The information age, with the usage of big data, has created opportunities for smart marketing systems. Marketing data intelligence systems accelerate product innovation and growth strategies with the information obtained from the data mining techniques about the marketing stakeholders. The implementation and adaptation of creative, intelligent technologies aid marketers in speedy decisions and sustainable competitive strategies to gain a competitive advantage in the market that would help the organization's sustenance over the long term. This chapter explains marketing intelligence, its quotient, relevant theories, evolution, framework, the transformation of marketing intelligence systems from digital marketing to social engineering, the tools of marketing intelligence, and the benefits of marketing intelligence.
Top1. Introduction
The traditional approach to marketing intelligence considers the collection of data from surveys and internal sources on market competition, industry, and customers (Grooms, 2001). However, the contemporary approach to marketing intelligence considers data mining techniques and models to uncover marketing data intelligence (Kozlenkova et al., 2014). According to Huster (2005) and Efrat et al. (2017), “marketing intelligence is defined as the process of gathering information on customers, competitors, markets, and industry through data mining techniques and then is applied to strategic marketing plans (David Rajesh et al., 2015; Abu-Rumman, 2021).
1.1. Marketing Intelligence Quotient
The Marketing Intelligence Quotient measures the closeness of business organizations with their customers effectively and efficiently through their strong and intensive customer-centric approaches (Efrat et al., 2017). It ensures a better understanding of the customers so that the organizations can offer the right choices to the right customers (fig.1).
Figure 1. Marketing intelligent systems
1.2. Theoretical Background
The marketing intelligence system is based on the resource-based theory (Barney, 1991; Al Shraah et al., 2013),), which states that organizations have to develop their capabilities to exploit the resources and gain a competitive advantage for sustainable development (Kozlenkova et al., 2014).
The market-based view or market positioning states that instead of a myopic view of inherent characteristics, the organization has to utilize the opportunities in the existing market environment to achieve a competitive advantage (McGee, 2015).
1.3. Evolution of Marketing Intelligence
Three waves of marketing intelligence are identified in the retail scenario (Festervand et al., 1988). The first wave used barcode scanning technology in product placement strategies like allocation, assortment, price, display, promotion, and feature advertising and also evaluated the outcome of sales turnover and margin (Huster, 2005; Gupta, 2021a; 2022). The second wave of marketing intelligence applied technologies like loyalty points, credit, and debit cards to track their purchase history, analyze those behavioral attributes, and design promotional communications for the targets (Gedenk et al., 2006; Al Shraah et al., 2022). The third-wave marketing intelligence system uses real-time tracking technologies like portable shipping devices, GPS, RFID, video, and clickstream that identify the customer path to the site, the factors affecting that and the purchase likelihood, etc. (Pio et al., 2021; Venkateswaran et al., 2018), to understand customer behavior and design the layout and atmospherics of the store, using navigational aids, placing products adjacently, managing queues and crowds in improving service levels and conducting in-store events and the outcome of these activities can be evaluated through the store path and traffic, penetration of aisle, dwelling time to know the amount of time spent by the customers in the particular location of the store, interaction time and conversion rate (Lies, 2019; Abu-Rumman and Qawasmeh, 2021) (fig.2).
Figure 2. Marketing intelligence framework