An investigation into the effect of competitive context on brand price elasticities

Transcription

1 An investigation into the effect of competitive context on brand price elasticities Abstract Extensive research has attempted to determine factors that consistently influence consumers responses to brand price changes (as measured through brand price elasticity). Scriven and Ehrenberg (2004) identified one such factor as being whether the price change passes a competitor brand s price. This paper examines the robustness of this finding through choice experiments across six frequently purchased consumer goods categories (beer, pasta sauce, toilet paper, bread, laundry detergent, and shampoo). The results indicate that brand price elasticities are consistently larger (i.e. more negative) for price changes that do pass another brand s price. This effect is most pronounced (1) for price decreases, (2) in contexts with high-priced competitors, (3) among light/non-users of the brand, and (4) among heavy users of the brand being passed. Keywords brand price elasticities, competitive contexts, prior brand usage Word count 7,745 (including 4500 words for tables/figures)

2 Introduction changes are one of the very few tools available to marketers to have a significant instant impact on a brand s sales. However, consumers responses to similar pricing activities can be vastly different across different time periods and markets. Understanding the influences on this variation is of great practical importance to marketers. Accordingly, extensive marketing literature have attempted to determine factors that consistently effect brand price elasticities (for meta-analyses, see Tellis 1988, Bijmolt, van Heerde et al. 2005). The majority of studies in this area have used revealed preference data (scanner panel and store-level sales) to investigate how different brand, category and consumer factors affect price elasticities (e.g., Bolton 1989, Krishnamurthi and Raj 1991, George, Mercer et al. 1996, Narasimhan, Neslin et al. 1996, Hamilton, East et al. 1997, Zenor, Bronnenberg et al. 1998, Bell, Chiang et al. 1999, Danaher and Brodie 2000, Fok, Horvath et al. 2006). These studies have found a consistent negative relationship between markets share and price elasticity, whereby smaller share brands have larger elasticities. Additionally, multiple studies have found larger elasticities for promotional price cuts with retailer support (e.g. in-store displays, feature advertising) (Narasimhan, Neslin et al. 1996, Zenor, Bronnenberg et al. 1998, Fok, Horvath et al. 2006), for brands in storable product categories (Narasimhan, Neslin et al. 1996, Bell, Chiang et al. 1999, Danaher and Brodie 2000), and among frequent users of a brand (Krishnamurthi and Raj 1991, Kalyanaram and Little 1994). However, many of the other factors analysed have found inconsistent results across these studies. A major limitation of using revealed preference data to address this research problem, is that it relies on marketing activities that have actually transpired. In this case, it has led to an abundance of studies researching promotional price changes (i.e. signaled temporary price cuts), with less focus on how consumers respond to regular (i.e. unsignaled) price increases and decreases. Additionally, scanner panel data records the brands that were chosen by a consumer, but rarely provide details about the other alternatives that were available but not purchased. This diminishes the ability to understand the potential influence of competitive context on price response. Alternatively, stated choice experiments give researchers far greater freedom to manipulate and isolate variables of interest that do not systematically occur in sales data. Scriven & Ehrenberg (2004) employed a stated choice method in their exploratory research to identify generalisable patterns in consumers responses to price changes. This involved manipulating prices across different brands, product categories and countries. Their results revealed that brand price elasticities were largely context-dependent. The factor that had the largest effect of elasticities was whether a price change passed the price of a competitor brand. This effect was strongest when passing the brand leader or multiple brands. The aim of the current study is to further explore the effect of passing competitor prices across various competitive scenarios. Research Questions As previously stated, Scriven and Ehrenberg (2004) identified that elasticities of price changes that pass competitors prices were larger than those of price changes that did not pass any competitors. Woodside and Ozcan (2009) also found price changes

