Brand-Pack Size Cannibalization Arising from Temporary Price Promotions

This study investigates how price promotions for one pack-size of a brand steal sales from the other pack-sizes of the same brand. To do so, the study examines twelve grocery product categories (seven US, three UK, two Australian). The analysis finds heavy cross-pack cannibalization. On average, 22 percent of the sales uplift for a promoted brand-pack size comes from other pack sizes of the same brand. Cross-pack cannibalization most typically occurs in the week of the promotion, but also transfers future week's sales away from the non-promoted pack size in 31 percent of cases. The study finds higher cannibalization is associated with packs that sell for a higher dollar value than others sold under the same brand; whereas higher price-per-weight, a packaging difference, and the item having a larger relative share of sales in the brand portfolio, are linked to lower cannibalization. Also examined is the impact of pack-size cannibalization on promotion profitability for retailer PLs. That analysis finds PL price promotions have generally negative impacts on PL profits, and that pack-size cannibalization exacerbates this negative outcome. The results suggest both retailers and manufacturers should carefully consider pack-size cannibalization when evaluating the outcome of temporary price promotions. The study also provides some evidence-based recommendations from which managers can attempt to minimize such cannibalization.     

Optimal retail sales strategies for old and new products in monopoly and horizontal competition scenarios

Advances in technology have made product updates more frequent and allowed consumers to choose different versions of the same product based on their preferences. It is crucial for retailers to understand how to formulate optimal sales strategies based on those different consumer preferences. To this end, we develop game models that consider the heterogeneity of consumer preferences under both monopoly and horizontal competition scenarios and perform the sensitivity analysis to examine the impact of consumer proportions and consumer preferences on retailers’ sales strategies. The results show that (i) regardless of competition or monopoly status, the original retailer can always maximize profit by setting prices based on the market share of traditional consumers, as long as the retailer sells both new and old versions of the product; (ii) the greater the competitive advantage of the competitor, the more advantageous the hybrid sales mode; (iii) if the price of the old product is below a certain threshold, there will be a positive profit for the original retailer when selling both the old and new products; and (iv) when consumer acceptance of competing retailers is lower, entering the retail market is not a good choice for competing retailers.     

Estimating cannibalizing effects of sales promotions: The impact of price cuts and store type

To evaluate the financial impact of supermarket sales promotions, managers must estimate how much new demand comes from cannibalizing the base product compared with other sources. However, investigations into cannibalization are scant. Using vector autoregression analytical framework applied to three years of supermarket scanner data, and sales promotions for pound cake, we estimate cannibalization effects for two common price reductions (10% and 15%), across large, medium and small supermarkets. The sales bumps varied across supermarkets for each price cut while cannibalization effects were substantial only in large supermarkets, with moderate effects in medium stores and no effects in small supermarkets.     

Consumer perceptions of monetary and non-monetary introductory promotions for new products

Abstract

Little research has examined how consumers respond to sales promotions in new product categories. This article fills this gap by integrating research on reference prices with literature on sales promotions for new product categories. Existing research suggests that consumers respond more favourably to non-monetary promotions (e.g. extra free promotions) than monetary promotions (e.g. price discounts) because non-monetary promotions are framed as segregated gains rather than reduced losses. However, both kinds of promotions are widely used in practice, suggesting the importance of other contributory factors. With a consumer experiment on a national panel of consumers, this research demonstrates that extra free product promotions are most preferred for existing products, and introductory low-price promotions are preferred for innovative products. The moderating effect of a product's innovativeness is explained via a new relationship in the marketing literature, whereby perceived risk mediates the relationship between perceived innovativeness and a consumer's tendency to stockpile.     

