Market Intelligence Research Articles

The Applicability of Artificial Intelligence Marketing for Creating Data-driven Marketing Strategies

The purpose of this paper is to explore the applicability of AI marketing for creating data-driven marketing strategies. Notably, the paper illustrates the existing circumstances of artificial intelligence in marketing practice. Besides, this paper argues for awareness of AI for customer satisfaction, employing AI to improve positioning, applying AI for accurate decision-making, and utilizing AI for sales, cost, and risk reductions. Lastly, this paper compares the applicability of AI marketing within two major regions from four regions identified in the study. A two-step approach was used to address the research question. First, a systematic literature review was conducted to identify the knowledge gap. Second, primary research through a survey study was conducted. Respondents of the primary study were represented by 367 marketing practitioners with 22 different marketing professions, representing 11 countries from 18 different industries, mainly from the Baltic and Caucasus regions. Based on findings and analysis, conclusions, limitations, and concepts for the future study were highlighted. The findings synthesized AI drivers, barriers, and outcomes in marketing. Further, outcomes confirmed a positive relationship with unitizing AI marketing in long-term strategic marketing planning. The paper offers practical guidance to the companies or inspires marketing leaders to use AI in data-driven marketing strategies. It has a significant value due to the complexity of the current marketing environment, whether micro or macro. Marketing Practitioners are searching for added value to prove the applicability of AI marketing in everyday strategies for decision-makers.

Navigating the city: Role of property-market intelligence channels in urban governance networks

This study presents a novel perspective on the impact of market-intelligence channels on property markets and the subsequent effects on the formation of alliances among public- and private-sector actors in urban governance. I argue and demonstrate that property actors, especially investors, collaborate through knowledge coalitions by utilizing the market-intelligence channels they created, not only to navigate property markets but also to establish the mode of regulation in urban development. By using a strategic-relational perspective, it is possible to analyze the underlying institutional infrastructure of the property market as a dynamic system shaped by the relationships and interactions among various social and economic actors. In addition to forming various marketing or lobbying coalitions, property actors forge alliances by converting pertinent information—such as locational analysis, socioeconomic data, policy and land-use forecasts, permit conditions, and planning strategies—into advanced market intelligence. This process allows them to define the norms, rules, and principles to be negotiated with public policymakers and enhance their positions in knowledge-based governance networks. To obtain empirical evidence about Amsterdam’s property market, a comprehensive data set was created to identify the influential actors. Extensive deskwork was conducted to map the diverse channels and connections of market intelligence. Key players in the property market were also interviewed to provide a comprehensive view of the active market-intelligence channels in governance networks.

Market intelligence applications leveraging a product-specific Sentence-RoBERTa model

Market intelligence, which collects and analyzes market trends and competitive landscape, is crucial for business success in the market. In particular, defining market scope is important because the market analysis outcomes vary depending on where the market boundaries are. However, this has been challenging due to the difficulty in scoping a number of similar products into the target market appropriately. To address this challenge, this study devised a novel method for acquiring reliable market intelligence utilizing the Sentence-RoBERTa (SRoBERTa) model, a pre-trained language model (PLM) specialized in computing sentence similarity. The SRoBERTa model was fine-tuned with 26,248,771 data on product relations and built a product-specific SRoBERTa model (named Pro-SRoBERTa) for effectively identifying the products that fall within the market scope. It outperformed the untrained model by up to 82.8 % on the hierarchical product categorization task. Finally, the Pro-SRoBERTa model was applied to determine the scope of the market followed by obtaining diverse market intelligence. The analysis module was successfully implemented in the market information system using a large-scale, real-world dataset.

