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Net Promoter Score (NPS) has been widely adopted by managers as a measure of customer mindset and predictor of sales growth. Over time, practitioners have evolved the use of NPS from its original purpose as a transaction-based customer loyalty metric, towards a metric for tracking overall brand health which includes responses from non-customers. Despite enduring managerial popularity, academics remain skeptical of NPS, citing methodological issues and ongoing concerns with NPS measurement. This study re-visits the use of NPS as a predictor of sales growth by analyzing data from seven brands operating in the U.S. sportswear industry, measured over five years. Our results confirm-within the context of our study-that while the original premise of NPS is reasonable, the methodological concerns raised by academics are valid, and only the more recently developed brand health measure of NPS (using an all potential customer sample) is effective at predicting future sales growth., Author(s): Sven Baehre [sup.1] , Michele O'Dwyer [sup.1] , Lisa O'Malley [sup.1] , Nick Lee [sup.2] Author Affiliations: (1) grid.10049.3c, 0000 0004 1936 9692, Kemmy Business School, University of Limerick, [...]

In recent years, Taylor's law describing the power function relationship between the mean and standard deviation of certain phenomena has found an increasing number of applications. We studied the characteristics of Taylor's law for branded product sales using point-of-sale (POS) data for brands sold in 72 grocery stores in the Greater Tokyo area. A previous study found that product sales follow Taylor's law with a scaling exponent of 0.5 for low sales quantities and 1.0 for large sales quantities. In the current study, we observed Taylor's law with cross-over for 54 product brands and estimated the value of the two coefficients in the theoretical curve to characterize the cross-over. The coefficients represent the fluctuations in the number of items purchased per consumer and the number of consumers in one store and in all stores. The estimated coefficients suggested the dependence of the features of Taylor's law on the category to which the brands belong. We found that brands in the same category tend to share similar features under Taylor's law. However, some brands exhibited specific features that differed from others in the same category. For example, for many brands in the Laundry Detergent and Instant Noodles categories, the number of customers purchasing the products in each store fluctuated significantly, whereas the number of purchased items per customer varied widely in the Japanese Tea category. In the coffee category, our results indicated that the degree of fluctuation in the number of purchasing customers largely depends on the brand. [ABSTRACT FROM AUTHOR]

To say that selling in today's environment is challenging is an obvious understatement after the global spread of COVID-19 has forced businesses big and small to toss even their best-laid [...]

In today's societies, given the increasing tendency to buy from malls and megastores that can meet all the buyer's needs in a limited time, we witness a large-scale growth of modern malls. Due to the breadth of services and diversity in such places, it is necessary to have a central intelligent control unit that takes control of all existing systems. The Internet of Things is one of the new technologies in the last decade, playing an essential role in intelligent business computing. The volume of customers coming to the mall, the customer service, and the customer buying behavior are factors whose analyses can dramatically increase the revenue from the stores and lead to better customer satisfaction. Many models are used to serve this purpose, one of which is the Bayesian Network model. In this research, using this model based on the interests and preferences of customers and purchasing patterns, we identify customers' needs and provide them with the desired product. After implementing this model, increasing the potential sales in the store and increasing the performance and speed of the store function are expected. [ABSTRACT FROM AUTHOR]

Within the contemporary business milieu, the discipline of selling and sales management has taken on a more prominent role in recent years. Myriad factors have contributed to the rise of interest in sales including globalization, technology, more sophisticated analytical approaches and new opportunities for co-creation of value between organizations and their customers. Over the past three decades, seven faculty consortia in sales have served as milestones to document the progress of the field, particularly the evolution of academic research. This article provides key takeaways from the most recent American Marketing Association (AMA) Faculty Consortium in Selling and Sales Management, which had the overarching goal of fostering new opportunities for building intercontinental research teams to effectively address the substantive issues for the future of the field. [ABSTRACT FROM PUBLISHER]

