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.     

Identifying Sales Performance Gaps with Internal Benchmarking

This research investigates how retailers can benefit from identifying the sales growth potential of in-store salespeople in every product category. The proposed novel approach helps retailers develop an equitable evaluation of their sales force, using both observable and unobservable factors that affect sales. By extending stochastic frontier regression to a multivariate case, the resulting factor-analytic frontier formulation leverages the correlation pattern of sales across product categories and salespeople over time. A unique data set, from a franchise chain with 481 salespeople, operating in 35 stores and selling 11 related product categories, identifies a gap between observed category profits and an estimated profit frontier for each salesperson and category. This novel model also can benchmark each salesperson against all others across product categories while accounting for observable and unobservable factors. This approach has practical value, in that retailers can identify both top-performing salespeople and underperformers, who then might be matched to establish a positive learning environment that aligns top performers with proven sales expertise in a product category with peers who struggle with that category.     

Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google.com

We investigate the cross channel effects of search engine advertising on Google.com on sales in brick and mortar retail stores. Obtaining causal and actionable estimates in this context is challenging: Brick and mortar store sales vary widely on a weekly basis; offline media dominate the marketing budget; search advertising and demand are contemporaneously correlated; and estimates have to be credible to overcome agency issues between the online and offline marketing groups. We report on a meta-analysis of a population of 15 independent field experiments, in which 13 well-known U.S. multi-channel retailers spent over $4 Million in incremental search advertising. In test markets category keywords were maintained in positions 1-3 for 76 product categories with no search advertising on these keywords in the control markets. Outcomes measured include sales in the advertised categories, total store sales and Return on Ad Spending. We estimate the average effect of each outcome for this population of experiments using a Hierarchical Bayesian (HB) model. The estimates from the HB model provide causal evidence that increasing search engine advertising on broad keywords on Google.com had a positive effect on sales in brick and mortar stores for the advertised categories for this population of retailers. There also was a positive effect on total store sales. Hence the increase in sales in the advertised categories was incremental to the retailer net of any sales borrowed from non-advertised categories. The total store sales increase was a meaningful improvement compared to the baseline sales growth rates. The average Return on Ad Spend (ROAS) is positive, but does not breakeven on average although several retailers achieved or exceeded break-even based only on brick and mortar sales. We examine the robustness of our findings to alternative assumptions about the data specific to this set of experiments. Our estimates suggest online and offline are linked markets, that media planners should account for the offline effects in the planning and execution of search advertising campaigns, and that these effects should be adjusted by category and retailer. Extensive replication and a unique research protocol ensure that our results are general and credible.     

Predicting Under- and Overperforming SKUs within the Distribution–Market Share Relationship

This research presents a retail analytics application which uses machine learning (ML) to identify and predict under- and overperforming consumer packaged goods (CPGs) using retail scanner data. Essential to measuring market performance at the SKU level is the relationship between distribution and market share (the velocity curve). We validate that ML can reproduce the velocity curve, and ML is further used to predict underperforming, in-line performing, and overperforming SKUs relative to the velocity curve, based on a range of variables (SKU features) at a point in time. Our ML approach can correctly predict 83% of SKUs as under-, in-line-, or overperforming based on their characteristics. The research analyzes 9,321 SKUs of 2,565 brands across seven product categories of CPGs which were sold in 8,117 stores from 49 different retail chains of five different retail channels located in the US states of California, New York, Texas, and Wisconsin. The retail stores comprise convenience stores, drug stores, food stores, liquor stores, and mass merchandise retail stores. The data is Nielsen retail store scanner data for the calendar year 2014. The relationship between distribution and market share is a market-wide proxy for the ratio of relative sales in a category to, for example, aggregate shelf space, a key retail productivity metric. We further find indications that the distribution of SKUs across different store sizes, the stores’ category specialization, the line length of the brands, the overall performance of the parent brand, and sales consistency are the most important characteristics for the prediction of market share performance beyond the velocity curve. The methods and results presented will help CPG marketers (suppliers and retailers) understand which SKUs are under-, in-line-, or overperforming and the potential factors contributing to that performance. Optimizing assortments and portfolios is essential to decrease failure rates of individual SKUs. ML approaches can evolve to complementary support tools for such management problems.     