On consumer choice patterns and the net impact of feature promotions

Even in the digital age, feature promotions continue to receive significant investments from CPG manufacturers and retailers. Whether this is money well spent depends on consumers' (heterogeneous) tendency to switch brands or stores in response to features. This study proposes a ‘Mixed-pattern Random-effects Nested Logit’ (MRNL) model to analyse the effect of feature promotions in a multi-retailer multi-brand setting. Across 16 different CPG categories, our results reveal that in all cases a mixture of choice patterns prevails: about half of households exhibit a brand focus (i.e. rather substitute between stores offering that brand), the remaining half show evidence of a store focus (i.e. rather substitute brand offers within a visited store). We find that the size of the promotion lift and its underlying sources differ substantially between patterns. Brand-focused consumers are generally more responsive to feature ads than store-focused consumers – especially in low-concentration categories; while they imply much stronger cannibalization for the manufacturer, and much weaker cannibalization for the retailer. It follows that retailers reap much higher benefits in the brand-focused segment, while manufacturers may not prefer that segment in terms of net gains and must be wary of subsidizing those consumers. We identify household and category characteristics that underlie the choice patterns and offer opportunities for targeting.     

Pre-launch Prediction of Market Performance for Short Lifecycle Products Using Online Community Data

Prediction of sales for short life-cycle products can be problematic. Generic predictive models based on past launches may provide only crude historic data which are unsuited for distinctive, innovative products. This paper investigates the role of online communities in providing pre-launch data to predict post-launch sales. We argue that levels of awareness, word-of-mouth, expectations, and adoption intention prevailing within an online community for an upcoming product have an independent direct effect on the product's future sales. Additionally, we test the complementarity effect of these community variables by introducing a higher order construct called Pre-release Community Buzz, to demonstrate the incremental explanatory power of using pre-launch community variables to predict post-launch sales. Data for community variables were collected from a movie-based online community, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). We found strong support for both direct and complementarity effects of community variables in predicting a movie's opening week sales. We also found that community variables mediate the effects of generic predictor variables such as MPAA ratings, star cast, production budget and competition on opening week sales. Tests for robustness demonstrated the value of community variables. Models which included community variables had higher predictive power than those without. Implications for theory and practice are presented.     

Product-Type Moderating Effects on Short-Term Demand for Reduced Price Convenience Goods

Abstract

A field experiment within a supermarket chain found that demand sensitivity to price reductions varied sharply between product categories according to whether the product was a stock-up good, increased consumption good or a non-consumption increase good. Following a price reduction, stock-up goods and increased consumption goods were both elastic while non-stock up goods showed much less sales change. While stock-up goods then showed later lagged decreases in sales as consumers extend their savings, increased consumption goods returned to previous sales levels. The results imply simple but useful pricing strategies for grocery retailers.     

Is Online Word of Mouth Higher for New Models or Redesigns? An Investigation of the Automobile Industry

Changing consumer preferences, entry of new competitors with better products, and product improvements by existing competitors make new products a necessary investment for most companies. In addition to the investments in R&D and production of new products, firms also need to invest in advertising to promote them. The growing use of social media by consumers therefore makes online consumer conversations an attractive additional format for firms to promote products at a lower cost. This is particularly so in the automobile industry where advertising costs are very high. Whether consumers discuss a newly introduced product, and help to promote it, however, may depend on how new the product is. This is the question that we investigate in the context of the automobile category. Specifically, we examine whether online consumer conversations are more likely for new models (e.g., Chevy Volt introduced in 2010) or redesigns of existing models (e.g., the redesign of Chevy Impala in 2010). We use data from two online sites where consumers discuss automobiles – consumerreports.org and edmunds.com – for our analysis. Our empirical investigation also accounts for the effects of sales on word of mouth and the simultaneity between sales and word of mouth. Additionally, we also consider the effect of satisfaction on word of mouth and the endogeneity of satisfaction. Our results across two datasets suggest that redesigns stimulate significantly more conversations than new models. Managerial and research implications of the findings are discussed.     

The timing of version releases: A dynamic duopoly model

In many R&D-intensive consumer product categories, firms deliver value to consumers through the quality enhancements provided by new and improved versions of existing products. Therefore, important marketing decisions relate to a firm’s strategy for developing quality enhancements and releasing new versions. This paper explores this type of product development using a dynamic duopoly model that endogenizes each firm’s decisions over how much to invest in R&D and when to release new versions. Specifically, I explore how two key industry fundamentals—the degree of horizontal differentiation and the cost of releasing a new version—affect firms’ product development strategies and, accordingly, the evolution of industry structure. I find that varying the degree of horizontal differentiation gives rise to three distinctly different types of competitive dynamics: preemption races when the degree of horizontal differentiation is low; phases of accommodation when it is moderate; and asymmetric R&D wars when it is high. Furthermore, I find that an increase in the cost of releasing a new version can induce firms to compete more aggressively for the lead and, in doing so, release new versions more frequently despite the higher cost.     