Paid search advertising is a critical source of traffic for sellers on e-commerce platforms. As the mobile Internet gains prominence as the main channel for reaching consumers, sellers need to know how to select and bid on keywords in online versus mobile search settings. This study compares the differential effects of paid search keywords in online and mobile settings on both direct and indirect sales, along with the moderating roles of keyword specificity and keyword cost. Two field studies and two lab experiments consistently show that a paid keyword in a mobile setting can prompt higher direct sales than it does in an online setting, but it generates lower indirect sales in general. Moreover, while keyword cost attenuates this positive relationship between mobile searching and direct sales, keyword specificity and keyword cost attenuate this negative relationship between mobile searching and indirect sales. Empirical evidence also reveals the sales and return on investment of paid search keywords in mobile and online settings. This study enriches previous literature by detailing new insights into the distinct settings of mobile and online search advertising., Author(s): Feng Wang [sup.1] , Li Zuo [sup.2] , Zhi Yang [sup.1] , Yueyan Wu [sup.1] Author Affiliations: (1) grid.67293.39, School of Business Administration, Hunan University, , Changsha, China (2) [...]

Objective: Extensive marketing of 'toddler milks' (sugar-sweetened milk-based drinks for toddlers) promotes unsubstantiated product benefits and raises concerns about consumption by young children. The present study documents trends in US toddler milk sales and assesses relationships with brand and category marketing. Design: We report annual US toddler milk and infant formula sales and marketing from 2006 to 2015. Sales response models estimate associations between marketing (television advertising spending, product price, number of retail displays) and volume sales of toddler milks by brand and category. Setting: US Nielsen retail scanner sales and advertising spending data from 2006 to 2015. Participants: Researchers analysed all Universal Product Codes (n 117·4 million) sold by seven infant formula and eight toddler milk brands from 2006 to 2015. Results: Advertising spending on toddler milks increased fourfold during this 10-year period and volume sales increased 2·6 times. In contrast, advertising spending and volume sales of infant formulas declined. Toddler milk volume sales were positively associated with television advertising and retail displays, and negatively associated with price, at both the brand and category levels. Conclusions: Aggressive marketing of toddler milks has likely contributed to rapid sales increases in the USA. However, these sugar-sweetened drinks are not recommended for toddler consumption. Health-care providers, professional organizations and public health campaigns should provide clear guidance and educate parents to reduce toddler milk consumption and address misperceptions about their benefits. These findings also support the need to regulate marketing of toddler milks in countries that prohibit infant formula marketing to consumers. [ABSTRACT FROM AUTHOR]

Abstract Retail atmospherics is becoming an increasingly important strategic tool for stores and restaurants. Ambient music and background noise are especially important atmospheric elements given their ubiquity in retail settings. [...]

Abstract. In this paper, I introduce a framework of price promotions by firms that preschedule their sale dates. I set up a dynamic model of demand accumulation in which high- [...]

Purpose: The factors that influence the true market demand and their extent of influence are highly elusive and erratic. This paper aims at applying Artificial Intelligence (AI) techniques to identify and predict complex sales patterns and compare the results with traditional forecasting models. Design/methodology/approach: Sales data related to the sample firm was used in the study for forecast modelling using both, advanced forecasting method (ARIMA) and Artificial Neural Networks (ANNs). The latter considers inputs of influential/causal factors and revisits every time to identify new trends related to those factors, thus providing a more robust forecast. This is compared with results from the ARIMA model. Findings: It is inferred that neural networks with the input of influencing/causal factors has a greater accuracy when compared to ARIMA model. It is also time adaptive and changes according to trends experienced in the causal factors. Research limitations/implications: Though the purpose of the research is achieved, a few limitations exist because of the limited availability of data. Besides, the factors that affect the prediction are generalised and based on previous research works. A more customised approach towards the firm under study would greatly improve the accuracy. Practical implications (if applicable): Machine learning and big data are bringing paradigm changes in developing a better forecasting model. It has the potential to analyse huge amounts of data and provide instant insights that can greatly improve business performances. Originality/Value: This paper extends the scope of previous literature by taking into account the factors that influence the sales of the automobile industry, considering the Indian market during the time period (1988-2016). [ABSTRACT FROM AUTHOR]