3 induced greater response when they matched other brand s prices. The first research question aims to establish the generalisability of this passing competitor effect: RQ1: Do price changes that pass competitors prices consistently lead to larger elasticities? Numerous studies have attempted to determine whether the elasticities for price increases and decreases differ in a consistent pattern, however this research has produced mixed results. Some of these studies have shown the consumers are more responsive to price increases (e.g., Motes 1987, Scriven and Ehrenberg 2004, Dawes 2009), while others indicate greater response to price decreases (e.g., Litvack, Calantone et al. 1985, Ehrenberg and England 1990). While there may be inconsistencies, there is ample evidence to suggest that consumers respond to these pricing activities in different ways. The second research questions attempts to determine whether the effect of passing competitor prices differs when increasing and decreasing prices. That is, whether changing price to become cheaper than a competitor has a similar elasticity to passing to become more expensive than a competitor. RQ2: How does the effect of passing a competitor s price differ for price increases and price decreases? Research also indicates that the price sensitivity of a brand may depend on where the brand s price is relative to all other brands available. For instance, whether consumers respond to a price decrease of the cheapest brand in a different way to the most expensive brand available. The findings to date are mixed. Larger promotional elasticities have been found for both high price tier (Danaher and Brodie 2000, Fok, Horvath et al. 2006) and low price tier brands (Zenor, Bronnenberg et al. 1998). Additionally, Scriven and Ehrenberg (2004) noted that brands closest to the average category price had the largest elasticities. Looking at price increases, Sivakumar and Raj (1997) found that the higher price brands were more resilient to these changes. With regards to passing competitors prices, the price of the brand relative to competitors may also moderate this effect. For example, a price decrease that passes a competitor to make it the cheapest brand may produce a different result than a similar action that leaves the brand as a mid-priced option. Similarly, Sethuraman s (1996) investigated promotional cross-elasticities and found larger sales loses of brands in the low-price tier when a competitor promoted to become cheaper, but this was not seen among higher priced brands. The role of competitor prices is addressed with the third research question: RQ3: How does the effect of passing a competitor s price differ across different competitive price contexts? When passing a competitor s price there are two brands of interest, the brand changing its price (focal brand) and the brand being passed (competitor brand). Consumer prior experience with both of these brands may potentially effect how they respond to this change in price position. One of the robust findings across price elasticity studies is that heavy users of a brand are less responsive to price changes (Krishnamurthi and Raj 1991, Kalyanaram and

4 Little 1994, Scriven and Ehrenberg 2004, Dawes 2009). This research aims to establish whether this generalisation also extends to the passing effect, whereby heavy users may also be less responsive to this activity: RQ4: How does prior usage of the focal brand influence consumers responses to price changes passing the competitors price? The usage of the competitor brand may also effect how consumers perceive price changes of the focal brand. For example, if a consumer has never used the competitor brand before, they may be less likely to use it as a reference price to evaluate the price change of the focal brand. This study s final research question address this point: RQ5: How does prior usage of the competitor brand influence consumers responses to price changes passing the competitors price? Method Research Design To address the research questions, we use within-subject full factorial stated choice experiments across six different product categories. These use 3 2 x2 alternativespecific designs expressed over 18 choice sets. Between the choice sets there are two manipulations: price changes and competitive contexts. These experimental manipulations are linked to specific alternatives. Each experiment comprises of six alternatives: - Two mid-priced brands (alternative 1 and 2); - Two high-tier brands (alternative 3 and 4); and - Two low-tier brands (alternative 5 and 6). Alternatives 1 and 2 are the brands that experience price changes between choice sets. Both have prices manipulated across three levels: (1) regular price, (2) price decrease, and (3) price increase. change sizes range from 14.4% to 15.6% across the different brands and product categories. The price changes are not explicitly signaled to respondents (e.g., no sale signs). The regular price of alternative 2 is higher than the regular price of alternative 1. This ensures the occurrence of price changes that pass, and do not pass, competitors prices. Take for instance a price increase from the regular price of alternative 1. If alternative 2 were at its regular price level, this would be an example of passing a competitors price. However, if alternative 2 was at the increase or decrease price levels, alternative 1 s price increase would not have passed a competitor (see figure 1 for illustration). The remaining alternatives (3-6) are only ever shown at one price level. Instead, they are manipulated through choice sets via their presence or absence. Each choice set either displays the pair of high-tier brands (alternative 3 and 4) or the pair of low-tier brands (alternative 5 and 6). This changes the relative price position of alternatives 1 and 2. For instance, when alternatives 3 and 4 are present (high-tier competitive context), this makes alternative 1 the cheapest option. By contrast, when alternatives 5