Multichannel customer purchase behavior and long tail effects in the fashion goods market

The fast-paced growth of e-commerce is impacting the type and variety of products consumers purchase across channels. A commonly held theory, known as long tail theory, posits that online sales are less concentrated at the top of the sales distribution than offline sales, and that more variety is bought online, making the tails of the overall sales distribution denser with the growth of e-commerce. Most of the literature testing the long tail theory has focused on examining entertainment goods markets that do not require much physical examination, and has predominantly found results consistent with the theory. However, the magnitude and antecedents of the observed long tail effects might be different for product categories containing products that require more physical examination before purchase, such as fashion goods. In this study, using detailed individual and transaction level panel data from two multichannel fashion goods retail brands, we show that while the shift to the online channel results in a decrease in the concentration of overall sales for both brands, this change mostly results from consumers buying different products online rather than consumers buying a greater variety online compared to offline. We show that the flattening of the overall sales distribution with the growth of e-commerce in our data is driven by consumers sorting their purchases into channels based on product characteristics. In contrast to the recommendations from the previous long tail literature, our results show that fashion apparel retailers do not need to offer broader assortments online compared to offline, but they may find it profitable to carry or emphasize a different product mix online compared to offline. Our results also provide guidance to fashion goods retailers in curating their online and offline assortments and setting inventory management strategies across the channels.     

Consumer Product Redistribution

Abstract

Formats for product redistribution are emerging and evolving, creating alternative channel options for consumers' disposition of unwanted possessions. These retail formats operate in both informal (e.g., garage sales) and formal (online auctions) economies. As consumers participate in redistribution channels, some retailers are confronted with new competition and the potential for declining sales. This article expands on both recycling and disposition literature by examining consumer disposition behavior and the flow of used products through various redistribution channels. Strategies are offered to address consumer disposition behaviors as well as to assist retailers in combating traditional and non-traditional competition.     

The Impact of Price-Based and New Product Promotions on Fast Food Restaurant Sales and Stock Prices

A key tool used in demand or revenue management marketing strategies is the application of pricing tactics based on anticipated demand to enhance both customer utility and maximize firm performance (Wirtz et al., 2003). In the restaurant segment, particularly in quick-service restaurants (QSR), organizations focus on two main promotion formats to attract customers: price-based promotions and new product promotions. The purpose of this article is to explore how the number of price-based promotions and new product promotions influence firm sales growth or decline and change in stock prices. Results suggest that new product promotions can have a significant and positive effect on same store sales, whereas price-based promotions tend to results in lower same-store sales changes and changes in stock price. As an additional control for these results, the study controls for economic and seasonal conditions effects.     

An Assessment of When,Where and Under What Conditions In-Store Sampling is Most Effective

In-store product sampling is a commonly used promotional technique designed to give prospective consumers an opportunity to experience a product prior to purchase. While prior research has documented a positive relationship between short-term sales and perceptual measures of the customer shopping experience, little is known about the long-term impact of sampling or factors that moderate its success. In this paper, we develop an empirical approach that allows us to study the short-term and long-term effects of in-store sampling on both own and competitive products. We apply our approach to six store-level scanner data sets across four different product categories and show that in-store sampling has both an immediate (short-term) and sustained (long-term) impact on sales. We also show that the impact of sampling on sales is moderated by the characteristics of the store conducting the event, and that repeated sampling for a single product leads to a multiplicative increase in its long-term sales performance. We find that, unlike many types of in-store promotion, sampling results in a category expansion effect as opposed to a pure substitution effect. We contrast the immediate and long-term sales patterns for in-store sampling to those of product displays and discuss managerially relevant differences. Finally, we demonstrate incremental profit implications and store selection scenarios for different incremental costs of conducting the in-store events using constrained optimizations.     

