Journal of Strategic Marketing

An explosion of interest in marketing analytics and metrics has occurred in recent years from both academia and practice due to the big data revolution and the advent of artificial intelligence (AI) (Wedel & Kanan, 2015). This explosion is driven by the fact that firms that inject analytics and AI (A & AI) into their value chain experience higher productivity than their competitors. Data analytics is the set of techniques focus on gain actionable insight to make smart decisions from a massive amount of data. There is an increasing amount of research effort in the merge between data analytics and Industry 4.0 which evolves from industry 3.0 that limits its focus on routine operation (Duan & Xu, 2021). Marketing analytics, originated from business analytics (Holsapple, Lee-Post, & Pakath, 2014), refers to the collection, management, and analysis of data to extract useful insights to support marketing decision-making (Cao et al., 2019; Germann, Lilien, & Rangaswamy, 2013; Hanssens & Pauwels, 2016; Wedel & Kannan, 2016). The sheer magnitude of big data and its inherent diversity (text, numbers, emoji, video) are making traditional techniques obsolete which is propelling to conduct research on marketing analytics (comprising of both quantitative and qualitative data) (Sheth, 2021). Marketing analytics include descriptive, predictive and prescriptive modelling and their application to real-world business practices, including Amazon, e-Bay, Netflix, Linked In, ASOS, and Facebook, to name a few (Wedel & Kannan, 2016; Akter et al., 2022). Marketing analytics can be used to visualise and describe our consumer behaviours, predict future sales, and prescribe effective means to enhance competitive advantage and firm performance (Cao et al., 2019; Germann et al., 2013; Xu et al., 2016; Liang, Li, Zhang, Nolan & Chen, 2022).

In addition to marketing analytics, marketing metrics or key performance indicators (KPIs) should be set upfront to establish a connection between marketing goals and performance (Farris et al., 2010). Metrics should be easily replicated, easy to use and provide actionable insights to establish competitive advantages. Marketing analytics and metrics are gaining momentum in the data economy to create and capture value using data-driven insights (Misirlis & Vlachopoulou, 2018). However,  marketing analytics is currently beset with various algorithmic biases which question its applications in various contexts, such as data bias, model bias and contextual biases. Undoubtedly, marketing analytics play a key role in generating insights from big data to improve marketing decision-making and firm’ overall performance in various context such as service industry (Akter et al., 2019), social media (Wang et al., 2021; Sivarajah et al., 2020), public sector (Kopalle & Lehmann, 2021). and education sector (Pringle & Fritz, 2019). However, research is limited about the mechanisms through which it can be used to achieve sustained competitive advantage (Cao et al., 2019). Furthermore, the large potential marketing analytics is still largely untapped, unexplored (Ariker, Diaz, Moorman, & Westover, 2015; Cao et al., 2019; McKinsey, 2016; Wedel & Kannan, 2016) despite few research attempts to demonstrate the impact of marketing analytics improve firm competitiveness and/or performance (Germann et al., 2013; Hanssens & Pauwels, 2016; Xu, Frankwick, & Ramirez, 2016).

To tap into these new developments in marketing, the Guest Editors humbly welcome high-quality/high-impact full research papers, conceptual, methodological, qualitative, or quantitative contributions from scholars around the world that offer insight into this specific issue of marketing.

This special issue is assocaiated with the Marketing Analytics, Methods and Modelling track of ANZMAC Conference 2022, Australia. Conceptual and empirical work from the ANZMAC conference are encouraged to submit full drafts for consideration at the Journal of Strategic Marketing via the normal review protocol.

Suggested topics, but are not limited to:

1. Management of resources and capability development for analytics based marketing system (e.g., text mining, machine learning, visual analytics, fuzzy logic)
2. Descriptive, diagnostic, predictive and prescriptive analytics-based marketing models
3. Ethics, privacy and security issues related to Marketing Analytics, Methods and Modelling in the organization
4. Marketing analytics for new product/service development, pricing strategies, customer services, channel optimisation, and omnichannel promotional strategy.
5. Managing customer relationships using analytics and models
6. Marketing analytics capability, competition and firm performance
7. The role of the internal environment in marketing analytics and sustainable competitive advantages
8. Marketing analytics, marketing metrics and key performance indicators
9. Measuring the effectiveness and return on investment (ROI) of marketing expenses
10. Developing a global marketing dashboard encapsulating the essential metrics
11. Linking marketing metrics to financial performance and competitive advantages
12. Algorithmic biases in AI-based marketing models.
13. Marketing Analytics and models for metaverse environment.
14. Application of Marketing Analytics and models in B2B sector
15. Application of Marketing Analytics and models in shared economy
16. Application of Analytics and models in non-profit organizations and in public sector
17. Critical success factors and Strategies to overcome the Challenges of applying Analytics and models in business application
18. Future of Marketing analytics and modelling

Instructions for authors can be found at:

Please note that the Special issue submission is open to everyone. Authors should submit the manuscript by December 31, 2023, via the Journal’s online submission site. Please follow the author guidelines for submissions in the journal website (https://www.tandfonline.com/action/authorSubmission?show=instructions&journalCode=rjsm20)

During submission please choose “Special Issue Paper” as the submission type and select this special issue title The Future of Marketing Analytics from the drop-down menue to ensure that it will be reviewed for this special issue.

Manuscripts submitted after the deadline may not be considered for the special issue and may be transferred, if accepted, to a regular issue.

Papers will be subject to a strict review process under the supervision of the Guest Editors, and accepted papers will be published online individually, before print publication.

Instructions for AuthorsSubmit an Article