5 and 6 are present (low-tier competitive context), alternative 1 is only the third cheapest option. See figure 1 following. High-Tier Competitive Context Low-Tier Competitive Context Figure 1. Experimental design showing price changes and competitive contexts The choice experiments are replicated across six different commonly purchased fast moving consumer goods categories beer, pasta sauce, toilet paper, bread, laundry detergent and shampoo. These categories have been selected to represent consumable and non-consumable goods covering different price levels. See appendix 1 for full details of brands and prices, which reflect the in-market prices in the region of data collection. Sample & Survey Procedure A sample of 927 respondents over the age of 21 from Illinois, USA, was obtained through an online panel provider. Each respondent completed the choice tasks for two product categories that they had used at least once in the previous 12 months (36 choice sets in total). The order of product category, order of choice sets and alternative positions within choice sets were randomised between respondents. Following the choice tasks, respondents were asked brief questions about the frequency of usage for each brand in the survey. The sample size per product category ranged from 238 for laundry detergent to 295 for beer (table 1). Table 1. Number of respondents per category Product Category Sample Size Beer 295 Pasta Sauce 267 Toilet Paper 279 Bread 283 Laundry Detergent 238 Shampoo 293 Analysis This paper reports exploratory univariate analysis detailing the effects of passing a competitor s price across different conditions. The findings from this analysis will be later used to inform more detailed multinomial logistic based analysis. We estimate the brand price elasticities using the point elasticity formula: Elasticity = (share! share! )/share! (price! price! )/price!

6 Where share 1 and price 1 are the initial choice share and price (i.e. at regular price) and share 2 and price 2 the new choice share and price after the price changes (i.e. price increase or price decrease). This paper reports aggregate brand price elasticities within a category (for individual brand elasticities, see appendix 2). Results Overall results The average brand price elasticity across all categories was -2.6, with 50% of all elasticities between the range of -0.9 and This closely replicates the findings in Bijmolt et al s (2005) seminal meta-analysis, which also found an average elasticity of -2.6 and with 50% of elasticities between the range of -1 and -3. Table 2. Summary of elasticities Pasta Beer Sauce Toilet Paper Bread Laundry Detergent Shampoo All Categories Average Elasticity Std. Dev Min Max There was considerable variation in elasticity size both between and within product categories, with the full range of elasticities from 0 (i.e. no response) through to Respondents were least responsive to price changes for beer (-1.9) and pasta sauce (- 2.1), and most sensitive to the price changes for laundry detergent (-3.0) and toilet paper (-3.3). Passing competitor prices Table 3 classifies the elasticities into price changes that passed competitor prices and price changes that did not pass competitors. The results provide further support for Scriven and Ehrenberg s (2004) finding that elasticities are larger when passing the price of a competitor. The responses to price changes passing competitors was over three times larger than when there were no pass (-4.9 vs. -1.4). Table 3. Average elasticities when passing and not passing competitors prices Beer Pasta Toilet Laundry Bread Paper Detergent Shampoo Average Passing Not Passing This passing competitor effect on elasticities was prevalent across all product categories, but with differences observed with regards to the size of the effects. The effect was most pronounced for the shampoo category with the average elasticity over six times larger when a brand passed a competitor. change direction The passing competitor effect is examined separately for price increases and price decreases to address RQ2 (table 4).