考虑零售商销售努力的双渠道供应链定价策略研究

随着电子商务市场的日益成熟,制造商建设线上直销渠道来适应新的商品销售环境成为趋势。制造商线上直销渠道的建立占领了部分原本属于线下零售渠道的市场份额,对线下零售渠道造成冲击。针对双渠道供应链中的竞争,将零售商销售努力行为考虑在内,通过构建博弈模型分别研究了在集中决策模式和分散决策模式下,制造商与零售商的定价策略。研究发现,在集中决策模式下,线下零售渠道与线上直销渠道之间的价格差异随着两个渠道潜在需求量之间差异的增大而增大,并且两个渠道的最优价格分别与其市场潜在需求成正比。在分散决策模式下,两个渠道的最优价格亦与潜在需求成正比,并且线下零售渠道的最优价格随零售商销售努力程度的增加而增加,线上直销渠道的最优价格随着零售商销售努力程度的增加而减少。     

Decomposing the effect of advertising: What happens in the retail channel?

The diverging interests of manufacturers and retailers famously give rise to the double marginalization problem but have consequences far beyond pricing. Advertising is another marketing instrument that is under the control of the manufacturer but its ultimate effect on consumer demand also depends on retailers’ pricing decisions. We decompose the effect of advertising in the channel and highlight an additional route through which advertising affects sales, namely via the changes in the retail price that a strategic retailer makes in response to changes in demand following manufacturer advertising. The total demand effect of advertising thus comprises the direct effects of advertising on market shares, and the indirect effects coming through adjustments that the retailer makes to the in-store prices of all the brands in a given product category in response to the shifted demand due to advertising. We match advertising data for four different categories (both food and non-food) to store-level scanner panel data, which also include information on wholesale prices. Controlling for wholesale prices, we establish in a reduced-form model that the retailer reacts to manufacturer advertising by changing retail prices instead of simply imposing a constant markup on the wholesale price. To further explore the role of the strategic response of the retailer in a systematic fashion and quantify the effects derived in the decomposition, we estimate a discrete-choice model of demand and determine the magnitude of the direct and indirect effects. We find that the indirect effect of advertising through retailer prices is about half the size of the direct effect, and thus substantively affects advertising effectiveness.     

The Effects of Search-Related and Purchase-Related Mobile App Additions on Retailers’ Shareholder Wealth: The Roles of Firm Size,Product Category,and Customer Segment

Mobile channel additions have been shown to increase consumer-brand relationships, brand satisfaction towards and overall purchasing from a retailer, but what is less apparent is whether shareholders are fully rewarded for retailers’ mobile channel additions. Results from an event study on 115 announcements relating to mobile app additions of publicly traded U.S. retail firms between 2009 and 2016 indicate that the stock market responds generally positively to mobile app additions, but specifically to the two mobile app addition types. Stock market responses to search-related and purchase-related app additions are moderated by firm size, product category, and target customer age. For announcements of search-related apps, the market responds more positively to product retailers than to service retailers, and to small firms than large ones. For announcements of purchase-related apps, the market responds less positively to firms that target younger customers than firms who do not especially target them.     

Modifying Conjoint Methods to Model Managers' Reactions to Business Environmental Trends: An Application to Modeling Retailer Reactions to Sales Trends

This article proposes and demonstrates how conjoint methods can be adapted to allow the modeling of managerial reactions to various changes in economic and competitive environments and their effects on observed sales levels. Because in general micro-level data on strategic decision making over time are difficult and expensive to obtain, this approach can be of much value to the further study of managerial strategic behavior and market dynamics. In our application we model retailer reactions to changes in their sales, focusing in particular on the actions that affect the demand for retail space and possibilities to improve retail sites. Choice responses to hypothetical sales and environmental trend scenarios are collected from 183 retailers and used to estimate to logit regression model that predicts retailers' probabilities of choosing actions. The model results confirm that retailers are more likely to take action when sales go down than when they go up, and also that they react more quickly if sales go down. It is also found that retailers are more reluctant to change the positioning of their store when confronted with a sales increase than when confronted with a sales decrease. The model is compared with a non-experimental model that is based on retailers' reactions to the trends they report to have observed for their own stores. The article concludes with a discussion of the implications of this research for the further development of conjoint-like approaches to studying entrepreneurial behavior.     

The fight between store brands and national brands—What's the score?

In the Western world market shares for store brands have increased across all product categories. The competitive position of store brands compared to national brands may depend on the product category and a retail chain's overall brand assortment strategy. In order to investigate these possible chain and category effects we have selected five chains with different store brand strategies and three product categories that differ with respect to the number of strong national brands in a category. The results we report focus on the competitive position of store brands compared to national brands from a consumer point of view. We find that store brands are in a weak competitive position compared to national brands independent of category and retail chain brand assortment strategy.     

