۱- Introduction

۲- Theoretical background

۳- Methodological approach

۴- Findings and discussions

۵- Conclusions, implications, limitations and further research

References

Abstract

The increasing use of Artificial Intelligence (AI) in Social Media Marketing (SMM) triggered the need for this research to identify and further analyze such expectations of potential users of an AI-based software for Social Media Marketing; a software that will be developed in the next two years, based on its future capabilities.
In this research, we seek to discover how the potential users of this AI-based software (owners and employees from digital agencies based in France, Italy and Romania, as well as freelancers from these countries, with expertise in SMM) perceive the capabilities that we offer, as a way to differentiate our technological solution from other available in the market.
We propose a causal model to find out which expected capabilities of the future AI-based software can explain potential users’ intention to test and use this innovative technological solution for SMM, based on integer valued regression models. With this purpose, R software is used to analyze the data provided by the respondents. We identify different causal configurations of upcoming capabilities of the AI-based software, classified in three categories (audience, image and sentiment analysis), and will trigger potential users’ intention to test and use the software, based on an fsQCA approach.

Introduction

Artificial Intelligence (AI) technologies are highly effective in monitoring social media (Sterne, 2017) in order to get a complete picture of what people interacting on social networks are discussing about a brand in their posts and comments (sentiment analysis). They are useful as well to determine how they can be approached with personalized content (audience analysis) and how the images they share enable savvy marketers to recognize logos of brands or companies active in social media content (image analysis). The AI tools provide effective support to social media marketers in their tasks to optimize audience, image and sentiment analyses by identifying the brandedcontent that carries out high customer engagement with social media (Ashley and Tuten, 2015). Machine learning (ML), based on algorithms that enable specialized AI software to identify patterns within big data and classify it in categories, is perfectly adapted to deep analysis of social media content (Cambria et al., 2012). To capture the value of Artificial Intelligence technologies’ application in Social Media Marketing, this study explores the perceptions of 150 experts (owners and marketers of digital agencies and freelancers) from three countries (Romania, Italy and France) on twelve predefined capabilities of a future Artificial Intelligence-based software focused on Social Media Marketing analytics on audience, image and sentiment analysis and inspired by the principles characterized in previous approaches adopted by scholars in systematic literature reviews (Iqbal et al., 2018; Kurnia, 2018).