7 Table 4. Average elasticities when passing and not passing split by price increases and decreases Pasta Toilet Laundry Beer Bread Shampoo Average Sauce Paper Detergent Pass Increases No Pass Decreases Pass No Pass The effect of passing competitor prices on elasticity is seen for both price increases and decreases, with this effect appearing more pronounced for price decreases. Across all product categories, the passing on decrease elasticities (average -6.7) were greater than the passing on increase elasticities (average -3.0). Alternatively, the elasticities with no passing of competitors were quite similar for increases and decreases (average -1.5 and -1.4, respectively). Competitive price contexts Across the 18 choice sets, the price levels of alternatives 1 and 2 created 4 distinct price scenarios (see figures 2 and 3 for illustrations). This includes when a competitor was passed when increasing (price scenario 1) and a situation where the competitor was passed when decreasing (price scenario 2). Additionally, there were also two scenarios when no brands were passed, including when the competitor remained cheaper (price scenario 3) and when the competitor remained more expensive (price scenario 4). Each of these scenarios occurred with both high-tier competitors present and low tier competitors present (figures 2 & 3). Analysis of each of these price scenarios across different competitive tier contexts (table 5) provides insights to answer RQ3. Scenario 1 (Pass on Increase) High-Tier Competitive Context Low-Tier Competitive Context Scenario 2 (Pass on Decrease) High-Tier Competitive Context Low-Tier Competitive Context Figure 2. Passing competitor price scenarios 1 & 2

8 Scenario 3 (No Passing, Cheaper ) High-Tier Competitive Context Low-Tier Competitive Context Scenario 4 (No Passing, More Expensive ) High-Tier Competitive Context Low-Tier Competitive Context Figure 3. No passing price scenarios 3 & 4 Table 5. Average elasticities across different competitive price contexts Scenario 1 Scenario 2 Pass on Pass on Increase Decrease Scenario 3 No Passing, Comp. Below Scenario 4 No Passing, Comp. Above High-Tier s Increase -4.3* Decrease * Average Low Tier s Increase -1.8* Decrease * Average * change passed a competitor s price Table 5 displays the elasticities across the different price scenarios, competitor price tiers and price change directions. The results indicate that brand price elasticities are greatly context-dependent. For instance, average elasticities for equivalent price decreases ranged from -0.4 to -10. Larger elasticities were observed when passing competitor prices in both the high-tier and low-tier competitor contexts. However, these contexts appear to influence the size of this effect, with greater response to these price changes in the high-tier competitor contexts. This is inline with an overall trend of larger elasticities when competing against the more expensive brands across most scenarios (except scenario 4). The average elasticity when passing a competitor to become the cheapest brand (price scenario 2, high-tier context) was -10. This was by far the largest observed across

9 different situation. The opposite situation, in which a brand increases to become he most expensive brand (price scenario 1, low-tier context), produced a much smaller response, with an average elasticity of only Brand Usage To address the effects of consumers prior brand usage (RQ4 and RQ5), respondents have been classified into three usage segments for each brand. The heavy user segment includes respondents who use the brand, on average, at least once a month. The light users segment is constructed of those that usually use the brand at least once a year, but not more frequently that once a month. The respondents that claimed to rarely or never use a brand were classified as non-users. Table 6 reports that the average elasticities across different users of the focal brand (i.e. brand changing price). These results indicate smaller elasticities among heavy users of a brand, which is in line with findings from prior research on the topic (e.g., Krishnamurthi and Raj 1991, Kalyanaram and Little 1994, Scriven and Ehrenberg 2004, Dawes 2009). Table 6. Average elasticities across the focal brand usage segments Focal Brand Usage Heavy User Light User Non-User Beer Pasta Sauce Toilet Paper Bread Laundry Detergent Shampoo Avg. Pass No Pass Pass No Pass Pass No Pass The competitor passing effect is evident across all usage segments and there appears to be relationship with prior brand usage. The size of the passing effect is smaller among the heavy brand users. The average elasticities also show that the passing elasticities are smaller for light-users (-5.9) than for non-users (-8.1). However, analysis of the individual categories shows that there are also instances when the elasticities are larger among light-users than among non-users (beer, pasta sauce, laundry detergent). Additionally, table 7 six reports the results split by usage of the brand that is being passed. The results follow the opposite direction of the focal brand usage segments. Overall, heavy users of the competitor brand were the most responsive to price changes of the focal brand. Table 7. Average elasticities across the competitor brand usage segments Pasta Toilet Laundry Beer Bread Brand Usage Sauce Paper Detergent Shampoo Avg. Heavy User Pass No Pass Light User Pass No Pass Non-User Pass No Pass

