39 2.08 Eta2 0.03 0.02 Beta 0.05 0.10 Share change F 0.47 1.32 Eta2 0.00 0.01

Wilks' Lambda

Covariates

Company size

0.88

Market growth rate

0.89

Main effect 5.54*** 0.17 0.23 10.39** 0.09 0.17 9.78** 0.08 0.22 10.79** 0.09 0.21 4.56* 0.04

Relative advertising allocation 0.10 6.16** 3,142

0.83

Adjusted R2

0.04 2.77* 3,137

0.05 3.41* 3,143

0.03 2.33 3,114

F

d.f.

Notes: * p < 0.05 ** p < 0.01 *** p < 0.001

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Table IV. MANCOVA results: effects of advertising vs sales promotion allocation on outcomes

should first consider adjusting their brand strategy to focus on higher-priced, more meaningful new products or brand extensions (cf. Andrews and Low, 1998), using an individual branding approach. Impact of rational product/ market factors The impact of rational product/market factors on the allocation should be considered in light of influential organizational realities and personal biases. Managers might intend to be rational in their allocation decisions, but be less conscious of the impact of organizational and personal variables. Our results show that when retailer influence is strong, managers allocate proportionately fewer dollars to advertising, and more to consumer and trade promotion (retailer influence was measured using a one-item Likert scale asking respondents to rate how much influence retailers have over brand managers' marketing allocations). In order to counter-balance this tendency, managers might work more closely with retailers either to monitor the use of promotional dollars, or to work on joint advertising and promotion programs which create a win-win situation and increase the proportion of product sales at full price. However, as retailers grow in size and influence, the problem of retailer influence and escalating sales promotion spending will continue to be a difficult challenge for packaged goods manufacturers. For example, recent consolidation by large US grocery retailers such as Kroger, Albertson's, and Safeway has made the retailer manufacturer relationship a critical factor in decisions related to advertising and trade promotion spending. When managers have more experience with the company, they plan to allocate proportionately more dollars to advertising and fewer to consumer and trade promotion. Accordingly, firms may consider implementing a formal mentoring program, whereby more experienced managers work with less experienced managers in allocating their marketing communications budgets. Such a practice may offset the tendency of less experienced managers to use more sales promotions. This finding also highlights the need for more measurement techniques to assess the long-term effects of advertising, such as that recommended by Dekimpe and Hanssens (1997). Such techniques may help both inexperienced and senior brand managers understand more confidently the potential outcomes of their budget allocation decisions. New perspective Our findings provide marketing and advertising practitioners with a new perspective that may encourage them to more strategically manage the marketing communications budget allocation process. The antecedent relationships identified could be critiqued and discussed by brand planning teams to determine if these overall trends fit their company's strategic direction for a product or division. For example, should products in the mature phase of their life cycle receive more sales promotion spending and less advertising than new brands? Should a higher-priced, single brand receive more advertising and less sales promotion than other brands? How conscious are brand managers that retailer power influences allocations towards sales promotions at the expense of advertising and that their experience level may be influencing their decisions? By explicitly considering these issues in budgeting decisions, managers may be able to avoid allowing such factors to unwittingly bias their budget allocations. Our research objective was not to determine the optimal allocation of budgets, but to recognize the bounded rationality of the decision process by seeking to make a decision as free from bias and error as possible. Particularly where large budget amounts are involved, which is typical in many grocery product manufacturers, even minor, incremental improvements in budget allocation decision-making may improve brand performance significantly.405

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Importance of budget allocation