The effect of exclusive distribution on the sales of ready-made meals in online retail

This study examines the impact of exclusive distribution on sales for online retailers and the moderating effects of product assortment (width and depth) and within-category competitive intensity on this relationship. This study used panel data for 3285 ready-made meal products which are newly introduced from August 2018 to August 2021 at a leading online grocery retailer in Korea. The random-effects panel regression was applied to test the proposed model. The results show that exclusive distribution increases sales, and this effect is intensified with greater product depth and greater within-category competitive intensity. These findings provide useful implications for retailers to increase their likelihood of success when adopting an exclusive distribution strategy. This study also contributes to expanding the scope of the literature on the effect of exclusive distribution on sales in the context of online retail.     

The impact of weather on consumer behavior and retail performance: Evidence from a convenience store chain in China

Despite extensive use of weather data to adjust replenishment and inventory strategies in the retail industry, these companies do clearly know the effect of weather on consumer behavior and retail performance. How does weather affect consumers' purchasing behavior and thus retail performance? We study empirically these questions by analyzing more than 6 million transactions made by more than 1.62 million unique consumers at 146 convenience stores in a convenience store chain in China. We choose sun, rain, temperature, and air quality index as the main weather variables. We use the average number of items per order and the average price of each item in each order as indicators of consumer behavior, and use store daily sales as an indicator of retail performance. We found that under rainy weather, people will buy more products with higher item prices in one order. When temperature rises, people will buy fewer products with a lower item price in one order. In addition, sunny weather and rainy weather have a positive impact on daily sales than cloudy weather. Air quality has a negative impact on daily sales, while temperature has a positive impact on sales. Finally, we study the impact of weather on different product categories. We find that the results depend on the product category characteristics.     

The retailer's brand promotion strategy under competition: The impact of supply uncertainty

While retailers are committed to promoting product brands to increase sales quantity and brand visibility, retailers are exposed to supply uncertainty. Therefore, we explore the brand promotion strategies of retailers in a competitive model. We then investigate the decision model under three different brand strategies and explore the equilibrium outcomes of stakeholders under supply uncertainty. In addition, we analyze and discuss social welfare under different scenarios. The results show that when the promotion cost is high (i.e., the cost effect dominates the market expansion effect), neither retailer promotes the product brand. When the promotion cost is low (i.e., the market expansion effect dominates the cost effect), both retailers tend to promote the product brands. When the promotion cost and market expansion match each other, only one retailer promotes the product brand becomes the equilibrium strategy. It is worth noting that when both retailers promote the product brand, the retailer falls into a prisoner's dilemma. In addition, we find that the supply uncertainty level diminishes the cost affordability and the motivation of retailers to promote the product brands. Interestingly, the supply uncertainty level reduces the possibility of retailers being in a prisoner's dilemma. Besides, market expansion (supply uncertainty) contributes to improving (diminishing) social welfare.     

Which Products are More Responsive to In-Store Displays: Utilitarian or Hedonic?

In-store displays aim to boost sales of both utilitarian and hedonic products. Noting typical differences in the information processing and purchase behavior evoked by these product types, and building on congruency theory principles, the authors propose that different types of in-store displays (i.e., island, end-of-aisle, or shelf signage) are more appropriate for utilitarian versus hedonic products, and the use of price or product promotions might reinforce these effects. With a database that combines three data sources (scanner, observational, and survey), this article presents an analysis of a market share model at the SKU level. The results confirm that in-store displays have differential effects on sales, depending on their characteristics; congruency between the decision-making process of utilitarian versus hedonic products and the characteristics of in-store display types moderates their effectiveness in terms of SKU sales. Shelf signage strongly increases the sales of utilitarian products, whereas island and end-of-aisle displays increase sales of hedonic product categories more effectively. The use of congruent promotions creates synergistic influences that reinforce these effects. In particular, price promotions improve the impact of shelf signage on utilitarian products, and product promotions strengthen the impacts of island and end-of-aisle displays on hedonic products. These results extend prior research on in-store marketing actions and the nature of utilitarian versus hedonic products, as well as providing recommendations for retailers and manufacturers seeking to optimize their retail space and commercial budgets.     

Towards a Further Understanding of the Antecedents of Retailer New Product Adoption

In addition to the traditionally investigated profit-drivers of retail adoption, such as gross margin, trade support, consumer marketing support, and product uniqueness, the authors investigate to what extent relatively under-investigated variables, such as relationship variables and category variables, are potential antecedents of retailers’ new product adoption decisions. Based on a sample of 392 new product adoption decisions by buyers of a Dutch food retailer, the authors provide evidence that both relationship and category variables do matter in new product adoption decisions by retailers. They show a significant negative effect of relationship dependence, and a significant positive effect of relationship length on a retailer's new product adoption probability. Furthermore, the authors show that higher levels of expected category growth due to the new product introduction are associated with higher levels of retailer adoption probability. Finally, in contrast with all previous retail adoption studies, this study shows a significant, positive relation between the relative gross margin of the new product and the retailer adoption probability.     