We document that consistent patterns of high or low sales growth that are incongruent with underlying fundamentals are followed by significant stock price reversals. In contrast, no stock return reversals are found for firms that achieve the same level of sales growth in an inconsistent manner. Furthermore, future earnings announcement returns mimic the pattern of abnormal stock returns documented for the Consistent- and Inconsistent-Growth portfolios, respectively, corroborating our main findings. Our results are robust to controls for the magnitude of sales growth, fundamental strength, business cycle risk exposures, and standard risk factors. Our evidence is consistent with representativeness bias affecting investor interpretation of consistency in sales growth patterns. History: Accepted by Mary Barth, accounting. Keywords: representativeness * behavioral finance * asset pricing * fundamental analysis * stock return predictability, 1. Introduction A central issue in capital markets research is whether psychological biases affect investor processing of financial information. In a recent comprehensive study of behavioral finance theories, Chan et [...]

The purpose of this article is to find out the most important factors for sales of dairy products. Transactional data for sales are used. This article is published for the first time. The results of the analysis will show how transactional data may be used for data mining. SPSS is used to analyze the data. Statistical methods (such as independent samples t-test, Chi-square tests, Mann-Whitney U test, one-way ANOVA test) are applied to find dependencies. We suppose that the quantity of sales depends on the year, month, group, item and average price. At the end of the study we found out that “year” and “group” are factors which mostly influence the quantity of a sale. Factors “month”, “item” and “average sale price” do not affect the quantity of a single sale. Mathematical formulas are derived to predict the quantity of a future sale on the basis of independent variables such as year and group of stock.

We examine the effectiveness of Korea's Sunday superstore shopping regulation, whose purpose is to protect small- and medium-sized retailers as well as traditional markets. Applying a two-way random-effects regression model to the daily sales data of four megastores and four super supermarkets, we find the net sales decrease of superstores is on average 5.61% of daily sales after taking into account sales increases due to consumers' switching to weekdays. Only about J7%-19% of the reduced superstore sales are transferred to traditional markets. Based on these estimates, the compensating variation per year is predicted to be 2.4-2.5 trillion Korean won (around US $2.1-2.2 billion). (JEL L51, L88), I. INTRODUCTION The Korean government implemented a Sunday shopping regulation in 2012. This restriction is unique in its purpose and implementation; while most other countries have enforced Sunday shopping regulations [...]

Laboratory and field experiments show that when choosing among a set of objects, consumers could be subjected to context-dependent preferences and evaluate options by considering both the absolute utilities and [...]

Sellers of almost any product or service rarely keep their prices constant through time and frequently offer price discounts or sales. This paper investigates an explanation of sales as a [...]

The purpose of this article is to evaluate the impact of a new product on the sales of other products. Launching a new product may lead to increase or decrease of sales in the products of the same group. Customers may continue buying standard products or they may be oriented to new products. New products may cause internal competition. Statistical methods are applied. Time series analysis is used. Transactional database of a confectionary factory is the main source of data. The time series analysis is carried in two datasets - quantities of sales of three products on a daily basis and on a monthly basis. The main methods used are time series analysis and regression analysis. The three time series (corresponding to the three products) are separated into two parts - before and after launching the new product. It is proved that the new product does not affect the sales of the two other products. The new product is well accepted and its sales increase together with the sales of the two other products. [ABSTRACT FROM AUTHOR]

Theoretical model is used to examine the impact of increase in sales, financial costs and cash flow of Brazilian firms on their investment decisions.

Application of heuristic programming techniques for admission control and queueing of orders in business to control pricing of goods and services without affecting profitability.

Empirical model for continous review of base stock inventory and lost sales, based on varying demand for goods manufactured by company, is presented.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jada.2006.08.002 Byline: Dara Bergen, Ming-Chin Yeh Abstract: This study examined the effects of an environmental intervention promoting more non-energy-containing beverage consumption compared to sugar-sweetened soft drink consumption through vending machines in an urban college setting. Eight soft drink vending machines were randomly selected and assigned to one of three conditions over a 9-week period: energy-content labels on non-energy-containing beverage selection panels (intervention I), labels plus motivational posters (intervention II), or control. The totals of all beverages sold and machine revenue were recorded at baseline (2 weeks), intervention (5 weeks), and postintervention (2 weeks) periods. Use of energy-content labels and motivational posters, compared with control group, resulted in a significantly lower growth rate of sugar-sweetened beverage sales (P<0.05). Total revenue for all beverages increased during the intervention period. It is estimated that the non-energy-containing beverages combined accounted for 70.52% of the increased revenue. Results of this study suggest that energy-content labels and motivational posters on beverage vending machines may be an effective way to influence beverage sales.