With respect to the outcome results, the significant multivariate and univariate effects of the per cent advertising allocation on all four outcomes (consumer attitudes, brand equity, market share and profit) indicate the importance of the budget allocation for brand performance. These results support the warnings of many that funds diverted away from advertising to sales promotion may lead to unanticipated negative consequences. Consumer attitudes, brand equity, market share and profit were all significantly higher for brands whose advertising allocation was above the sample median of 20 per cent. These findings imply that it may be possible for many firms to simultaneously achieve positive results on all four outcomes by increasing their allocation to advertising and decreasing their allocation to sales promotion. The unexpected, positive relationship between the advertising allocation and change in market share suggests that sales promotions may not be having the effect on sales and share that many managers take for granted. Possibly, despite the market visibility generated by sales promotion activity, consumers may be tired of sales promotion offers and the positive relationship between advertising and share is the result of this promotion overkill. Alternatively, there may be so much sales promotion spending in some consumer packaged goods categories that firms using these promotions are making consumers less brand loyal and more price sensitive overshadowing the perceived benefits of the brands and reducing overall category sales (Mela et al., 1998; Papatla and Krishnamurthi, 1996). It is also well known that many retailers use trade promotions simply as a way to increase their profits they do not pass the savings on to consumers at all (Kahn and McAlister, 1997). Dollars might be shifted to advertising in order to build loyalty, while increasing the efficiency and effectiveness of a reduced sales promotion budget (Buzzell et al., 1990).

Implications of the study

Limitations and future research The implications of this study should be considered in the context of its limitations, which also suggest a number of areas for future study. We collected data based on brand managers' knowledge of facts and perceptions of reality. In accordance with our theoretical perspective, our goal in this study was to understand the marketing communications budget allocation as a decision made by brand managers. It is managers' perceptions of the factors we studied which affect their decision-making; hence, perceptual measures were used. While we used a wide variety of measures to attempt to minimize any possible halo effects, it would also be useful for future research to assess some of these variables more directly, such as consumer attitudes and profits. An additional limitation concerns the complex relationship between marketing communications allocations and outcomes many other variables are related to a brand's performance. While we attempted to address this by controlling for important covariates, other variables are likely to have an important effect on outcomes. We also acknowledge the lag time that should occur between the strategy and its outcomes, and the bidirectionality of many of the relationships in our study. We attempted to address this by using the last year's allocation and the current year's outcomes. We also recognize the strong potential for reciprocal effects of product/market factors as well as outcome variables, and the advertising allocation (dual causality). For example, strong profits may be an effect as well as a cause of increased advertising spending. We asked respondents to report the coming year's planned allocation to advertising, which allowed us to assess the effect of

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current market conditions on future allocations. However, further research is needed to better understand the direction of the long-term, causal relationships identified in our study. Useful extensions of this study might address not only the allocation percentage to advertising as compared to sales promotion, but also compare this to the absolute level of spending. Although we did not measure budget size directly, we found two brand managers in our data who identified themselves by sending their business cards with their surveys. Both of their brands are in the extremely competitive cola industry, one a large multinational, the other a small regional brand. The large-budget brand had an allocation of 86 per cent to advertising; the small-budget brand had 70 per cent allocated to trade promotion. It may be that smaller budgets dictate that a larger percentage is allocated to trade promotion in order to achieve adequate distribution levels and secure valuable shelf space. Future research could address these issues. Future research efforts Future research efforts could also explore the effects of other factors not measured in our study. It may be that special sales promotion types, such as contests and sweepstakes, for example, affect outcomes differently than commonly used promotions such as coupons. Internet advertising, fast becoming an important communications tool, may be related to antecedents and outcomes in a different way than traditional media and sales promotions. Relevant consumer-based characteristics such as brand loyalty and deal proneness might also affect allocation decisions. Another extension of this study could examine moderating relationships among antecedent variables. For example, it may be that in early stages of a product's life cycle, when category growth is generally a more important objective, there may be a different set of factors driving advertising or sales promotion spending than in later stages of a brand's life cycle, when brand development becomes the dominant goal. Marketing managers struggle with the need to support short-term market share and simultaneously build long-term brand equity and profitability for their brands. Marketing communications budget allocation decisions epitomize this struggle, one that short-term sales promotions appear to be dominating. The relative allocation between advertising and sales promotion is particularly important in today's environment of flat marketing budgets where an increased allocation to one communications tool typically comes at the expense of another. Despite the importance and timeliness of this allocation decision, it is poorly understood, particularly from the perspective of brand managers who are faced with making and implementing budget allocations. In order to address this lack of knowledge, we adopted a bounded rationality perspective and conducted a study of the antecedents and outcomes of brand managers' budget allocations to advertising and sales promotion. Our findings identify some of the decision heuristics and biases that help explain why brand managers continue to allocate much of their budget to sales promotions, despite the potential benefits of shifting some of it to advertising. A greater understanding of these issues offers managers and researchers alike the opportunity to improve the way this important decision is made.Notes 1. The categories for brand type were coded using 1 for family brand, 2 for single product brand, 3 for a group of single product brands, and 4 for ``other''. The first three categories made sense to code in a linear fashion, as each brand type increased in uniqueness and complexity. We determined that coding the ``other'' cases as a 4 was appropriate after looking closely at the eight cases in this category and noting that these exceptions were a step higher in complexity and uniqueness of brand type.JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000 407

