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Social media data have recently attracted considerable attention as an emerging voice of the customer as it has rapidly become a channel for exchanging and storing customer-generated, large-scale, and unregulated voices about products. Although product planning studies using social media data have used systematic methods for product planning, their methods have limitations, such as the difficulty of identifying latent product features due to the use of only term-level analysis and insufficient consideration of opportunity potential analysis of the identified features. Therefore, an opportunity mining approach is proposed in this study to identify product opportunities based on topic modeling and sentiment analysis of social media data. For a multifunctional product, this approach can identify latent product topics discussed by product customers in social media using topic modeling, thereby quantifying the importance of each product topic. Next, the satisfaction level of each product topic is evaluated using sentiment analysis. Finally, the opportunity value and improvement direction of each product topic from a customer-centered view are identified by an opportunity algorithm based on product topics’ importance and satisfaction. We expect that our approach for product planning will contribute to the systematic identification of product opportunities from large-scale customer-generated social media data and will be used as a real-time monitoring tool for changing customer needs analysis in rapidly evolving product environments. 相似文献
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Understanding user experience (UX) becomes more important in a market-driven design paradigm because it helps designers uncover significant factors, such as user’s preference, usage context, product features, as well as their interrelations. Conventional means, such as questionnaire, survey and self-report with predefined questions and prompts, are used to collect information about users’ experience during various UX studies. However, such data is often limited and restricted by initial setups, and they won’t easily allow designers to identify all critical elements such as user profile, context, related product features, etc. Meanwhile, with widely accessible social media, the volume and velocity of customer-generated data are fast-increasing. While it is generally acknowledged that such data contains important elements in understanding and analyzing UX, extracting them to assist product design remains a challenging issue. In this study, how UX data underlying product design can be isolated and restored from customer online reviews is examined. A faceted conceptual model is proposed to elucidate the crucial factors of UX, which serves as an operational mechanism connecting to product design. A methodology of establishing a UX knowledge base from customer online reviews is then proposed to support UX-centered design activities, which consists of three stages, i.e., UX discovery to extract UX data from a single review, UX data integration to group similar data and UX network formalization to build up the causal dependencies among UX groups. Using a case study on smart mobile phone reviews, examples of UX data discovered are demonstrated and both customers and designers concerned key product features and usage situations are exemplified. This study explores the feasibility to discover valuable UX data as well as their relations automatically for product design and business strategic plan by analyzing a large volume of customer online data. 相似文献
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《Information processing & management》2022,59(6):103085
Nowadays, Artificial Intelligence (AI) based modeling is the major consideration to build efficient, automated, and smart systems for our today's needs. Many companies are benefited from these modeling methods for their marketing efforts. Each firm has expected to increase its product development in an innovative way to improve its business growth. Successful firm marketing is to offer the right product to the right person at the right time. To market the product to the customer successfully, it is needed to segment the customer by finding their behavioral patterns. The customer behaviors and their purchasing patterns are used to generate profit for the company. Customer segmentation is the process of grouping customers based on commonalities. Developing an efficient AI-based customer segmentation to improve digital marketing growth is a challenging task. In this paper, an unsupervised deep learning model called a Self-organizing map with an Improved social spider optimization approach has been used for efficient customer segmentation. The customer data are analyzed by a feature engineering process using a swarm intelligence model called Modified social spider optimization to select the behavioral features of the customer. Then, the customers are clustered using Self Organizing neural network (SONN). Based on the clusters, the customers are classified using the Deep neural network (DNN) model. The experimental results prove the performance of the proposed model with high clustering and segmentation capability to improve the business profit in marketing. 相似文献