Unveiling creativity in artisanal beer through cultural and collective intelligence: a study of market in Mexico

PurposeThe principal objective of the study is to analyze the influence of ethnicity, culture and collective intelligence in entrepreneurial creativity, innovation and marketing of artisanal beer in Mexico.Design/methodology/approachThe qualitative data have been gathered by conducting four workshops with twelve respondents in each workshop across four states of Mexico comprising Mexico City, Puebla, Queretaro and Guadalajara. These workshops were held for four hours during the pre-lunch period over the weekends, which was participated by a mix of entrepreneurs and consumers.FindingsArtisanal entrepreneurship is driven by the culture, ethnicity, collective intelligence and frugal innovations. Ethnic products generate patriotic feeling and consumption for a social cause to encourage artisans at the grassroots with the local tags. Results also indicate that social media and crowd cognition play an important role in developing creative artisanal beer.Research limitations/implicationsThis study is founded on the theoretical maxims of social learning theory (SCT), social cognitive theory and theory of creativity. The contextual interpretation of SCT explains the socialization of concepts by modelling emotions and behavior to derive structural experiences as observed in artisanal entrepreneurship.Practical implicationsEntrepreneurs can develop brand emotions, boost anthropomorphic feelings and inculcate the sense of nationalism among consumers to market ethnic brands and develop social consciousness towards consumption of “Made in Mexico” products.Social implicationsArtisanal beer face major challenge of customer outreach by enhancing the brand proximity and ethnic values. Ethnic products hold a strong image in niche market and need to be stimulated by the experience sharing through social media and community interactions.Originality/valueThis research study significantly contributes to the existing literature on ethnic entrepreneurship and creativity using innovative research approach.

Pineapple Production and Its Marketing Channels in Bangladesh: Present Status, Prospects and Challenges

Pineapple production offers a unique opportunity for the farmers due to the favorable climatic conditions in Bangladesh. Consequently, pineapple cultivation in Bangladesh round the year, has picked up on quite a large scale. The nutritional condition of Bangladeshi individuals who are severely malnourished may be improved by pineapple. Pineapple cultivation is trending upward. Producing pineapples on the same site benefits farmers significantly more than growing other crops. Also, high return in comparison to other existing crops, easy cultivation process, possibility of intercropping, favorable weather condition are the main reasons behind its increasing production. Growing demand for chemical-free farm fresh pineapples among consumers has led farmers to pursue balanced use of pesticides and ripening agents. However, the demand for fertilizers and other chemicals has been increasing. Despite the fact that farming has grown highly lucrative, there are apparently many marketing and production related challenges that farmers must overcome. It is necessary to enhance Bangladesh's pineapple production and marketing system for the benefit of both producers and consumers, as it is ineffective and disorganized. Policymakers, extension agents, researchers and other actively involved marketing professionals should provide feedback to enhance their approach for raising future fair pricing by increasing production and marketing effectiveness. Infrastructure and technological investments, marketing channel diversification, farmer capacity building, supportive legislative reforms and enhanced market intelligence systems to boost competitiveness should all be included in sustainable pineapple farming methods, which can make pineapple farming more profitable.

The effects of AIoT-SC strategic alignment on SC intelligence and NPD performance

ABSTRACT The emergence of AIoT has profoundly influenced supply chain management (SCM) and new product development (NPD) performance. However, the AIoT and its strategic alignment with the supply chain (SC) strategy have not received equal attention in academia and industry. By incorporating concepts of strategic alignment, AIoT, and NPD from previous literature, this study proposes a new concept of AIoT-SC strategic alignment and examines its role in SC intelligence (SCI) and NPD performance. By using a partial least squares structural equation modelling (PLS-SEM) approach, the survey data results demonstrate that AIoT-SC strategic alignment in planning, making, delivery, sourcing, and return is positively related to SC intelligence regarding market intelligence quality (MIQ), SC partner intelligence quality (SCPIQ), and NPD performance. The study’s findings can guide managers in improving firms’ business functions through AIoT-SC strategic alignment. Furthermore, this research provides researchers with sound theoretical grounds/basis for further academic development of AIoT, SCM, and NPD.