2. R denotes reverse scoring. 3. An open-ended questionnaire below the categories asked respondents to detail the reasons why planned spending may have deviated from actual. In addition, they were asked to list any strategic changes which might have influenced this year's allocation. Of the 35 respondents who had a deviation from planned spending to actual, most cited competitive activity and pressure from retailers to increase trade deals (in order to keep shelf space and retail support). Other reasons for deviation from planned vs actual were delays in advertising creative, disappointing advertising results, investing in brand building activities, entering new geographical markets, introducing new products, oversupply of product, increased costs of products and organizational restructuring. Of the 42 respondents who cited strategic changes which influenced the planned allocation, the majority included a philosophical shift away from trade and into advertising activities. 4. For those firms which might have defined the various tools in a ``unique or different way'' or for those which felt a need to elaborate on the categories used by their firm, an open-ended question beneath the categories allowed respondents to elaborate on their categories. Information here generally supported the distinctions we draw between the three tools. For example, advertising expenditures included media spending; consumer promotion included in-store demonstrations, coupon vehicles such as FSI and direct mail, samples, and so forth. Only four of the 165 surveys indicated slight differences. For example, two respondents said that customer promotion included point of purchase and in-store (non-price) materials. And two respondents indicated that brand budgets did not contain trade dollars one because the trade budget is set prior to ``handling down'' a budget to brands, and the other because trade promotion was not considered a marketing expense, but rather an ``offset'' to revenue. We re-ran the analyses without these four cases; and the results did not change. 5. An ``other'' category was provided for those whose plan included other tools, such as direct mail. A total of 28 respondents include other items in their marketing communications budget. however, by using the relative allocation (advertising/consumer + trade promotion), we avoid bias in the antecedent hypotheses. To check for potential bias in the outcomes analysis, a covariate was added to control for these 28 cases, and the MANCOVA was re-run with the same results. In addition, we ran the MANCOVA again without these 28 cases, and again, the results were the same. 6. Coded from 1 through 7, higher numbers for higher growth rates. References Aaker, D.A. (1991), Managing Brand Equity: Capitalizing on the Value of a Brand Name, The Free Press, New York, NY. Aaker, D.A. (1996), Building Strong Brands, The Free Press, New York, NY. Advertising Age (1999), ``100 leading national advertisers'', Vol. 70, 27 September, pp. S24-S46. Ailawadi, K.L., Farris, P.W. and Parry, M.E. (1994), ``Share and growth are not good predictors of the advertising and promotion/sales ratio'', Journal of Marketing, Vol. 58, January, pp. 86-97. Ailawadi, K., Farris, P. and Parry, M. (1997), ``Explaining variations in the sdvertising and promotional costs/sales ratio: a rejoinder'', Journal of Marketing, Vol. 61, January, pp. 93-6. Abraham, M.M. and Lodish, L.M. (1990), ``Getting the most out of advertising and promotion'', Harvard Business Review, Vol. 90 No. 3, pp. 50-60. Alden, D.L., Steenkamp, J.B. and Batra, R. (1999), ``Brand positioning through advertising in Asia, North America, and Europe: the role of global consumer culture'', Journal of Marketing, Vol. 63, January, pp. 75-87. Anderson, E., Lodish, L.M. and Weitz, B.A. (1987), ``Resource allocation behavior in conventional channels'', Journal of Marketing Research, Vol. 24, February, pp. 85-97. Anderson, P.F. and Chambers, T.M.(1985), ``A reward/measurement model of organizational buying behavior'', Journal of Marketing, Vol. 49, Spring, pp. 7-23. Andrews, J. and Low, G.S. (1998), New but Not Improved: Factors that Affect the Development of Meaningful Line Extensions, Report Number 98-124, Marketing Science Institute, Cambridge, MA. Armstrong, J.S. and Overton, T.S. (1977), ``Estimating nonresponse bias in mail surveys'', Journal of Marketing Research, Vol. 14, August, pp. 396-402.408 JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000