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《International Journal of Information Management》2017,37(6):673-683
With the rapid development of information technology, customers not only shop online—they also post reviews on social media. This user-generated content (UGC) can be useful to understand customers’ shopping experiences and influence future customers’ purchase intentions. Therefore, business intelligence and analytics are increasingly being advocated as a way to analyze customers’ UGC in social media and support firms’ marketing activities. However, because of its open structure, UGC such as customer reviews can be difficult to analyze, and firms find it challenging to harness UGC. To fill this gap, this study aims to examine customer satisfaction and dissatisfaction toward attributes of hotel products and services based on online customer textual reviews. Using a text mining approach, latent semantic analysis (LSA), we identify the key attributes driving customer satisfaction and dissatisfaction toward hotel products and service attributes. Additionally, using a regression approach, we examine the effects of travel purposes, hotel types, star level, and editor recommendations on customers’ perceptions of attributes of hotel products and services. This study bridges customer online textual reviews with customers’ perceptions to help business managers better understand customers’ needs through UGC. 相似文献
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越来越多的企业在产品创新中吸引顾客参与,期望提升顾客满意。以往研究表明,在简单产品的创新中,顾客参与程度和满意度之间呈现正向关系。但是,在高复杂度产品创新范畴,本研究却发现顾客参与和满意之间并非呈现简单的线性关系,还受到一些因素的调节作用。本研究在高复杂度产品创新中提出顾客知识的概念,将顾客参与分为两个构面(顾客作为信息提供者和共同参与者),将顾客满意分为两个维度(顾客对参与过程体验满意度和对参与结果满意度),探讨顾客知识对参与程度和满意度关系的调节效应。实证研究结果显示,在高复杂度产品创新中,无论顾客是作为信息提供者,还是作为共同开发者,在相同参与程度时,高知识顾客的满意度高于低知识顾客。同时,由于顾客知识的调节效应,顾客参与和满意之间不是在任何情况下都呈正向关系,当低知识顾客作为共同开发者,参与越深反而对参与过程感觉越不满意。研究结论为如何吸引顾客参与来提升顾客满意提供了具体指导。 相似文献
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Customers commonly share opinions and experiences about products via the internet by means of social media and networking sites. The generated textual data is often analysed by means of Sentiment Analysis (SA) as means to assess customer opinions on product features more efficiently than through surveys. To enable a more objective product target setting, the impact of product feature performance changes on customer satisfaction is essential. Kano et al. (1984) presented a survey-based model to classify product features based on their impact on customer satisfaction to aid designers in their product target setting. Approaches extending the Kano model rely on customer surveys as input data. In addition, existing studies classifying extracted product features from textual data (e.g. product reviews) rarely provide a clear separation in terms of Kano categories. Thus, the impact of identified product features on customer satisfaction remains unknown to product designers. This paper presents a methodology for autonomously classifying extracted aspects from textual data into Kano categories. For verification purposes, two examples using coffee machine and smartphone user reviews are presented. Results indicate that the proposed methodology efficiently provides product designers with insightful customer information through the proposed aspect categorization. 相似文献
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本文通过问卷调查数据,检验了顾客满意度对口碑推荐进而对新客户购买决策的影响,模型中同时考虑了产品涉入度和情感承诺的调节作用以及顾客交流特征(口碑传播者的专业性、关系强度、感知风险)对新客户购买决策的影响。结果表明:顾客满意度对口碑推荐有显著的正向影响;口碑推荐对新客户购买决策有显著的正向影响;产品涉入度在顾客满意度和口碑推荐的关系中起着显著的正向调节作用,但情感承诺的调节作用不明显;口碑传播者的专业性以及关系强度对新客户购买决策有显著的正向影响,感知风险的影响不显著。同时本文通过计算口碑推荐数量和口碑转换概率从而预测出基于口碑推荐方式获取新顾客数量。 相似文献
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[目的/意义]实现海量产品评论数据的快速分析,帮助产品设计人员高效地获取用户需求,在新产品设计的决策中提供参考。[方法/过程]在特征提取和情感分析的基础上,构造了包括"词+词性+词干+位置+依存关系"等节点特征的条件随机场模型,按照"产品特征、谁、在何种情境下、遇到了什么问题"4个要素,以描述手机屏幕和电池的负面评论为例,从产品评论中提取用例。[结果/结论]模型评估和实证研究表明,所构造的模型可以有效地从评论文本中识别产品特征、使用主体、使用情景和遇到的问题,从而快速构造用例,获取用户需求。 相似文献
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领先用户在线参与新产品开发的动机研究 总被引：2，自引：0，他引：2
新产品开发与改进需要客户的参与,而领先用户是最适宜的客户.在文献研究的基础上,综合以往对客户参与的动机研究,提出了领先用户参与新产品开发的9个动机的假设.然后结合这些研究开发了量表对国内某智能手机厂商的产品开发论坛中的领先用户进行问卷调查.用因子分析方法对问卷进行分析.研究表明影响最大的是独特性产品需求和认知动机两个动机,其次,是利益动机与产品生产控制动机.而交往动机与网络沉浸动机则不明显. 相似文献