Durable Goods Monopoly,Buyer Uncertainty,and Concurrent Selling and Renting

Stylized durable goods monopoly models typically conclude that monopolists prefer to rent their output due to commitment problems associated with sales. However, we commonly observe monopolistic firms in durable goods industries simultaneously selling and renting output. To address this apparent discrepancy a simple two‐period asymmetric information model is constructed where buyers are uncertain of the good's durability and the firm's manufacturing costs. This is a natural asymmetric information specification since the firm typically has more precise knowledge of product durability and production costs than buyers do. The analysis indicates that a monopolist may wish to concurrently sell and rent output when buyers do not have perfect knowledge. If, for example, consumers believe that product durability and manufacturing costs are higher than they truly are, the firm may wish to simultaneously sell and rent output. Thus buyers' expectations about firm costs and product durability are of critical importance in durable goods models, particularly in terms of explaining concurrent rentals and sales.     

The influence of demand factors on dynamic competitive pricing strategy: An empirical study

This empirical paper investigates the relationship between the dynamic strategic interactions among competitors in a component market and demand factors in the market for the end product. The structure of competition in the US microprocessor (MPU) industry is analyzed using data on prices and sales in both the MPU market as well as the market for personal computers. The pattern of dynamic strategic interaction between competing firms in this market on a key decision variable, price is studied. Non-nested model comparison tests based on equilibrium solutions derived for specific differential games are applied to identify the mode of competitive strategy between pairs of competing brands. The empirical fit to the longitudinal and cross-sectional data, of alternative models of competition, independent (Bertrand?CNash), Stackelberg leader?Cfollower, and Collusion, is used to determine which dynamic model best describes actual competitive behavior over the life of each MPU. Demand for the product market which is downstream from microprocessors, that for personal computers, is estimated using a generalized diffusion model with price effects. Data from the markets for desktop and laptop computers are analyzed at the level of computer vendor and internal microprocessor. Patterns are uncovered, linking downstream demand parameters with upstream competitive strategy. There is evidence to suggest that when there are strong diffusion effects driving sales of both the competing computer brands, there is a higher likelihood of Bertrand?CNash competition among MPU firms. However, when there are higher cross-price effects (substitutability) among personal computer brands there is a greater chance of Stackelberg leader?Cfollower price competition. When self-price effects are relatively high, the likelihood of Bertrand?CNash competition among MPU firms increases. Furthermore, when the potential demand for the computer product category is high, there is a higher likelihood of Bertrand?CNash pricing in the MPU market.     

Acquiring customers through online marketplaces? The effect of marketplace sales on sales in a retailer's own channels

Online retailers are increasingly using third-party online marketplaces (e.g., Amazon, Taobao) as an alternative sales channel to their website. While cross-channel sales elasticities have been established for many sales channel combinations (e.g., adding bricks to clicks), we lack an understanding of whether the use of third-party marketplaces grows or cannibalizes a retailer's sales. Practitioners argue that firms can build their e-commerce business through acquiring customers by selling on the marketplace. Indeed, a marketplace could complement a retailer's offering (e.g., acquiring new customer segments), although inventory effects might mitigate this complementarity. Alternatively, cannibalization might occur from losing customers from one's website to the online marketplace. The present research investigates which of the two opposing forces prevails using a time series of category sales data from one of the largest global marketplace sellers. The authors use vector autoregressive modeling to show that marketplace sales increase sales on a retailer's website (0.014% for every 1% in marketplace sales). This effect is strongest for categories with large choice and low product prices. Acquiring customers through the marketplace might be cheaper than through other sources (estimated at 24% of initial sales). However, online retailers should be aware that this strategy strengthens the marketplace and may have potential negative long-term consequences (e.g., through marketplace control of the customer relationship).     

