ICCMI 2016: “Big Data in Data-driven innovation: Applications, Prospects and Limitations in Marketing”
Members of the Laboratory e-Bi Lab participated in writing the research paper “Big Data in Data-driven innovation: Applications, Prospects and Limitations in Marketing”, which was presented at the 4th International Conference on Contemporary Marketing Issues -ICCMI 2016, which was held in Heraklion Crete on 22-24 June 2016.
The real power of enterprises is related to their innovativeness, translated to their capacity accessing data and creating valuable knowledge. ―Data-Driven Innovation‖ (DDI), techniques and technologies for processing and analysing ―big data‖, is defined as the method to innovate using data-based decision process. Big data characterized by 3Vs: volume, variety and velocity seems to be a major resource for enterprises in the competitive race against rivals, since data provides significant knowledge about processes, customers, human capital and technology to enterprises. Data-driven innovation has the capacity to introduce new improved products and services, new improved production processes, better organizational management, more efficient R&D, better supply chain management and more efficient marketing.
Big data and its applications in business intelligence can contribute to business added value. In marketing intelligence, leveraging data for marketing decision making has the ability to improve sales and marketing performance by reducing inefficient marketing expenditures and increasing consumer surplus with customised marketing. Recent evidence shows that 5Ps (People, Product, Promotion, Price and Place) marketing mix can be used in Big Data management for marketing intelligence (Fan, 2015). Therefore, leveraging big data can create the prerequisites for marketing innovation, which is the implementation of a new marketing method involving significant changes in product design or packaging, product placement, product promotion or pricing (OECD, 2005). There is evidence that data-driven decision making have a positive impact in enterprises‘ performance (Brynjolfsson, 2011; Davenport & Harris, 2007; Lavalle, 2010; Bakhshi et al., 2014), but limited research exists in the impact big data in marketing innovation. The scope of this study is to present evidence about the impact of big data in marketing innovation of enterprises, sources of data-driven innovation in marketing and limitations of that approach.
Keywords: big data, data-driven, innovation, marketing, marketing intelligence.
Authors: Ioannis Kopanakis, Konstantinos Vassakis & George Mastorakis