Volume 12 (2026-27)

Marketing analytics is entering a period of accelerated computational growth. Advances in artificial intelligence (AI), automation and emerging optimisation techniques promise gains in modelling power, personalisation and real-time decision making. At the same time, these forces are exposing a growing weakness: the declining reliability of identity data. Here, ‘identity’ refers to the persistence and fidelity of analytical identifiers used for measurement and decisioning, rather than legal identity or personally identifiable information. Synthetic activity, autonomous agents, behavioural mimicry and the fragility of credential systems under post-quantum threats increasingly undermine identity continuity across channels. As systems become faster and more autonomous, identity instability intensifies: attribution models become fragile, segmentation accuracy degrades and optimisation engines converge on signals that may not reflect genuine human behaviour. Analytical confidence can increase even as trust in identity signals declines, widening the gap between model sophistication and insight reliability. By 2030, a primary constraint on marketing effectiveness will be the continuity and authenticity of identities behind the data. This paper examines why identity integrity becomes a bottleneck for measurement, audience definition and optimisation performance in high-compute environments. It introduces an identityresilient analytics framework integrating post-quantum-ready identity binding, identity confidence scoring, AI containment and identity-aware governance, and concludes with a practical roadmap to help organisations preserve analytical reliability and operate with confidence in an increasingly synthetic digital ecosystem. This article is also included in The Business & Management Collection which can be accessed at http://hstalks.com/business.
Keywords: identity integrity; marketing analytics; agentic AI; synthetic behaviour; attribution accuracy; post-quantum identity

As customer journeys in the enterprise sector become increasingly complex, involving multiple stakeholders and prolonged sales cycles, traditional last touch attribution (LTA) models fail to capture the contribution of early and mid-stage interventions. This practical implementation case study documents how a high-touch marketing organisation transitioned from LTA to a data-driven multi-touch attribution framework built on Markov chain modelling. The paper demonstrates how shifting to an enterprise attribution model reveals the correlational value of ‘nurturing’ touch points — such as blogs and webinars — that are often undervalued by single-touch heuristics. The paper also addresses the organisational challenges of this transition, proposing a three-phase implementation roadmap: technical proof-of-concept, internal marketing education and sales alignment. The findings indicate that although algorithmic models offer a more holistic representation of the customer journey, their effectiveness depends on addressing the perceived ‘black box’ nature of the methodology. Reframing the output around ‘marketing influence’ rather than credit allocation helps build trust in the model and fosters shared accountability between sales and marketing. This article is also included in The Business & Management Collection which can be accessed at http:// hstalks.com/business.
Keywords: multi-touch attribution; Markov chains; B2B marketing; sales-marketing interface; change management; marketing analytics

The digital revolution has accelerated the adoption of artificial intelligence (AI) in marketing and sales to enhance organisational resilience and efficiency. This study combines bibliometric analysis with expert interviews to examine how AI is applied in these functions. A systematic review (2006–2024) using PRISMA criteria was analysed with VOSviewer and Bibliometrix, and complemented by interviews with 23 marketing professionals. Six key themes emerged: sales, artificial intelligence, supply chain management, sustainability, COVID-19 and information systems. These highlight AI’s role in optimisation, customer engagement and operational efficiency. Interview findings reinforce the importance of predictive analytics, personalised marketing and automated decision making. The study provides an integrative overview of how AI supports marketing and sales resilience, with implications for practitioners and future research. This article is also included in The Business & Management Collection which can be accessed at http://hstalks.com/business.
Keywords: artificial intelligence; marketing resilience; sales resilience; sales strategy; digital transformation; sustainability

Neuromarketing has expanded rapidly over the past two decades as neuroscience tools have become more accessible to marketing practitioners and researchers. Nevertheless, the field still lacks an integrated practice-oriented overview that explains how its main themes have developed. This study addresses that gap by applying a structured text-mining approach to 4,292 scholarly publications drawn from major academic databases. Using natural language processing techniques such as text cleaning, keyword extraction, topic modelling and cluster analysis, the study identifies the main research streams and shows how conclusions were derived from the data. The analysis demonstrates that neuromarketing has evolved into a broad multidisciplinary domain shaped by technologies such as fMRI, EEG, artificial intelligence, virtual reality and wearable sensors. Ethical concerns have also intensified, with growing attention to autonomy, privacy and the responsible use of consumer data. While established theories such as the theory of planned behaviour and dual-process models continue to guide research, new directions focus on technology—consumer interactions, emotional processing and predictive analytics. The findings clarify where the field has generated genuinely new insights, for example through multimodal measurement of consumer emotion, and where it primarily reinforces existing knowledge. Despite significant progress, challenges remain in theoretical integration, methodological consistency and the incorporation of practical neuroethical guidelines. By showing how large-scale text mining can map conceptual evolution and reveal hidden patterns, this paper offers researchers and practitioners a clearer understanding of the field’s trajectory and guidance for developing more coherent, transparent and ethically informed neuromarketing practices. This article is also included in The Business & Management Collection which can be accessed at http://hstalks.com/business.
Keywords: neuromarketing; natural language processing; text mining; consumer neuroscience; neuroethics

Retail membership clubs are an important yet under-researched area of scholarly research in retailing. This paper examines how shoppers belong to, and shop at, membership clubs. It situates membership clubs within the broader context of the human need for belonging, alongside recent trends towards greater social isolation. Using a largescale syndicated survey, the paper analyses self-reported behaviours related to membership clubs. It explores the social functions these clubs serve and examines how membership relates to shopper characteristics, marketing influences, happiness levels and other aspects of people’s lives. The results indicate that membership is strongly associated with being married, having children, higher income and higher overall spending levels. The most prevalent membership programmes are found to be Amazon Prime, Costco and Walmart+, with most members belonging to multiple clubs. This article is also included in The Business & Management Collection which can be accessed at http://hstalks.com/business.
Keywords: retailing; membership clubs; belonging; shopper experience; happiness; retail analytics

Emotions play a key role in marketing, yet their role in sequential decision making is not well understood. Common wisdom holds that positive and neutral emotions are best, but underestimates the value of negative emotions. This paper examines how emotional states affects decisions in marketing negotiations through the lens of game theory. Building on empirical research using ultimatum games, this paper demonstrates that both positive and negative emotional priming increase generous behaviours compared with neutral conditions. The findings of this paper offer actionable insights for marketing practitioners seeking to optimise negotiations, promotional offerings and customer engagement strategies. This paper challenges traditional rational actor models by showing how systematic emotional effects influence economic decisions that marketers can measure, test and strategically incorporate into customer experiences. This article is also included in The Business & Management Collection which can be accessed at http://hstalks.com/business.
Keywords: marketing decision making; emotions; game theory; generosity