SMEs internationalization! Market intelligence and entrepreneurial orientation influence on international performance: a moderation model

PurposeDrawing on resource-orchestration theory (ROT), this study investigates the influence of market intelligence and entrepreneurial orientation (EO) on international performance of born global (BG) small and medium enterprises (SMEs) in emerging markets with the mediating role of global technological competence. Quality focus is used as a moderator between global technological competence and international performance.Design/methodology/approachData were gathered through a survey, and PLS-SEM was employed for hypotheses testing with a sample of 256 BG SMEs.FindingsThe results showed that market intelligence, EO, global technological competence and quality focus positively relate to international performance. Moreover, market intelligence and EO are positively associated with global technological competence. Besides, global technological competence significantly mediates the relationship between market intelligence, EO and international performance. Finally, quality focus strengthens the positive relationship between global technological competence and international performance.Practical implicationsOur research demonstrates that if management utilizes or invests on market intelligence, EO, global technological competence and quality focus, then the BG SMEs will increase their international performance.Originality/valueThe paper contribution lies in its focus on exogenous constructs (i.e. market intelligence, EO, global technological competence and quality focus) to determine the international performance of born global SMEs in emerging markets.

How artificial intelligence can enable data classification for market sizing - Insights from applications in practice

Determining the size of the addressable market is a key aspect of market intelligence and requires identifying and delineating projected budget data from potential customers. The market intelligence arena is characterized by a wide range of disparate sources, many of which are unstructured, ranging across competitive, market, financial, and technology sources, and typically necessitating significant manual work to analyze, reconcile, and integrate. The authors present an approach for classification of data from one of these sources, facilitating aggregation and analysis of intelligence information. We describe a concept proof using machine learning that extends a model for automatic mapping of publicly available budget data to segments and subsegments of a market segmentation taxonomy. This approach automates the tagging of market and market segment for each program and cost element by training classification models on the manually labeled historical data. We describe the evaluation and use of multiple natural language processing (NLP) and classification modeling methods. This work's contribution is demonstrating how NLP and machine learning techniques can provide useful data classification and automatic classification even when source data diverges from its specified taxonomic description.

Identifying green skills gaps through labor market intelligence

Identifying green skills gaps through labor market intelligence

Marketing Channels of Pomegranate in Pune Division of Maharashtra, India

Pomegranate, scientifically named Punica granatum L., is prized globally, particularly in tropical and subtropical regions like India, Iran, and Spain. Pomegranate cultivation has surged in India, notably in Maharashtra, Gujarat, and Karnataka, with India emerging as a top global producer. In 2020-21, India expanded pomegranate cultivation to 2.88 lakh hectares, yielding 32.70 lakh tonnes. Maharashtra led with 54.89% of national production and 59.38% of cultivated area, underscoring its key role despite slightly lower productivity than the national average. The objectives of the study were to identify different marketing channels of pomegranate, to estimate the price spread and marketing efficiency of identified marketing channels and to identify problems faced by stakeholders. The primary data was collected from 60 Pomegranate farmers and from 30 intermediaries. The study identified four different pomegranate marketing channels. Channel-1 (Producer →Pre-harvest contractor → Wholesaler-cum-commission agent→ Retailer →Consumer), Channel-2 (Producer →Wholesaler-cum-commission agent→ retailer → consumer), Channel-3 (Producer →Collection Center (CC) → Distribution Center (DC) → Consumer), Channel-4 (Producer →Village trader →Wholesaler-cum-commission agent →Retailer → Consumer). Channel-3 providing producers with 69.78% of the consumer price and demonstrating highest efficiency (2.31) for its Acharya-Agarwal marketing efficiency method was used. Pomegranate producers face challenges including high transportation costs, storage issues, price volatility, and market information deficits. Production problems include pest infestations, high input costs, and labor shortages. Intermediaries grapple with quality variation, labor scarcity, and price fluctuations. Strategic interventions in infrastructure, logistics, and market intelligence are crucial for sustainable profitability.

Dot-com and AI bubbles: Can data from the past be helpful to match the price bubble euphoria phase using dynamic time warping?

The article investigates the existence of a price bubble in the artificial intelligence market, employing the Generalised Supremum Augmented Dickey-Fuller test and dynamic time warping methodology. It proposes a method to detect the end of the price bubble euphoria phase, generating an average profit of close to 7 % over 5 days and over 10.5 % over 20 days, with almost 90 % effectiveness. The study found that the AI market experienced a phase of euphoria due to the COVID-19 pandemic. Four companies – META PLATFORMS, WORKDAY, SALESFORCE and NVIDIA CORPORATION – were identified, whose stock prices currently resemble the euphoria phase.