Myths about internet are clarified. In this context, the usage of Internet for sales and purchasing is discussed.

An analysis of optimal control policies with respect to lost sales inventory models is presented.

CASE DESCRIPTION This case primarily focuses on the rescue of a brand which has been around for nearly a century, and how strategic marketing can be effectively used to rebuild [...]

People expect more money to give up an object, because they perceive the transaction to be a sort of loss to them. It follows then that they are willing to pay less for possessing the same object. This phenomenon is called endowment effect. Endowment effect does not exist in routine transactions or exchange transactions. The effect of curiosity on endowment effect is also examined.

This study measures social desirability bias (SD bias) by comparing the level of discipline sales managers believe they would administer when supervising unethical selling behavior with the level of discipline they perceive other sales managers would select. Results indicate the presence of SD bias; the sales manager respondents consistently claimed that they would be stricter while their peers would be more lenient. Using an analytical technique that takes social desirability bias into account, it appears that sales managers' use of discipline is affected by the sales performance of the salesperson being disciplined resulting in more lenient discipline for top sales performers. In addition, the more lenient treatment for top sales performers persists even when there is a pattern of a prior ethical infraction and the existence of an explicit organizational policy proscribing the act in question. Sales managers believe that, like themselves, others would be stricter when an unethical act is committed for the second time but not as strict as they personally would be. A within-subjects interaction effect indicates more SD bias under the condition of the unethical act being committed for the second time. KEY WORDS: ethics in sales, ethical violations and employee supervision

A study analyzing the reasons for disparity between the individual's willingness to pay a price for a good and his willingness to accept a price for the same good is presented.

ABSTRACT The purpose of this exploratory study was to examine the relationship between sales effectiveness and small firm performance in a time when a proliferation of technological innovations are available [...]

ABSTRACT The words used by sellers to describe their goods to induce buyers to purchase them can land the seller in court if the goods fail to measure up and [...]

Abstract The author offers a critical examination of the provisions on purchase and sale in the Civil Code of the Russian Federation. Focusing narrowly on the text of the code, [...]

The guidelines for high-performance sales activities required in organizations are addressed. These guidelines are used by Roche Diagnostics to improve their sales and business.

The different ways in which interfunctional climate, comprised of the two elements of communication ease and co-operation, might affect sales-distribution relationship effectiveness is investigated. Impact of management and subordinate levels within each respective function are examined and it is found that cooperation is an important element for sales-distribution effectiveness across both functions and management levels.

The authors present a model of free sample effects and evidence from two field experiments on free samples. The model incorporates three potential effects of free samples on sales: (1) [...]

Byline: Igal Hendel (1), Aviv Nevo (2) Keywords: sales; panel data methods Abstract: One of the puzzles of store-level scanner data is the lack of a dip in quantity sold in the weeks following a promotion. Such a dip is predicted by a consumer inventory model. During a promotion consumers buy more, not only for current consumption, but stockpile for future consumption. The predictions of such a model have been confirmed by household-level data yet seem harder to find in aggregate brand- or category-level data. We re-examine this puzzle and reach two conclusions. First, the effects at the household-level are present, but are much smaller than previously found. Our estimates are different because we control for household heterogeneity in a more general way than most previous work. This suggests that since the effects are small they might be harder to spot in aggregate data. Second, we show that the dip is present in the aggregate data, once we control for additional promotional activity, like feature and display. The latter has an opposing dynamic effect that masks the existence of the post-promotion dip. Author Affiliation: (1) Madison and NBER, University of Wisconsin, USA (2) Berkeley and NBER, University of California, USA Article History: Registration Date: 11/10/2004

The authors examine foreign and domestic sales in light of single output and two kinds of risk aversion. Results of this complicated model are unambiguous in the case of substitutes.