Balasubramanian, S.K. and Kumar, V. (1990), ``Analyzing variations in advertising and promotional expenditures: key correlates in consumer, industrial, and service markets'', Journal of Marketing, Vol. 54, April, pp. 57-68. Balasubramanian, S.K. and Kumar, V. (1997a), ``Explaining variations in the advertising and promotional costs/sales ratio: a reanalysis'', Journal of Marketing, Vol. 61, January, pp. 85-92. Balasubramanian, S.K. and Kumar, V. (1997b), ``Explaining variations in the advertising and promotional costs/sales ratio: a response, research criteria, and guidelines'', Journal of Marketing, Vol. 61, January, pp. 97-8. Blattberg, R.C. and Neslin, S.A. (1990), Sales Promotion: Concepts, Methods, and Strategies, Prentice-Hall, Englewood Cliffs, NJ. Bucklin, R.E. and Gupta, S. (1998), Commercial Adoption of Advances in the Analysis of Scanner Data, Report Number 98-103, Marketing Science Institute, Cambridge, MA. Burke, M.C. (1984), ``Strategic choice and marketing managers: an examination of businesslevel marketing objectives'', Journal of Marketing Research, Vol. 21, November, pp. 345-59. Buzzell, R.D. and Gale, B.T. (1987), The PIMS Principles: Linking Strategy to Performance, The Free Press, New York, NY. Buzzell, R.D., Quelch, J.A. and Salmon, W.J. (1990), ``The costly bargain of trade promotion'', Harvard Business Review, Vol. 68, March/April, pp. 141-9. Catry, B. and Chevalier, M. (1974), ``Market share strategy and the product life cycle'', Journal of Marketing, Vol. 38, October, pp. 29-34. Cotton, B.C. and Babb, E. (1978), ``Consumer response to promotional deals'', Journal of Marketing, Vol. 42, July, pp. 109-13. Dekimpe, M.G. and Hanssens, D.M. (1997), Sustained Spending and Persistent Response: A New Look at Long-term Marketing Profitability, Report Number 97-102, Marketing Science Institute, Cambridge, MA. DeVincentis, J.R. and Kotcher, L.K. (1995), ``Packaged goods salesforces beyond efficiency'', The McKinsey Quarterly, No. 1, pp. 72-85. Dillman, D.A. (1978), Mail and Telephone Surveys: The Total Design Method, John Wiley & Sons, New York, NY. Dodson, J.A., Tybout, A.M. and Sternthal, B. (1978), ``Impact of deals and deal retraction on brand switching'', Journal of Marketing Research, Vol. 15, February, pp. 72-81. Doob, A.N., Carlsmith, J.M., Freedman, J.L., Landauer, T.K. and Soleng, T. Jr (1969), ``Effect of initial selling price on subsequent sales'', Journal of Personality and Social Psychology, Vol. 11 No. 4, pp. 345-50. Fader, P. and Lodish, L. (1990), ``A cross category analysis of category structure and promotional activity for grocery products'', Journal of Marketing, Vol. 54, October, pp. 52-65. Farris, P.W. (1977), Determinants of Advertising Intensity: A Review of the Marketing Literature, Report No. 77-109, Marketing Science Institute, Cambridge, MA. Farris, P.W. (1978), Advertising Intensity in Consumer Goods Businesses: An Empirical Analysis, Report No. 78-118, Marketing Science Institute, Cambridge, MA. Farris, P.W. and Albion, M.S. (1980), Determinants of Variations in the Advertising-to-Sales Ratio: A Comparison of Industry and Firm Studies, Report No. 80-107, Marketing Science Institute, Cambridge, MA. Farris, P.W. and Buzzell, R.D. (1979), ``Why advertising and promotional costs vary: some cross-sectional analyses'', Journal of Marketing, Vol. 43, Fall, pp. 112-22. Farris, P.W. and Quelch, J.A. (1987), ``In defense of price promotion'', Sloan Management Review, Vol. 29 No. 1, pp. 63-9. Fraser, C. and Hite, R. (1988), ``An adaptive utility approach for improved use of marketing models'', Journal of Marketing, Vol. 52, October, pp. 96-103. Friedmann, L. (1992), ``What management needs to know about sales promotion'', Conference on Sales Promotions from the Consumer, Manufacturer, and Retailer Perspectives, Report No. 92-103, Marketing Science Institute, Cambridge, MA, p. 3. Gupta, S. (1988), ``Impact of sales promotion on when, what, and how much to buy'', Journal of Marketing Research, Vol. 25, November, pp. 342-55.JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000 409