How online reviews and coupons affect sales and pricing: An empirical study based on e-commerce platform

With rapid economic growth largely fueled by digital technologies, online reviews are among the new wave of technologies that still make a significant contribution to this new digital economy. However, there is scarce academic research in promoting or responding online reviews using reduction coupons with threshold issued by sellers and pricing decisions. We employ a three-stage least squares (3SLS) model to estimate the effects of online reviews and coupons on online product sales and price. We also extend our research using the data of two product categories. Our results mainly include: (1) Negative impact of negative online reviews on sales is moderated by price, and consumers are more tolerant of negative reviews of high-priced products. (2) Consumers' perceived usefulness of online coupons helps promote more sales and weaken the relationship between negative reviews and sales. (3) Positive online reviews weaken the negative relationship between online negative reviews and the price of product. (4) Consumers’ increased perceived usefulness of online coupons will encourage sellers to set a higher price and weaken the negative relationship between negative reviews and the price of product. (5) Compared with the search product, sellers regard negative reviews from the product with experience attributes as less helpful and apply less effective coupon promotion to response to negative reviews. Our study clarifies the interaction between online reviews and online coupons on e-commerce platforms under the operation scenario. We also provide empirical support for accurate promotion and higher sales revenue through reasonable pricing decisions and specified reduction coupons.     

Substitution or Promotion? The Impact of Price Discounts on Cross-Channel Sales of Digital Movies

Technology is transforming the marketing function in many ways, and this transformation is particularly apparent for information goods such as movies where digital technologies provide marketers with new distribution channels, which in turn create new opportunities for cross-channel effects. However, these digital channels also provide researchers with new opportunities to measure micro-level customer behavior to understand the impact of cross-channel effects in real-world settings.In this paper, we study cross-channel effects between movies sold in digital purchase (commonly known as Electronic Sell Through or EST) and digital rental (commonly known as Video-On-Demand or VOD) markets. We do this using a unique sales dataset from a major digital movie retailer provided by a major movie studio. Our analysis takes advantage of a 14-week field experiment that allows us to measure the impact of price discounts on own- and cross-channel sales. We use this experiment to estimate own and cross price elasticities, whether price discounts cannibalize future sales, and most importantly whether price discounts in one channel affect sales for the same product in a presumably competing channel.Our analysis indicates that digital movie consumers are highly sensitive to price promotions. However, we also find that, contrary to expectations, price promotions in a digital sales channel for a movie do not seem to cannibalize digital rentals. Indeed, our results suggest that, if anything, price promotions for digital movie sales can increase digital rentals. We explore a variety of explanations for this counterintuitive result, including the possibility that the ease of information transmission online through third-party websites, blogs, and online discussion areas may create information spillovers such that price discounts in one channel may increase product awareness in other competing sales channels. From a managerial perspective, our results suggest that cross-channel cannibalization can be reduced or even reversed in the presence of information spillovers, and that there are many new opportunities for marketers to directly measure these cross-channel effects using experimental data from online platforms.     

A Micromodel of New Product Adoption with Heterogeneous and Forward-Looking Consumers: Application to the Digital Camera Category

We develop an empirical model for the adoption process of a new durable product that accounts for consumer heterogeneity as well as consumers forward-looking behavior. Accounting for heterogeneity is important for two reasons. As the mix of consumers with different preferences and price sensitivities could change over time, firms need to update their marketing strategies. Further, it allows for a variety of shapes for the aggregate adoption process over time. As prices for durable and technology products fall over time with firms continually introducing enhanced products, consumers may anticipate these prices and improvements and delay their purchases in the product category. Forward-looking consumers optimize purchase timing by trading off their utilities from buying the product and their expectations on future prices, quality levels, and brand availability. Such forward-looking behavior will result in price dynamics in the marketplace as price changes today influence future purchases. And it results in different shapes of the new product sales pattern over time by influencing the time to take-off. We show how the parameters of our model can be estimated using aggregate data on the sales, prices, and attributes of brands in a product category. We apply our model to market data from the digital camera category. Our data are consistent with the presence of both heterogeneity and forward looking behavior among consumers. At the product category level, we are able to decompose the effects of the entry of Sony into primary demand expansion and switching from other brands. At the brand level, we find that there exist several segments in the market with different preferences for the brands and different price sensitivities leading to differences in adoption timing and brand choice across segments. For a given brand, we show how the changing customer mix over time has implications for that brands pricing strategies. We characterize how price effects vary across brands and over time and how price changes in a given time period influence sales in subsequent periods. Model comparison and validation results are also provided.