Despite the burgeoning research on business failure in industrial markets, not much has been conducted on the role played by marketing analytics in mitigating such failure in the post-pandemic ...period. Against this backdrop, this study was aimed at investigating the antecedents of marketing analytics success (MAS) and its overall effects on strategic business value and profitability. Drawing on quality-dominant logic through the dynamic capability lens, this study yielded a model that, on the basis of data, model, and deployment quality, explains the achievement of MAS and the avoidance of business failure. This study, the data for which were gathered in Australia from 314 sample elements, shows that MAS significantly contributes to strategic business value and profitability. Such findings present a theoretically rigorous and practically relevant framework of MAS capable of mitigating the causes of business failure by harnessing analytics insights.
•This study identifies data, model, and deployment qualities as the antecedents of marketing analytics success;•The study models the effects of marketing analytics success on strategic business value and profitability;•The study uses quality-dominant logic through the dynamic capability lens.
The authors provide a critical examination of marketing analytics methods by tracing their historical development, examining their applications to structured and unstructured data generated within or ...external to a firm, and reviewing their potential to support marketing decisions. The authors identify directions for new analytical research methods, addressing (1) analytics for optimizing marketing-mix spending in a data-rich environment, (2) analytics for personalization, and (3) analytics in the context of customers' privacy and data security. They review the implications for organizations that intend to implement big data analytics. Finally, tuming to the future, the authors identify trends that will shape marketing analytics as a discipline as well as marketing analytics education.
Detailed feedback on exercises helps learners become proficient but is time-consuming for educators and, thus, hardly scalable. This manuscript evaluates how well Generative Artificial Intelligence ...(AI) provides automated feedback on complex multimodal exercises requiring coding, statistics, and economic reasoning. Besides providing this technology through an easily accessible web application, this article evaluates the technology’s performance by comparing the quantitative feedback (i.e., points achieved) from Generative AI models with human expert feedback for 4,349 solutions to marketing analytics exercises. The results show that automated feedback produced by Generative AI (GPT-4) provides almost unbiased evaluations while correlating highly with (r = 0.94) and deviating only 6 % from human evaluations. GPT-4 performs best among seven Generative AI models, albeit at the highest cost. Comparing the models’ performance with costs shows that GPT-4, Mistral Large, Claude 3 Opus, and Gemini 1.0 Pro dominate three other Generative AI models (Claude 3 Sonnet, GPT-3.5, and Gemini 1.5 Pro). Expert assessment of the qualitative feedback (i.e., the AI’s textual response) indicates that it is mostly correct, sufficient, and appropriate for learners. A survey of marketing analytics learners shows that they highly recommend the app and its Generative AI feedback. An advantage of the app is its subject-agnosticism—it does not require any subject- or exercise-specific training. Thus, it is immediately usable for new exercises in marketing analytics and other subjects.
This study focuses on the use of big data analytics in managing B2B customer relationships and examines the effects of big data analytics on customer relationship performance and sales growth using a ...multi-industry dataset from 417 B2B firms. The study also examines whether analytics culture within a firm moderates these effects. The study finds that the use of customer big data significantly fosters sales growth (i.e. monetary performance outcomes) and enhances the customer relationship performance (non-monetary performance outcomes). However, the latter effect is stronger for firms which have an analytics culture which supports marketing analytics, whereas the former effect remains unchanged regardless of the analytics culture. The study empirically confirms that customer big data analytics improves customer relationship performance and sales growth in B2B firms.
•Grounded on a multi-industry dataset from 417 B2B firms.•Examines the effects of customer big data analytics (BDA) on customer relationship performance and sales growth.•Uses latent moderated structural equations method in Mplus.•Finds that customer BDA significantly fosters sales and customer relationship performance.•The effect of customer BDA on customer relationship performance is stronger for firms where analytics culture is strong.
The age of digitisation has resulted in an explosion of studies investigating the benefits of Big Data Analytics (BDA) as a means to enhance competitive advantage in organisations. However, the best ...way to leverage BDA is still inconclusive. Moreover, there is paucity of studies investigating how SMEs, who are recognised as having high levels of entrepreneurial orientation, can utilise big data and marketing analytics to support innovation and competitive advantage in dynamic environments. This study employs dynamic capabilities as a lens to investigate the nuanced relationships. Adopting a partial least squares (PLS) path modelling method with 194 UK SMEs, this study finds that knowledge integration mechanisms are particularly critical value creation enablers by transforming EO and BDA into organisational wide capabilities in support of innovation and competitive advantage. These novel and nuanced insights are of value to both practitioner and researchers.