Artificial Intelligence in Marketing

This thesis explores the application of artificial intelligence in marketing and the trends, challenges and opportunities of digital transformation. Firstly, it introduces the definition, development history and main technology and application areas of artificial intelligence. Then, it analyses the overview of the application of AI in the business field, including personalised recommendation, intelligent customer service and other aspects. Subsequently, how AI has changed marketing strategies and practices is explored and compared with traditional approaches. In terms of specific applications, the role and benefits of personalised recommendation systems, intelligent customer service systems, etc. are highlighted. In addition, the application of data-driven market trend analyses, intelligent predictive models, etc. in marketing is examined. Finally, the impact of AI and digital transformation on marketing is summarised, highlighting the need for companies to strengthen data security and management, and to grasp the opportunities of technological development to achieve sustainable development and competitive advantage.

How to be a fanboy: Wizard magazine and the pedagogy of comic book fandom

ABSTRACT The 1990s were a pivotal time in comics history, and during this period, there was arguably no more important outlet than Wizard magazine. The magazine played an important pedagogical role as both a gateway to and a gatekeeper of fandom. Initially launched as a guide to collecting comic books, Wizard later evolved into a lifestyle and entertainment magazine for a loosely defined “fanboy” readership. While arguably more accessible than the comics it covered, it addressed its audience in exclusive terms, assuming a normatively male, heterosexual, and white fan. Based on a close reading of a sample of eight self-reflective “milestone” issues, this article assesses Wizard as not merely a purveyor of market intelligence to comic book speculators but as a cultural artifact engaged in defining the meaning of fandom for a generation of comic book readers.

The Role of Artificial Intelligence in Social Media Marketing and Its Sustainable Prospects

Technology is rapidly evolving, and we are constantly exposed to new and inventive solutions. Artificial intelligence is a rapidly developing technology that has the potential to revolutionize the world through intelligent machines. So artificial intelligence is surrounds us. A computer or robot operated by a computer can perform human-like skills like reasoning, discovering meaning, generalizing, and learning through experience. Social media marketing promotes firms and their protection services to their target audience, empowering people, small enterprises, and major corporations to monitor, evaluate, and optimize their online presence. This study aims to analyze the impact of artificial intelligence on social media marketing and its future prospects. The study relies on secondary data analysis to provide empirical support. This study explores the application of artificial intelligence in social media marketing. This paper provides a framework for understanding the usage of artificial intelligence in social media marketing and the tools available.

Revisiting the Policy Implications of Medical Tourism in the Post-COVID-19 Pandemic From a Malaysian Perspective: A Qualitative Study.

Background Malaysia has been one of the most prominent destination countries for medical tourism. The industry received significant government support to create a conducive environment for its growth, such as the provision of an investment tax allowance for the facilities participating in medical tourism and the establishment of the Malaysia Healthcare Travel Council (MHTC) to coordinate collaboration between various industry stakeholders to promote medical tourism activities at the international level and facilitate inbound medical tourists. The establishment of the MHTC facilitates collaboration between various industry stakeholders. In addition to facilitating medical tourism activities, MHTC is also involved in analysing relevant data, including but not limited to the socio-demography of medical tourists, the trend of their healthcare service utilisation, revenue generated, and market intelligence to promote the industry's growth. The council serves as a medium to facilitate the collaboration of stakeholders such as the hospitals participating in medical tourism, the Association of Private Hospitals Malaysia, the Malaysian Society for Quality in Health, and various government agencies, including the Ministry of Health and the Department of Immigration, Malaysia. We explore the policy-related implications of medical tourism and its relationship with the Malaysian national healthcare system. Methodology We revisited Pocock and Phua's conceptual framework of policy implications for medical tourism to explore its relevance after more than a decade of intensive government support and the aftermath of the COVID-19 pandemic. We employed a qualitative case study design using semi-structured, in-depth interviews with stakeholders from the Ministry of Health Malaysia, the private health sector, professional bodies, academics, and health-related civil society organisations. Results Our study found that many issues identified in the original framework remain relevant after over a decade. However, we also identified additional implications, such as the role of insurance portability in encouraging the growth of international hospital accreditation and the issue of equitable access to healthcare within the context of the current Malaysian healthcare system in the aftermath of COVID-19. Conclusion Due to its vulnerability, there is a need to develop a strategic collaboration that includes incorporating medical tourism activities into a broader framework, such as promoting aged care within the retirement destinations package for expatriates, which could ensure its sustainability instead of relying solely on medical tourism activities. In the meantime, policy implications arising from the industry remain relevant and should be addressed through a comprehensive structural reform of the national healthcare system involving stakeholders from the public and private health sectors.