Hardy, K.G. (1984), ``Factors associated with successful manufacturer sales promotions in Canadian food and drug businesses'', in Jocz, K.E. (Ed.), Research on Sales Promotion: Collective Papers, Marketing Science Institute, Cambridge, MA, pp. 63-82. Honnold, D. (1992), ``Promotions or advertising: modelling a better mix'', Conference on Sales Promotions from the Consumer, Manufacturer, and Retailer Perspectives, Report No. 92-103, Marketing Science Institute,Cambridge, MA, p. 5. Jones, J.P. (1990), ``The double jeopardy of sales promotions'', Harvard Business Review, Vol. 68 No. 5, pp. 145-52. Kahn, B.E. and McAlister, L. (1997), Grocery Revolution: The New Focus on the Consumer, Addison-Wesley, Reading, MA. Lancaster, K.M. (1986), ``Are there scale economies in advertising?'', Journal of Business, Vol. 59 No. 3, pp. 509-26. Low, G.S. and Mohr, J.J. (1999), ``Setting advertising and promotion budgets in multi-brand companies'', Journal of Advertising Research, Vol. 39, January/February, pp. 67-78. Mantrala, M.K., Sinha, P. and Zoltners, A.A. (1992), ``Impact of resource allocation rules on marketing investment-level decisions and profitability'', Journal of Marketing Resarch, Vol. 29, May, pp. 162-75. March, J.G. and Simon, H.A. (1958), Organizations, John Wiley & Sons, New York, NY. Martin, D. (1989), Romancing the Brand: The Power of Advertising and How to Use It, American Management Association, New York, NY. Mathews, R. (1996), ``The real truth about trade promotion'', Progressive Grocer, Vol. 75, September, p. 42. Mela, C.F., Gupta, S. and Lehmann, D.R. (1997), ``The long-term impact of promotion and advertising on consumer brand choice'', Journal of Marketing Research, Vol. 34, May, pp. 248-61. Mela, C.F., Jedidi, K. and Bowman, D. (1998), ``The long-term impact of promotions on consumer stockpiling behavior'', Journal of Marketing Research, Vol. 35, May, pp. 250-62. Mintzberg, H. (1978), ``Patterns in strategy formulation'', Management Science, Vol. 24, May, pp. 934-48. Mintzberg, H., Ahlstrand, B. and Lampel, J. (1998), Strategy Safari, The Free Press, New York, NY. Murry, J.P. and Heide, J.B. (1998), ``Managing promotion program participation within manufacturer-retailer relationships'', Journal of Marketing, Vol. 62, January, pp. 58-68. Narisetti, R. (1997), ``Many companies are starting to wean shoppers off coupons'', Wall Street Journal, 22 January, p. B1. Papatla, P. and Krishnamurthi, L. (1996), ``Measuring the dynamic effects of promotions on brand choice'', Journal of Marketing Research, Vol. 33, February, pp. 20-35. Quelch, J.A. (1983), ``It's time to make trade promotion more productive'', Harvard Business Review, Vol. 83, May/June, pp. 130-36. Quelch, J.A. (1989), Sales Promotion Management, Prentice-Hall, Englewood Cliffs, NJ. Quelch, J.A., Farris, P.W. and Olver, J.M. (1987), ``The product management audit'', Harvard Business Review, Vol. 65, March-April, pp. 30-36. Quelch, J.A., Marshall, C.T. and Chang, D.R. (1984), ``Structural determinants of ratios of promotion and advertising to sales'', in Jocz, K.E. (Ed.), Research on Sales Promotion: Collective Papers, Marketing Science Institute, Cambridge, MA, pp. 83-105. Reitman, V. (1992), ``Retail resistance: eliminated discounts on P&G goods annoy many who sell them'', Wall Street Journal, 11 August, pp. A1, A6. Robinson, P.J. and Luck, D.J. (1964), Promotional Decision Making: Practice and Theory, McGraw-Hill, New York, NY. Samuelson, P.A. (1970), Economics, 8th ed., McGraw-Hill, New York, NY. Sawyer, A.G. and Dickson, P.R. (1984), ``Psychological perspectives on consumer response to sales promotion'', in Jocz, K.E. (Ed.), Research on Sales Promotion: Collective Papers, Marketing Science Institute, Cambridge, MA, pp. 1-21. Schrage, M. (1996), ``Clipped and challenged: Procter & Gamble Co.'s advertising strategy'', Adweek, Vol. 37, 19 Feburary, p. 36. Sethuraman, R. and Tellis, G.J. (1991), ``An analysis of the tradeoff between advertising and price discounting'', Journal of Marketing Research, Vol. 28, May, pp. 160-74.410 JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000