The ‘online high street’ or the high street online? The implications for the urban retail hierarchy

The U.K. has the greatest proportion of online sales in Europe. This study seeks to explore the differential effects of online retailing on the (evolving) hierarchy of shopping centres by examining current trends and underlying forces. The overall objectives of the paper are to qualify and explore the influence of online retailing in the decision-making processes of leading retailers today; and to assess how virtual influences become manifest in the tangible built environment and have impacted the retail hierarchy? It differentiates online retail trends by sector and retailer size, and examines the consequences for different types of shopping centres. The empirical research is based on the changing location of stores of a major fashion retailer and interviews with three of Britain’s leading retailers that have seen the more substantial increase in online turnover in recent years. Major retailers are found to have integrated online offerings, such as click and collect, into a ‘multi-channel’ retailing approach. Online retailing has therefore become an inherent and central element within large retailers’ business and therefore real estate strategies, with considerations such as online marketplace penetration and possible ‘cannibalisation’ coming to the fore in decision-making about store location. Online retail sales are, to a degree, drawing sales away from shopping centres but its impact on the existing shopping hierarchy is largely to reinforce established long-term trends driven by the motor age and the shift to out of town retailing. This is symbolised by the largest ‘high street’ fashion retailer now having more branches in retail parks than town centres. Out of town shopping centres for example are benefitting because of the ease of goods collection offered by these locations.     

Retail environment and manufacturer competitive intensity

We study how the intensity of competition and the degree to which manufacturers enjoy market power depends on the retail environment in a given market. Past research has discussed the growing importance of retailers and the power they enjoy over manufacturers. Yet, the empirical literature to date has not determined which retail characteristics have the largest impact on competitive behavior.Our starting point is the estimation of a structural demand-and-supply model, where both consumers’ decisions and the strategic interactions between manufacturers and retailers are explicitly modeled. We identify the type of competitive behavior of manufacturers by measuring the deviation from a Bertrand-Nash equilibrium. This measure of competitive conduct is expressed as a function of key retail characteristics such as size of the retailer, its assortment depth, and category expertise.We illustrate the proposed approach using data for the ground coffee category in Germany. Our findings indicate that retail characteristics have indeed a significant effect on competitive intensity among upstream firms and on their ability to exercise market power. Hence, a manufacturer considering entry into a new market should not only take into account its competitors but also the specifics of the retail environment in this market.     

Combining sell-out data with shopper behaviour data for category performance measurement: The role of category conversion power

Retailers need to manage a series of complex decisions relating to numerous products. To reduce this complexity, they have introduced category management practices, which consider groups of similar products (categories) that can be managed separately as single business units (SBUs). Although the concept that the store offer should be organised as a category mix and that this strategy allows for better overall store management is already consolidated, retailers still struggle to adopt an approach to the store performance measurement starting from a category level perspective. Nowadays, the available methods for measuring categories’ performance are quite limited. The current trend sees the measurement of category performance mainly based on sell-out data that are ill-equipped to fully address category management issues. Retailers should broaden their field of analysis not only by focusing on the product/sales perspective but also by including other methodologies such as shopper behaviour analysis. In this regard, the use of technology offers the retail sector new perspectives for those analysis. Therefore, we intend to contribute to the ongoing debate on the retail analytics topic by presenting a shopper behaviour analytics system for category management performance monitoring. More in detail, we could derive a new key performance indicator, category conversion power (CCP), aimed at analysing and comparing the single categories organised within the store. The research is based on a unique dataset obtained from a real-time locating system (RTLS), which allowed us to collect behavioural data togheter with sell-out data (from POS scanner). We argue that retailers could exploit this new analytical method to gain more understanding at the category level and therefore make data-driven decisions aimed at improving performance at the store level.     

Information effects of warehouse automation on sales in omnichannel retailing

The recent development of an omnichannel business environment provides a seamless shopping experience throughout the customer journey. Although previous studies have identified the importance of rapid product delivery, consumers cannot evaluate delivery quality until it has arrived. This study argued that warehouse automation and retail channel brand characteristics lead to informative signals and to firms' higher sales in the omnichannel context. By analyzing panel data from the Japanese retail market, we tested the effects of warehouse automation and the moderating effects of omnichannel, online, and offline brand offerings on the effectiveness of the warehouse automation signal. Results showed that warehouse automation signaling positively affects firms’ sales and has a positive interaction effect with omnichannel offerings.