Avoiding digital marketing analytics myopia: revisiting the customer decision journey as a strategic marketing framework

Online Reputation for Food Sector Exporters in the B2B Context: The Importance of Sustainability

Food exporting companies play a fundamental role in the development of international trade. However, the conceptualization and measurement of their online corporate reputation has not been extensively studied in Business to Business markets, unlike in Business to Consumer contexts. The aim of this research is to identify the variables that determine the online reputation of food companies operating in B2B markets, and to analyze their relationship with the volume of food exports. For this purpose, a three-stage quantitative and qualitative study has been developed, based on in-depth interviews with experts from export organizations and managers of Peruvian food exporting companies, the estimation of an Advanced Sentiment Analysis, the construction of a Total Online Reputation Index (TOR), and the development of regression analysis. The study has identified 13 variables that affect the online reputation of food exporting companies and indicates that the presence of sustainability content on their website and the number of pages visited positively affect the volume of food exports. Moreover, the TOR could have a significant explanatory capacity with respect to company exports. These results constitute a reference guide for both companies in the sector and official export agencies, highlighting the critical aspects to promote their exports.

Enhancing Marketing Provision through Increased Online Safety That Imbues Consumer Confidence: Coupling AI and ML with the AIDA Model

To enhance the effectiveness of artificial intelligence (AI) and machine learning (ML) in online retail operations and avoid succumbing to digital myopia, marketers need to be aware of the different approaches to utilizing AI/ML in terms of the information they make available to appropriate groups of consumers. This can be viewed as utilizing AI/ML to improve the customer journey experience. Reflecting on this, the main question to be addressed is: how can retailers utilize big data through the implementation of AI/ML to improve the efficiency of their marketing operations so that customers feel safe buying online? To answer this question, we conducted a systematic literature review and posed several subquestions that resulted in insights into why marketers need to pay specific attention to AI/ML capability. We explain how different AI/ML tools/functionalities can be related to different stages of the AIDA (Awareness, Interest, Desire, and Action) model, which in turn helps retailers to recognize potential opportunities as well as increase consumer confidence. We outline how digital myopia can be reduced by focusing on human inputs. Although challenges still exist, it is clear that retailers need to identify the boundaries in terms of AI/ML’s ability to enhance the company’s business model.