Shimp, T.A. (1997), Advertising, Promotion, and Supplemental Aspects of Integrated Marketing Communications, 4th ed., Dryden, Orlando, FL. Simon, H.A. (1987), ``Making management decisions: the role of intuition and emotion'', Academy of Management Executive, Vol. 1, February, pp. 57-64. Stewart, D. (1996), ``Allocating the promotional budget: revisiting the advertising and promotion-to-sales ratio'', Marketing Intelligence & Planning, Vol. 14 No. 4, pp. 34-8. Strang, R.A. (1980), The Promotional Planning Process, Praeger, New York, NY. Tellis, G.J. (1998), Advertising and Sales Promotion Strategy, Addison-Wesley, Reading, MA. Tenser, J. (1996), ``Polls concur: spending is flowing to the trade'', Supermarket News, Vol. 46, 3 June, p. S1. Wansink, B. and Ray, M.L. (1996), ``Advertising strategies to increase usage frequency'', Journal of Marketing, Vol. 60, January, pp. 31-46. Zenor, M.J., Bronnenberg, B.J. and McAlister, L. (1998), The Impact of Marketing Policy on Promotional Price Elasticities and Baseline Sales, Report Number 98-101, Marketing Science Institute, Cambridge, MA. Appendix. Survey Items Product/market factors Brand type. (Family vs single product brands). Please check the brand type that best describes your brand responsibility (check one). This is a: Family brand (one brand name/multiple products, i.e. Dole products) (n = 93). A single product brand (i.e. Cracklin' Bran cereal, which comes in multiple sizes and flavors) (n = 29). A group of single product brands (n = 35). Other (specify): (n = 8)[1]. Relative price. (Seven-point Likert scale, strongly agree, strongly disagree anchors.) Relative to my competitors, my brand's retail selling price is higher. Market share. (Seven-point Likert scale.) Relative to my competitors, the volume market share for my brand is quite a bit lower. (R)[2]. Stage of brand's product life cycle. Which of the following best describes the product life cycle stage of your brand: Introductory, Growth, Maturity, Decline [Because of the nature of our hypothesis, which compared earlier stages of the PLC introductory and growth to maturity, respondents in the introductory or growth stage were coded as ``1'' (cf. Sethuraman and Tellis, 1991), while respondents in the mature stage were coded as ``2.'' The ``other'' or ``decline'' cases (n = 10) were coded as missing for this variable.] Organizational factors Retail influence. (Seven-point Likert scale.) Retailers have no influence in how funds are allocated to the various marketing tools for my brand. (R) Short-term perspective. (Seven-point Likert scale) (Coefficient alpha = 0.89). Top managers repeatedly tell employees that this business unit's survival depends on its shortterm performance. According to senior managers here, short-term performance is the most important measure of our business unit's success. This organization's management is satisfied achieving short-range goals and objectives. Decision-maker's experience. Please specify the number of years that you have worked in this company.JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 9 NO. 6 2000 411

