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Suggests that frequent review of product sales performance is essential to the planning and control process. Investigates those products which have reached maturity or saturation stage of their product life cycle and reviews these in order to decide on their future product strategy. Evaluates the policy options available to management.

The essential investments in new product development (NPD) made by industrial companies entail effective management of NPD activities. In this context, performance measurement is one of the means that can be employed in the pursuit of effectiveness.

Companies spend millions on training their sales representatives. Thousands of textbooks have been published; thousands of training videos have been recorded. Hundreds of good pieces of advice and tips for sales representatives have been presented along with hundreds of sales methods and techniques. Probably the largest number of indicators and measures are applied in sales and distribution. On the one hand, this is a result of the fact that sales provide revenue and profit to a company; on the other hand, the concept of management by objectives turns out to be most effective in regional sales teams with reference to sales representatives and methods of performance evaluation. As a result, a whole array of indices has been created which enable the evaluation of sales representatives’ work and make it possible to manage goods distribution in a better way.

The indices presented in this chapter are rooted in the consumer market and are applied most often to this type of market (particularly in relation to fast-moving consumer goods at the level of retail trade). Nevertheless, many of them can be used on other markets (services, means of production) and at other trade levels (wholesale).

Although the values of many indices presented herein are usually calculated by market research agencies and delivered to companies in the form of synthetic results, we have placed the emphasis on the ability to determine them independently, both in descriptive and exemplifying terms. We consider it important to understand the genesis of indices and build the ability to interpret them on that basis. What is significant is that the indices can be interpreted differently; the same index may provide a different assessment of a product’s, brand or company’s position in the market depending on the parameters taken into account. Therefore, we strive to show a certain way of thinking rather than give ready-made recipes and cite ‘proven’ principles. Sales and distribution are dynamic phenomena, and limiting them within the framework of ‘one proper’ interpretation would be an intellectual abuse.

This study aims to understand how different levels of streamer channels influence luxury brand sales in live streaming commerce. This study also seeks to understand the conditions under which luxury brands may benefit more from different level streamer channels.

Panel data were collected from 17 international luxury brands on the Douyin live streaming platform in an 18 week period from August to December 2020 and analyzed by using a two-way fixed effects model.

The authors compared different mega-, macro- and micro-streamer channels within live streaming commerce and found that the densities of mega- and macro-streamer channels had significant positive impacts on luxury brand sales in live streaming commerce. Moreover, the effects of the density of streamer channel on luxury brand sales were moderated by such variables as product line breadth, product line depth, product type (star/non-star) and product price (high/low). The authors found that product line breadth and depth could reduce the positive impact of the densities of mega- and macro-streamer channels on luxury brand sales. For star products and high-priced products, the relationship between the density of mega-streamer channel and luxury brand sales was more likely to be observed than for non-star products and low-priced products. The relationship between the density of macro-streamer channel and luxury brand sales was more likely to be observed in low-priced products than in high-priced products.

The findings make important contributions to the literature in that the authors expand the influencer-brand fit theory by proposing a new model of effects of the densities of mega-, macro- and micro-streamer channels on sales performance across different luxury products to improve our understanding of the fit among influencers, brands and products. This helps luxury brands make basic decisions of “who sells” and “sells what” when engaging in live streaming commerce.

Entrepreneurship literature recognizes the founder’s involvement as a salient factor in determining the success of startups. Nevertheless, its role in conjunction with the marketing roles of founders has been relatively unexplored. Very little is known about how founder’s involvement in marketing tasks (i.e. developing products, sales and customers) helps attain success in early startups. To fill this knowledge gap, this study aims to qualitatively investigate the founder’s involvement under three vital functional areas (i.e. sales, customer development and product development) and also explain their entwined nature of the relationship as the early-stage startups grow to become a scalable businesses.

This study used purposive sampling for conducting in-depth interviews with 11 startup founders in the midwestern city of the USA. A constant comparative method was used to code the interview transcripts, while juxtaposing them with extant literature.

Using three levels of axial coding, this study identified 32 descriptive codes, 11 aggregate codes and 2 interpretive codes. Following this, the authors present five propositions that illustrate the relationship between founders’ involvement, customer development, product development and sales.

This study offers guidelines to founders on how they could generate initial sales, identify early customers and build and sustain mutually beneficial relationships with them.

This study contributes to the extant literature on entrepreneurship and innovation literature. It presents motivation and potential processes, including systematic activities performed by founders in generating sales in conjunction with customer development and product development, thereby making a novel contribution.

The purpose of this study is to identify crucial and new product selling challenges in the Information and Communication Technology (ICT) sector for the companies operating in Business to Business (B2B) sales setting.