Novel approaches to enable equitable access to monoclonal antibodies in low- and middle-income countries.

Monoclonal antibodies (mAbs) are revolutionizing management of non-communicable diseases in high-income countries and are increasingly being advanced for a range of infectious diseases (IDs). However, access to existing mAbs is limited in low- and middle-income countries (LMICs), and investment in developing fit-for-purpose mAbs for IDs that disproportionately affect LMICs has been limited. Underlying these access barriers are systemic challenges, including a lack of commercial incentives to target LMIC markets and complexity in manufacturing and regulatory processes. Novel strategies are needed to overcome systemic access barriers for mAbs. We outline key areas where new approaches could address these barriers, based on a multistakeholder consultation in March 2023. Three disease-market archetypes are identified to guide thinking about business models tailored to different contexts. New business models are needed to incentivize development and manufacturing of ID mAbs and to ensure mAbs are optimized with a target product profile and cost of goods that enable use in diverse LMIC settings. Lessons can be applied from voluntary licensing strategies and product development partnerships that have shown success in catalysing development and affordable supply for a range of infectious diseases. Technology transfer will be key to expand LMIC research and manufacturing capacity and to enable sustainable and diversified supply. Improved market intelligence, demand aggregation mechanisms, and portfolio-based manufacturing models could be used to de-risk commercial investment and establish a sustainable manufacturing ecosystem for affordable mAbs. Novel regulatory approaches and robust technology transfer may reduce data requirements and timelines for biosimilar approvals. Trailblazer products, with coordinated "end-to-end" support from funders, can demonstrate proof of concept for pathways to accessible mAbs across a broader range of LMICs. Research funders; local, regional, global health agencies; and, private sector partners should commit to implementing innovative partnerships and end-to-end strategies that enable equitable access to mAbs for infectious diseases in LMICs.

The use of artificial intelligence and machine learning in e-commerce marketing

The object of this research is the use of artificial intelligence (AI) and machine learning (ML) in e-commerce marketing strategies. Traditional e-commerce marketing approaches often lack a personalized customer experience and find it difficult to adapt to changing consumer behavior. The integration of artificial intelligence and machine learning offers a solution to these problems, enabling real-time marketing initiatives and data analysis. Studies have shown that the use of artificial intelligence and machine learning in e-commerce marketing has led to improved customer relationship management, increased operational efficiency, and more customer-centric advertising strategies. In addition, technologies such as visual search, virtual personal shoppers, and real-time product targeting have changed the e-commerce landscape by providing interactive and personalized shopping experiences. Artificial intelligence and machine learning algorithms analyze vast amounts of customer data to identify patterns, preferences and trends, enabling e-commerce businesses to conduct targeted marketing campaigns and optimize product offerings. Using advanced technologies, companies can streamline operations, increase customer satisfaction and stay ahead of the competition in the digital marketplace. This data suggests that integrating artificial intelligence and machine learning into e-commerce marketing strategies can benefit businesses by improving customer engagement, increasing sales, and gaining a competitive advantage. However, a successful implementation requires access to quality data, a robust AI infrastructure, and ongoing monitoring and optimization to ensure effectiveness and relevance in a dynamic marketplace.