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住宅产品顾客满意度评价模型研究 总被引：1，自引：0，他引：1
在深入研究顾客满意的影响因素、住宅产品的特点和住宅产品消费者行为分析的基础上,提出了住宅产品顾客满意度评价模型,为住宅产品企业分析顾客满意状态,实施顾客满意战略提供了方法和手段。 相似文献
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顾客如何感知大规模定制——基于顾客自我效能、选项呈现方式与定制满意的实证研究 总被引：1，自引：0，他引：1
基于消费者自我定制产品视角,探讨顾客自我效能、企业定制选项呈现方式与定制结果满意之间的关系,通过对手机和笔记本电脑的定制模拟实验数据发现:不同定制的选项呈现方式导致的顾客感知决策难度和定制结果满意存在不同,"减法"定制方式比"加法"定制方式顾客感知决策难度更大,顾客对定制结果的满意度更高。研究还发现,顾客自我效能显著影响对定制方式的选择,高自我效能个体偏好"减法"定制方式,低自我效能个体偏好"加法"定制方式,高自我效能个体比低自我效能个体对定制结果的满意度更高。最后提出研究的理论价值和管理启示。 相似文献
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In this study the authors propose a distinction between two approaches to market information, rooted in the marked-based learning theory. The two approaches are conceptualized and operationalized on the basis of their differences along three processes: generation, dissemination and use of market information. In the retrospective approach, the generation process is based on expressed customer needs and extant market relations; the dissemination is based on formal mechanisms; the use process is more instrumental. In the forward-looking approach, the generation process is based on latent customer needs and on the evolutionary patterns of the future market relations; the dissemination process is more informal; the use of information is more conceptual. A series of hypotheses concerning the relationships between these approaches, product innovativeness and firm performance are tested on a sample of Italian fashion firms. Results suggest that the two approaches are complementary for firm performance, but have opposite effects on product innovativeness: while a forward-looking approach is positively related to product innovativeness, a retrospective approach seems to be negatively related. The results also shed light on how market information approaches and product innovativeness jointly affect firm performance. 相似文献
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《Information processing & management》2022,59(1):102800
At present, the focus of marketing research is mostly on the influencing factors, composition, and measurement of brand equity. The meta-combined brand equity analysis is based on two main research perspectives: financial perspective and customer perspective. While the financial perspective is based on the incremental discounted future cash flows that would result from a branded product's revenue over the revenue of an unbranded product, the brand equity from the customer's perspective is the consumer's reaction to brand marketing behavior, the impact on brand knowledge. The decision-making of marketing behaviors often faces choices related to ethics. Therefore, once the moral value of a company through marketing behavior is recognized by consumers, the ethical behavior presented in this article through marketing behavior will make consumers feel more about the brand. How does the brand equity of your customer's products affect you? In this experiment, shopping groups with the same shopping experience were selected. During the survey process, all customers in different periods and the same time were selected as far as possible based on the practicability of the survey. The study survey covered 4 main aspects; customer satisfaction, overall overview of customer satisfaction; the advantages and disadvantages of marketing strategies through quantitative analysis and to put forward reasonable marketing strategy improvement opinions and suggestions to improve customer satisfaction. Using the technique of parameter prediction of the financial industry, the experiment proved that the non-standard promotion behavior, the integrity of the enterprise and the social responsibility are three aspects (P<0.05) that have an impact on the customer's brand equity among the corporate marketing components. It was a detailed study of the current state of brand marketing strategies and customer satisfaction, found key indicators of brands that could improve customer satisfaction, and presented corresponding suggestions for optimizing marketing strategies. It shows that. It has the importance of good guidance and references to improve customer satisfaction in the industry. 相似文献
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O2O在线外卖顾客满意度评价体系区别于传统的餐饮顾客满意度评价,为提高O2O模式下在线外卖的顾客满意度,本文通过对顾客满意评价体系以及餐饮行业顾客满意因素研究,提出了O2O模式在线外卖用户满意度的模糊评价模型。模型给出在线外卖顾客满意的4个影响因素,即食品因素、价格因素、服务因素以及便利因素,其中食品因素对顾客满意的影响程度最大。利用模型对在线外卖的代表性平台"饿了么"进行顾客满意度的实证分析,验证了模糊评价体系可行性,并根据评价结果提出了提高O2O在线外卖顾客满意度的措施建议。 相似文献
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众多研究将服务化视为制造企业获取竞争优势的重要途径。然而,伴随着对商业模式过度创新的质疑和对硬科技的持续关注,服务化究竟能否促进产品创新并最终塑造长期竞争优势亟待研究。因此,本研究分析了服务化对制造企业产品创新的影响及环境不确定性的调节作用。基于中国239家制造企业的样本数据,研究表明：1）服务化与产品创新度之间呈U型关系;2）技术动态性和市场不确定性负向调节服务化与产品创新度之间的关系。研究结果有助于制造企业全面认识服务化作用,明确服务化对产品创新的积极作用和不利影响,根据不同的环境条件有效推进服务化实践。 相似文献