This study uses qualitative techniques of focus group discussion, semi-structure interviews and thematic content analysis to explore crucial and new product selling challenges. Total interpretive structuring modeling (TISM) is used to create a hierarchy amongst the factors and interpret the relationships amongst them.

This study identifies crucial challenges for the ICT sector. The TISM framework helped in identifying variables and explained the relationship between the identified variables.

The findings may have been affected by the small size of the sample, the research was restricted to Indian market only and the result would have varied across cultures and different domains.

Companies in the ICT sector are eager to develop new products but fail to sell it. Salespeople play a crucial role in diffusing the new product in the market. Addressing the challenges faced by salespeople will improve not only the sales of the new product but also the overall the operational efficiency of the sales force.

Although several studies have suggested that sales force is the major contributing factor to new product success, few studies have focused on the role of salespeople in new product launch, particularly with respect to challenges in new product selling.

This is the first study to identify new product selling challenges in the ICT sector.

The purpose of this paper is to examine the performance of salespeople when selling new products (namely, electronic goods) in a business-to-business context by incorporating the organizations’ perceived psychological climate into goal orientation theory.

The current study uses the goal orientation theory to examine the performance of 158 salespeople based on new electronic product sales. Organizational psychological climate perceptions (i.e. customer orientation, sales supportiveness and sales innovativeness) are included as variables that can moderate salespeople’s performance. This study used partial least squares to examine its proposed model.

This study found that the learning goal orientation and the performance-prove goal orientation positively affect salespeople’s self-efficacy to sell new products, whereas a performance-avoid goal orientation negatively affects efficacy. In addition, new product selling self-efficacy itself has a positive influence on new product sales performance. As for the moderator, sales supportiveness and customer orientation have the ability to moderate the relationship between self-efficacy and performance.

This study has implications for sales managers or product managers who are responsible for promoting new products. First, this study’s findings suggest that managers should consider employing performance-prove goal-oriented staff and learning goal oriented staff to sell new products. Second, management can attempt to develop a more supportive climate for the sales team, such as assisting the team in obtaining needed resources from other departments. Finally, management needs to let salespeople know that they are doing their best to understand what new products existing and potential customers will need in the near future.

This current research is one of the first to examine how the perceived psychological climates of organizations (i.e. sales supportiveness, sales innovativeness and customer orientation) may moderate salespeople’s performance when selling new products. Second, this research examines how different types of goal orientation affect salespeople’s self-efficacy when selling new products. Previous results have not always been consistent regarding the influence of a performance-prove goal orientation. Last but not least, this study tests how new product selling self-efficacy mediates the relationships between goal orientations and new product sales performance as scholars have suggested that more research into the mediating role of self-efficacy is needed.

The rapid development of e-commerce has brought not only great convenience to people but a great challenge to online stores. Phenomenon such as out of stock and slow sales has been common in recent years. These issues can be managed only when the occurrence of the sales volume is predicted in advance, and sufficient warnings can be executed in time. Thus, keeping in mind the importance of the sales prediction system, the purpose of this paper is to propose an effective sales prediction model and make digital marketing strategies with the machine learning model.

Based on the consumer purchasing behavior decision theory, we discuss the factors affecting product sales, including external factors, consumer perception, consumer potential purchase behavior and consumer traffic. Then we propose a sales prediction model, M-GNA-XGBOOST, using the time-series prediction that ensures the effective prediction of sales about each product in a short time on online stores based on the sales data in the previous term or month or year. The proposed M-GNA-XGBOOST model serves as an adaptive prediction model, for which the instant factors and the sales data of the previous period are the input, and the optimal computation is based on the proposed methodology. The adaptive prediction using the proposed model is developed based on the LSTM (Long Short-Term Memory), GAN (Generative Adversarial Networks) and XGBOOST (eXtreme Gradient Boosting). The model inherits the advantages among the algorithms with better accuracy and forecasts the sales of each product in the store with instant data characteristics for the first time.

The analysis using Jingdong dataset proves the effectiveness of the proposed prediction method. The effectiveness of the proposed method is enhanced and the accuracy that instant data as input is found to be better compared with the model that lagged data as input. The root means squared error and mean absolute error of the proposed model are found to be around 11.9 and 8.23. According to the sales prediction of each product, the resource can be arranged in advance, and the marketing strategy of product positioning, product display optimization, inventory management and product promotion is designed for online stores.

The paper proposes and implements a new model, M-GNA-XGBOOST, to predict sales of each product for online stores. Our work provides reference and enlightenment for the establishment of accurate sales-based digital marketing strategies for online stores.

An updated version of the original (1985) text, the book covers all aspects of marketing and selling bank services: the role of marketing; behaviour of customers; intelligence, planning and organisation; product decisions; promotion decisions; place decisions; price decisions; achieving sales. Application questions help to focus the readers' minds on key issues affecting practice.