This study introduces the knowledge fusion taxonomy to understand the relationships among traditional marketing analytics (TMA), big data analytics (BDA), and new product success (NPS). With high ...volume and speed of information and knowledge from different stakeholders in the digital economy, the taxonomy aims to help firms build strategy to combine knowledge from both marketing and big data domains. The study suggests that knowledge fusion to improve NPS is not automatic and requires strategic choices to obtain its benefits.
Retail forecasting: Research and practice Fildes, Robert; Ma, Shaohui; Kolassa, Stephan
International journal of forecasting,
10/2022, Letnik:
38, Številka:
4
Journal Article
Recenzirano
Odprti dostop
This paper reviews the research literature on forecasting retail demand. We begin by introducing the forecasting problems that retailers face, from the strategic to the operational, as sales are ...aggregated over products to stores and to the company overall. Aggregated forecasting supports strategic decisions on location. Product-level forecasts usually relate to operational decisions at the store level. The factors that influence demand, and in particular promotional information, add considerable complexity, so that forecasters potentially face the dimensionality problem of too many variables and too little data. The paper goes on to evaluate evidence on comparative forecasting accuracy. Although causal models outperform simple benchmarks, adequate evidence on machine learning methods has not yet accumulated. Methods for forecasting new products are examined separately, with little evidence being found on the effectiveness of the various approaches. The paper concludes by describing company forecasting practices, offering conclusions as to both research gaps and barriers to improved practice.
The rise of sharing economy has accelerated the growth of marketing analytics to match demand and supply in industrial markets. However, the conceptualization of marketing analytics remains unclear ...in the sharing economy. Theorizing market turbulence as the dark side of the sharing economy, this study presents a marketing analytics capability model using dynamic capabilities and contingency theories to advance thought and practice in industrial marketing research. Using a thematic analysis and a survey-based empirical study on B2B cloud sharing platforms (n = 252), the findings present pattern identification, real-time solutions and data governance as the antecedents of marketing analytics capability with its holistic effects on marketing agility and marketing effectiveness. The empirical findings further support the mediating role of marketing agility and the moderating impact of market turbulence on marketing analytics-effectiveness and marketing agility-effectiveness chain. Overall, our results contribute toward a more nuanced understanding of the dark side of market turbulence on marketing analytics capability dynamics in the sharing economy.
•Marketing analytics capability includes pattern identification, real-time solutions and data governance.•Marketing analytics capability accelerates marketing agility and marketing effectiveness in the sharing economy.•Market turbulence, including technology, competitor and customer turbulence, is the dark side of a sharing economy.
While marketing analytics plays an important role in generating insights from big data to improve marketing decision-making and firm competitiveness, few academic studies have investigated the ...mechanisms through which it can be used to achieve sustained competitive advantage. To close this gap, this study draws on the dynamic capability view to posit that a firm can attain sustained competitive advantage from its sensing, seizing and reconfiguring capabilities, which are manifested by the use of marketing analytics, marketing decision-making, and product development management. This study also examines the impact of the antecedents of marketing analytics use on marketing related processes. The analysis of a survey of 221 UK firm managers demonstrates: (a) the positive impact of marketing analytics use on both marketing decision-making and product development management; (b) the effect of the latter two on sustained competitive advantage; (c) the indirect effect of data availability on both marketing decision-making and production development management; and (d) the indirect effect of managerial support on marketing decision-making. The research model proposed in this study provides insights into how marketing analytics can be used to achieve sustained competitive advantage.
•Understanding how marketing analytics can be used to gain firm competitiveness underpinned by the dynamic capability view.•Demonstrating that a firm can attain sustained competitive advantage from its sensing, seizing and reconfiguring capabilities.•Dynamic capabilities being manifested by the use of marketing analytics, marketing decision-making, and product development management.•Testing hypotheses based on data collected from 221 UK companies.
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