Resumen de Data-driven marketing image: scale development and validation

Elena García y García, Francisco Rejón Guardia, Laura Berenice Sánchez Baltasar

• Purpose – This study develops and validates a measurement scale for assessing the corporate image of companies that use data-driven marketing in their decision-making and actions in online retailing.

  Theoretical framework – The study is grounded in theories of corporate image and consumer behaviour, integrating concepts of data-driven marketing and privacy to develop the DDMI scale.

  Design/methodology/approach – A mixed methods approach is employed, beginning with a deductive literature review and qualitative expert interviews to generate scale items, followed by a pilot study and a large-scale survey of 301 consumers via Amazon MTurk. Exploratory and confirmatory factor analyses are conducted to validate the scale.

  Findings – DDM strategies significantly affect how customers perceive a company’s image. The DDMI provides a validated scale that measures aspects that are important to customers, such as privacy concerns and personalised customer experience. It reveals that effective communication, efficient payment processes and robust customer support are vital for a positive corporate image.

  Practical & social implications – The study offers a novel tool to assess corporate image in environments characterised by high data usage. It enables companies to refine their DDM strategies by identifying how specific practices affect consumer perceptions.

  Originality/value – This research introduces the first validated scale to measure consumer perceptions of corporate image in DDM contexts. It advances marketing theory by capturing key dimensions of the digital era, personalisation, privacy and support.