In a situation where several hundred new music albums are released each month, producing sales forecasts in a reliable and consistent manner is a rather difficult and cumbersome task. The purpose of this study is to obtain sales forecasts for a new album before it is introduced. We develop a hierarchical Bayesian model based on a logistic diffusion process. It allows for the generalization of various adoption patterns out of discrete data and can be applied in a situation where the eventual number of adopters is unknown. Using sales of previous albums along with information known prior to the launch of a new album, the model constructs informed priors, yielding pre-launch sales forecasts, which are out-of-sample predictions. In the context of new product forecasting before introduction, the information we have is limited to the relevant background characteristics of a new album. Knowing only the general attributes of a new album, the meta-analytic approach proposed here provides an informed prior on the dynam ics of duration, the effects of marketing variables, and the unknown market potential. As new data become available, weekly sales forecasts and market size (number of eventual adopters) are revised and updated. We illustrate our approach using weekly sales data of albums that appeared in Billboard's Top 200 albums chart from January 1994 to December 1995. (Forecasting; Empirical Generalization; Hierarchical Bayes Model), Introduction The business of making and selling records provides a clear illustration of one of the balancing principles in business: potential profit versus potential risk. While there are considerable potential [...]

Purpose |!|#8211; The paper aims to find the functional relationship among 14 shampoo brands|!|#39; price, quality, marketing expense and sales in the Chinese shampoo industry. Also studied is which one, among these factors, is the more important. Design/methodology/approach |!|#8211; By using data envelopment analysis models, the authors propose to maximize the sale allocating efficiency scores to satisfy the hypothesis that the shampoo market is efficient, and then, the sales functions, linear and exponential, can be determined and specified. Findings |!|#8211; It is found that an exponential sales function is more suitable to characterize the Chinese shampoo industry, and the price factor is a major influence on creating sales. Originality/value |!|#8211; The paper proposes a method, from an original perspective, to analyze the sales function among the influence factors and to determine which one is more important. The method can be applied to other markets if the assumed conditions could be satisfied. [ABSTRACT FROM AUTHOR]

The article offers information on a study conducted by the authors in which they compared seven distribution models for retail sales data. The authors compared seven probability distribution models like lognormal, square root transformation and exponential. It highlights that square root transformation provided lowest error and Weibull model provided best overall fit to these data.

The focus of this paper is on the benefits of visual analysis for pharmaceutical and healthcare companies particularly in relation to their sales activity; however it is easy to see how these benefits can transfer to other areas of the organisation, whether this is marketing, research or clinical trials. To illustrate the benefits of visual analysis, this paper will base its arguments on a case study for a ‘flu vaccine. The benefits of such analysis can assist all levels of the organisation from strategic planning at board level through to tactical managerial decision-making through to assisting in the day-to-day planning and operation of the field sales representatives.Journal of Medical Marketing (2006) 6, 119–125. doi:10.1057/palgrave.jmm.5050025 [ABSTRACT FROM AUTHOR]

This paper analyses the dynamics of strike incidence when a firm's market share affects its future profitability. Inventory accumulation is assumed to be impossible, so during a strike sales are [...]

I. Introduction In a recent communication in this journal, O'Neill |6~ claims that computing entropy indices for concentration as was done by Hexter and Snow |3~, Hexter |2~, and Nissan [...]

THE LASER MARKETPLACE: FORECAST 1991 Whither goest the laser industry? Will it continue to grow, albeit slowly, through the current economic uncertainties, as it did during the 1974-75, 1980-81 and […]

HOW TO PREDICT SEASONAL PATTERNS Regular seasonal patterns appear in most business data. The weather affects sales of everything from snorkeling gear to snowmobiles. During the December holiday season there […]

Need for marketers to target women to increase their sales is highlighted.

Over 25 years, we have developed many sales-force and modeling insights through over 2,000 projects with several hundred selling organizations in over 50 countries. Content insights are useful in making [...]