Abstract
Nowadays, Big Data and Artificial Intelligence (AI) play an important role in different functional areas of marketing. Starting from this assumption, the main objective of this theoretical paper is to better understand the relationship between Big Data, AI, and customer journey mapping. For this purpose, the authors revised the extant literature on the impact of Big Data and AI on marketing practices to illustrate how such data analytics tools can increase the marketing performance and reduce the complexity of the pattern of consumer activity. The results of this research offer some interesting ideas for marketing managers. The proposed Big Data and AI framework to explore and manage the customer journey illustrates how the combined use of Big Data and AI analytics tools can offer effective support to decision-making systems and reduce the risk of bad marketing decision. Specifically, the authors suggest ten main areas of application of Big Data and AI technologies concerning the customer journey mapping. Each one supports a specific task, such as (1) customer profiling; (2) promotion strategy; (3) client acquisition; (4) ad targeting; (5) demand forecasting; (6) pricing strategy; (7) purchase history; (8) predictive analytics; (9) monitor consumer sentiments; and (10) customer relationship management (CRM) activities.
Highlights
In recent years, the word “Big Data” has become increasingly popular
E-commerce, Artificial Intelligence (AI) technologies, Pradana, Sing, and Kumar (2017) suggest that and Big Data analytics used for generating the encompanies, to facilitate the interaction with the hanced customer insights that can be used to perconsumers on the corporate or e-commerce sonalize the products and services constitute an websites, can utilize Intelligent Conversational important building block for online relationships
As we could conclude from the literature review carried out in this article, Big Data analytics tools and AI find large application in the marketing field, especially in the domain of customer analytics and decision support systems
Summary
The word “Big Data” has become increasingly popular Both academics and non-academics use this term to designate large volumes of extensively varied data that are generated, captured, and processed at high velocity (Laney, 2001). Company management, supported by Big Data analytics tools, can make better decision about production quantity, stock control and inventory, sales forecasting, logistics optimization, supplier coordination, and purchase channels selection (Schneider & Gupta, 2016; Bradlow, Gangwar, Kopalle, & Voleti, 2017). Based on these premises, it is important to investigate how Big Data and AI should be leveraged strategically to plan the customer journey. The findings reveal how such data analytics tools can increase the marketing performance (i.e., media spend and touch point selection (see Edelman, 2010), and reduce the complexity of the purchase patterns and consumer activities
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