Budget allocation ``Responding to competitive threats and/or financial concerns may mean that what you actually spend on advertising, consumer promotion, and trade promotion differs from what you planned to spend. Planned refers to the percentage allocation numbers in your brand plan; Actual refers to the percentage that was actually spent after changes and adjustments in spending were made during implementation in the past year[3]. (Note: if your brand is a new brand, put `0' in last year's columns.) All responses are anonymous''[4]. Last year's planned spending (divide 100%) Advertising Consumer promotion Trade promotion Other (specify)[5] Total 100 per cent 100 per cent 100 per cent Last year's actual spending (divide 100%) This year's planned spending (divide 100%)

Outcomes Consumer attitudes. (Seven-point Likert scale) (Coefficient alpha = 0.70). Consumer attitudes, in general, for my brand are very positive. Consumer attitudes towards my brand, relative to my key competitor(s), are more favorable. Relative to last year, consumer attitudes for my brand are more positive. Consumers feel better now about my brand than they have in the past. Brand equity. (Seven-point Likert scale) (Coefficient alpha = 0.78) When it comes to brand equity, I would say my brand does pretty well. My brand's equity is not as strong as I would like it to be (R). Relative to my major competitors, my brand's equity is solid. Current market share The current monthly volume market share for my brand nationally is: (please fill in per cent). Last year's market share. My brand's monthly volume market share nationally a year ago was: (please fill in per cent). (Change in market share computed as the difference between current year's share +100 and last year's share + 100, to produce an index number.) Profit Relative to other brands in my company, my brand's profit performance has been very good lately. (Seven-point Likert scale.) Covariates Market growth rate[6]. Compared to last year, the annual volume sales growth for this brand's product category is: Decreasing more than 10 per cent/6 to 10 per cent/1 to 5 per cent/Stable-no growth/ Increasing 1 to 5 per cent/+ 6 to +10 per cent/ Growing over 10 per cent. Company size Please circle the one number which best describes the size of your company relative to other competitors in your industry. (Seven-point scale, anchored by 1 = ``relatively small'', 7 = ``relatively large,'' 4 labeled ``about the same''.)