Emotional Intelligence in Marketing: Connecting Brands with Consumers

This study investigates the relationship between emotional intelligence, brand communication strategies, consumer brand perception, and customer loyalty within the context of PT. Lautan Luas Tbk. Through quantitative analysis utilizing Smart PLS, data was collected from a sample of 80 individuals using random sampling techniques. The results reveal significant direct effects of emotional intelligence and brand communication strategies on consumer brand perception and customer loyalty, as well as significant indirect effects of both emotional intelligence and brand communication strategies on customer loyalty through consumer brand perception. Specifically, higher levels of emotional intelligence among marketing staff and effective brand communication strategies positively influence consumer brand perception, subsequently leading to increased customer loyalty. These findings emphasize the importance of emotional intelligence and strategic brand communication in cultivating strong brand-consumer relationships and driving sustainable business growth.

Accounting Information Systems for Strategic Management: The Role of Intellectual Capital in Mediating the Relationship between Customer, Company, and Performance

This research aims to investigate the role of Intellectual Capital (IC), Managing Accounting Information Structures (MAIS), Internal Task Productivity (ITP), and Customer Performance (CP) in moderating the link between strategies and Financial Productivity (FP). The population for this study consisted of medium and enormous manufacturing enterprise business units located in Java. In this study, the enterprise unit is the specific part of the firm accountable for producing and marketing a product or group of items. It is organized based on the type of item that it deals with and operates independently from other companies or divisions within the parent organization. The company unit has a distinct set of competitors, separate from those of different units. It is overseen by an executive liable for establishing and carrying out strategies to meet the specified profit goal. An approach to invention, including product invention, task creativity, and technology, significantly influences firm performance if there is a robust ITP, dependable market analysis, intelligence systems, and effective competitive positioning. The ITP enhances the alignment between the approach and the FP by including operational management activities, customer management chores, Invention Tasks (IT), and regulatory and social tasks. This research found no impact of IC on CP and ITP; similarly, MAIS did not influence FP. Information systems affect financial performance by ITP infrastructure and corporate processes. The contributions of this study include the novel application of the continuous invention approach, integrating product invention and task and information technological devices, which past studies have not explored; the utilization of IC, MAISs, ITP, and CP as mediating factors; the adoption of a holistic method by incorporating aspects of IC, MAIS, and non-FP as contextual factors, about contingency methods, which have not been investigated in the previous study; the development of novel ideas in conjunction with the balanced scoring framework; and the examination of both single and numerous mediating effects on the impact of sustainable approaches to the invention on FP.

Adaptation of strategic models of enterprises to industry markets

Introduction. In the contemporary conditions of global business, enterprises constantly face challenges associated with the need to adapt to dynamic industry markets. Rapid technological advancements, shifting consumer preferences, and unpredictable economic conditions require a strategic approach that enables enterprises to quickly and effectively adapt to them. The relevance of this study is driven by the necessity for enterprises to remain competitive and resilient amidst constantly changing market dynamics. In today’s fast-paced business environment, strategic flexibility is a prerequisite for survival and growth. Achieving organizational success requires understanding how enterprises can adapt their strategic models in accordance with the dynamics of the industry market. The purpose of this paper is to explore various strategies and approaches employed by enterprises to adapt to the dynamic structure of industry markets. Results. Based on a thorough analysis of existing literature and real-life examples, this paper draws several key conclusions. Firstly, it emphasizes the importance of strategic flexibility and agility for enterprises to seize new opportunities and mitigate risks. Secondly, it underscores the significance of market intelligence and data-driven decision-making to justify strategic adaptation. Thirdly, it examines the role of organizational culture, leadership, and innovation in enhancing enterprise adaptability. The conclusions drawn from this study highlight the importance of enterprises adopting a dynamic and iterative approach to strategic planning. Static, one-size-fits-all strategic models are no longer viable in today’s unstable markets. Instead, enterprises must foster a culture of flexibility and innovation, constantly reassessing their strategies in response to changing market trends and competitive pressures. Despite providing valuable insights into the adaptation of strategic models to industry market dynamics, some areas for further research remain insufficiently explored. Future research could delve into a deeper examination of specific industries or regions, elucidating how contextual factors influence strategic adaptation.