10 Again, prior brand usage shows a relationship with the passing competitor effect. In this case, the largest elasticities were observed among respondents who were heavy users of the brand that was passed (-7.5). Interestingly, even the non-users of the competitor brand were still more responsive to price changes that passed this brand, albeit to a lesser degree (average elasticity -3.5). Summary The results of this study provide further support for Scriven and Ehrenberg s (2004) finding that price changes passing competitor prices produce larger brand price elasticities. This was found to hold for both price increases and price decreases across different brands, product categories, competitive contexts and usage segments. However, the strength of this effect varied systematically across those conditions. With regards to price change direction, this research indicates a greater response to price decreases passing a cheaper brand than price increases passing a more expensive brand. The prices of the brands in the wider competitive set also appear to have an effect, with greater elasticities when competing against high-tier brands. In addition to these contextual effects, the results indicate that prior usage experience influences consumers responses to price changes passing the competition. Smaller elasticities have been observed for heavy users of the focal brand, while larger elasticities are the norm for heavy users of the competitor brand.

11 References Bell, D. R., et al. (1999). "The Decomposition of Promotional Response: An Empirical Generalization." Marketing Science 18(No. 4): Bijmolt, T. H. A., et al. (2005). "New empirical generalizations on the determinants of price elasticity." Journal of Marketing Research XLII(May): Bolton, R. N. (1989). "The Relationship Between Market Characteristics and Promotional Elasticities." Marketing Science 8(2): Danaher, P. J. and R. J. Brodie (2000). "Understanding the Characteristics of Elasticities for Frequently Purchased Packaged Goods." Journal of Marketing Management 16: Dawes, J. (2009). "The effect of service price increases on customer retention: the moderating role of customer tenure and relationship breadth." Journal of Service Research 11(3): Ehrenberg, A. S. C. and L. R. England (1990). "Generalising a pricing effect." The Journal of Industrial Economics 39(September): Fok, D., et al. (2006). "A hierarchical bayes error correction model to explain dynamic effects of price changes." Journal of Marketing Research 43(3): George, J., et al. (1996). "Variations in Elasticities." European Journal of Operational Research 88: Hamilton, W., et al. (1997). "The Measurement and Utility of Brand Elasticities." Journal of Marketing Management 13(No. 4): Kalyanaram, G. and J. D. C. Little (1994). "An Empirical Analysis of Latitude of Acceptance in Consumer Package Goods." Journal of Consumer Research 21(December). Krishnamurthi, L. and S. P. Raj (1991). "An Empirical Analysis of the Relationship Between Brand Loyalty and Consumer Elasticity." Marketing Science 10(2): Litvack, D. S., et al. (1985). "An Examination of Short-Term Retail Grocery Effects." Journal of Retailing 61(3): Motes, W. H. (1987). "Replication of Pricing Effects on Brand Choice Behaviour." European Journal of Marketing 21(1): Narasimhan, C., et al. (1996). "Promotional Elasticities and Category Characteristics." Journal of Marketing 60(April): Scriven, J. and A. Ehrenberg (2004). "Consistent Consumer Responses to Changes." Australasian Marketing Journal 12(3):

12 Sethuraman, R. (1996). "A Model of How Discounting High-d Brands Affects the Sales of Low-d Brands." Journal of Marketing Research 33(November): Sivakumar, K. and S. P. Raj (1997). "Quality tier competition: how price change influences brand choice and category choice." Journal of Marketing 61(July): Tellis, G. J. (1988). "The Elasticity of Selective Demand: A Meta Analysis of Econometric Models of Sales." Journal of Marketing Research 25(November): Woodside, A. G. and T. Ozcan (2009). "Customer choices of manufacturer versus retailer brands in alternative price and usage contexts." Journal of Retailing and Consumer Services 16(2): Zenor, M. J., et al. (1998). "The impact of marketing policy on promotional price elasticities and baseline sales." Journal of retailing and consumer services 5(1):