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This summary has been provided to allow managers and executives a rapid appreciation of the content of this article. Those with a particular interest in the topic covered may then read the article in toto to take advantage of the more comprehensive description of the research undertaken and its results to get the full benefit of the material present

Executive summary and implications for managers and executivesAdvertising works and don't you forget it! Despite the fact the sales promotions receive considerable criticism from academics and practicing marketers, there is a continued growth in the total amount spent on such promotions and in the proportions of overall marketing expenditure given over to sales promotions. Either the ordinary brand manager knows something we don't or else there is a failure to connect with such people. Low and Mohr find that the problem lies or appears to lie in part with the fact that the ``rational'' budget allocation decision taken by a product or brand manager is bounded by factors within the firm the rational decision is ``bounded''. As Low and Mohr describe ``F F F managers use their own biases judgment to make decisions and are influenced by the realities of organizational life''. Most brand managers will explain their use of sales promotions by saying that they ``work''. To understand the allocation decision between sales promotions and advertising we have therefore to appreciate just what is meant by the brand managers understanding of what works. Delivering to the performance target Brand managers even where they do not receive a performance element in their pay are driven by the need to meet targets set for the brand or brands that they manage. These targets are usually set in terms of sales revenue, contribution or market share. And, given the focus within most businesses, the targets are set on an annual basis. Imagine that you are a brand manager and you have received the sales, market share and contribution targets for your brand. You have to make a choice between advertising and sales promotions in the allocation of the limited budget available. You start off applying your knowledge of brand marketing by defining a strategy for the brand's promotion. Being a welltrained marketer you focus on the benefits of advertising and create a strategy that aims to build the ``brand franchise'' as a means of securing long-term advantages for the brand. Great stuff. But then you look again and realise that, at some point during the year, the brand's performance will be examined. You may know your strategy to be right but you also know that you cannot be sure that, come the six-month review, the figures for share or sales revenue will be on target. The result is that you build into the strategy promotional campaigns that will deliver the right numbers. One of your colleagues may have stuck with his/her campaign after all it is the right approach. But, following her six-month review, the sales figures are not there. What happens here is a mad rush of promotions designed to shore up the failure of the advertising campaign. This short-term perspective has been criticised at great length. Marketers know that the best way to build a brand is to use advertising. Marketers know that sales promotions can damage brand image. If you are always offering a deal it gets increasingly hard to secure sales at the full price. And we can assume that the pricing decision is made to deliver a set level of contribution to the firm's profits. If you want brand managers to deliver on the promise of strong image and a powerful brand franchise, you have to set targets that allow them to invest budgets in advertising rather than price-cutting sales promotions.

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Retail pressure and retailer power The traditional brand management model is predicated on pulling customer through the retailer. Because you invested in high profile advertising the retailer had to stock your product or disappoint customers. The power within the system lay with the big brands that could dictate a great deal to the retailer. But two important things happened. First, retail price maintenance was scrapped firms could no longer insist that retailers stick to the recommended price. Second, the retailers began to grow in size and to invest in systems that gave them far more information about consumers and consumer behaviour than was available to the big brand owners. The result of this change was that retailers began to insist on the brand owners supporting their strategies. And, at the heart of these strategies, was the desire to pull in more customers through the delivery of low prices. Trade promotions and trade discounting were essential to such a strategy. As the bigger retailers pushed out and absorbed the smaller shops, the power of the store chains forced brand owners to respond by trade promotions. The result has been huge shifts of marketing spend from advertising to trade promotions. And, at the same time as this consolidated retailer power it also gave those retailers the ability to focus on increasing their own overall margins through own label products and, at least in the UK, by developing their own brands through advertising. Is there hope for brands? Not if they rely on sales promotions The sales promotion is just another name for a price cut. Yes that price cut is delivered through a coupon, a good deal or a competition. But it remains a price cut. If brand owners