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This paper aims to improve understanding of data-driven marketing by examining the experiences of managers implementing big data analytics in the marketing function. Through a series of research questions, this exploratory study seeks to define what big data analytics means in marketing practice. It also seeks to uncover the challenges and identifiable stages of big data analytics implementation.

A total of 15 open-ended in-depth interviews were conducted with marketing and analytics executives in a variety of industries in Ireland and the USA. Interview transcripts were subjected to open coding and axial coding to address the research questions.

The study reveals that managers consider marketing big data analytics to be a series of tools and capabilities used to inform product innovation and marketing strategy-making processes and to defend the brand against emerging risks. Additionally, the study reveals that big data analytics implementation is championed at different organizational levels using different types of dynamic learning capabilities, contingent on the champion’s stature within the organization.

From the qualitative analysis, it is proposed that marketing departments undergo five stages of big data analytics implementation: sprouting, recognition, commitment, culture shift and data-driven marketing. Each stage identifies the key characteristics and potential pitfalls to be avoided and provides advice to marketing managers on how to implement big data analytics.

The objective of this paper is to investigate IMC metrics in the lens of an institution-wide change management process, and to do so, the authors develop and test an organizational data quality enhancement model.

Qualitative research was conducted, with a follow-on quantitative pre-test. A subsequent, larger-scale quantitative survey resulted in a total of 128 responses, 124 useable. A regression analysis was conducted using the factor scores of the six organizational dimensions as independent variables and overall data quality as the dependent variable.

The findings show that overcoming poor IMC data quality requires a corporate culture that reduces cross-functional and departmental divides. The authors also support the idea that horizontally organized learning organizations not only have superior IMC data, but they also achieve higher rates of return on their cross-platform IMC efforts.

The research has limitations in terms of substantive generalizability, since it focuses on one industry within the USA. Future research can expand to other industries and expand to a global setting in order to replicate these findings.

Most improvement seems to be needed in the area of sharing customer data. The findings provide a signal to marketing organizations that want to connect with their customers that data quality must be a strategic priority, with appropriate processes in place to manage data at every touch point.

Research is needed that establishes effective methods for measuring the success of data-driven communication efforts to support management.

The paper aims to present a study of the question of customer information management in business‐to‐business (B2B) firms, what distinguishes firms that manage customer information well, and what internal processes are necessary for success.

This paper summarizes the themes from several research studies using both qualitative and quantitative methods.

The study finds that companies that distinguish themselves from others in the area of customer information management practices pay attention first to their company's overall strategy, establish and/or enforce data quality standards, involve functional departments in the development of customer databases and their applications, and use both relational and transactional data in their data applications.

Managers in this area would do well to follow the precepts suggested in this work, especially in terms of developing quality databases before embarking on a customer marketing strategy.

The value of the paper is the consistent themes throughout research studies in various B2B contexts.