13 Appendix 1 Experimental Design Specifications Table 8. Beer design specifications Beer Alternative Type Brand Regular ($) Decrease ($) 1 Change Coors Light Change Budweiser High Tier Corona Extra High Tier Heineken Low Tier Miller High Life Low Tier Pabst Blue Ribbon Table 9. Pasta sauce design specifications Pasta Sauce Alternative Type Brand Regular ($) Increase ($) Decrease ($) 1 Change Prego Change Ragu High Tier Nature s Promise High Tier Classico Low Tier Del Monte Low Tier Hunt s Table 10. Toilet paper design specifications Toilet Paper Alternative Type Brand Regular ($) Increase ($) Decrease ($) 1 Change Conttonelle Change Charmin High Tier Seventh Generation High Tier Scott Low Tier Angel Soft Low Tier White Cloud Table 11. Bread design specifications Bread Alternative Type Brand Regular ($) Increase ($) Decrease ($) 1 Change Brownberry Change Sara Lee High Tier Pepperidge Farm High Tier S. Rosens Low Tier Butternut Low Tier Sunbeam Increase ($)

14 Table 12. Laundry detergent design specifications Laundry Detergent Alternative Type Brand Regular ($) Decrease ($) 1 Change All Change Purex High Tier Wisk High Tier Gain Low Tier Era Low Tier Great Value Table 13. Shampoo design specifications Shampoo Alternative Type Brand Regular ($) Increase ($) Decrease ($) 1 Change Garnier Fructis Change Herbal Essences High Tier L Oreal Advanced High Tier Pantene ProV Low Tier CVS Low Tier Suave Increase ($)

15 Appendix 2 Brand level elasticity results Table 14. Beer brand-level elasticity results Scenario 1: Scenario 2: Scenario 3: Scenario 4: Beer Pass Increase Pass Decrease Below Above Comp Tier High Low High Low High Low High Low Alt 1 Increase (Coors Light) Decrease Alt 2 Increase (Budweiser) Decrease Average Increase Decrease Table 15. Pasta sauce brand-level elasticity results Scenario 1: Scenario 2: Scenario 3: Scenario 4: Pasta Sauce Pass Increase Pass Decrease Below Above Comp Tier High Low High Low High Low High Low Alt 1 Increase (Prego) Decrease Alt 2 Increase (Ragu) Decrease Average Increase Decrease Table 16. Toilet paper brand-level elasticity results Scenario 1: Scenario 2: Scenario 3: Scenario 4: Toilet Paper Pass Increase Pass Decrease Below Above Comp Tier High Low High Low High Low High Low Alt 1 Increase (Cottonelle) Decrease Alt 2 Increase (Charmin) Decrease Average Increase Decrease Table 17. Bread brand-level elasticity results Scenario 1: Scenario 2: Scenario 3: Scenario 4: Bread Pass Increase Pass Decrease Below Above Comp Tier High Low High Low High Low High Low Alt 1 Increase (Brownberry) Decrease Alt 2 Increase (Sara Lee) Decrease Average Increase Decrease

16 Table 18. Laundry detergent brand-level elasticity results Scenario 1: Scenario 2: Scenario 3: Scenario 4: Laundry Detergent Pass Increase Pass Decrease Below Above Comp Tier High Low High Low High Low High Low Alt 1 Increase (All) Decrease Alt 2 Increase (Purex) Decrease Average Increase Decrease Table 19. Shampoo brand-level elasticity results Scenario 1: Scenario 2: Scenario 3: Scenario 4: Shampoo Pass Increase Pass Decrease Below Above Comp Tier High Low High Low High Low High Low Alt 1 (Garnier Increase Fructis) Decrease Alt 2 (Herbal Increase Essences) Decrease Average Increase Decrease Table 14. Average brand-level elasticity results (all categories) Average (All Categories) Scenario 1: Pass Increase Scenario 2: Pass Decrease Scenario 3: Below Scenario 4: Above Comp Tier High Low High Low High Low High Low Alt 1 Increase Decrease Alt 2 Increase Decrease Average Increase Decrease