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Big Data in Data-driven innovation: applications, prospects and limitations In marketing

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Ioannis Kopanakis, Konstantinos Vassakis & George Mastorakis. "Big Data in Data-driven innovation: Applications, Prospects and Limitations in Marketing".
Presentation at 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece.

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Big Data in Data-driven innovation: applications, prospects and limitations In marketing

  1. 1. ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece Big Data in Data-driven innovation: applications,prospectsand limitationsIn marketing Ioannis Kopanakis Konstantinos Vassakis George Mastorakis Department of Business Administration Technological Educational Institute of Crete Agios Nikolaos, Crete, Greece
  2. 2. Introduction Knowledge- Innovation - Performance ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece 2  In modern economies, characterized as “knowledge-based”, the changing customer needs, technological evolutions and the competitive market pressure have made innovation a vital determinant of enterprises’ success (Daud, 2012).  Hence, enterprises have to adopt strategies innovation- oriented in order to build and sustain competitive advantage in the globalized and technology changing environment they operate.  Innovation is dependent on the combination of technologies and exploitation of knowledge.
  3. 3. Data to knowledge 3  The capacity of enterprises to access information and create valuable knowledge provides them competitive advantage in the innovation race against rivals (Sarvan et al., 2011).  In the era of Industry 4.0 (4th industrial revolution), Data has major impact on businesses, since the revolution of networks, platforms, people and digital technology changed the determinants of firms’ innovation and competitiveness (OECD, 2015). ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece Source: https://goo.gl/6ciVPo
  4. 4. Data – Driven Innovation (DDI) Knowledge to Innovation 4  “Data-Driven Innovation” (DDI) -> techniques and technologies for processing and analysing “big data” as the method to innovate using data-based decision process.  DDI’s economic value expecting to be enormous in the following years and it has the capacity to introduce:  new improved products & services,  new improved production processes  better organizational management  more efficient R&D  better supply chain management  more efficient marketing ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  5. 5. Big Data 5  Large streams of data generated through information and communication technologies (ICT) and Internet of Things (IoT) named “Big data” -> datasets with large volume that cannot be captured, stored, managed and analysed by typical database software tools (Manyika et al., 2011)  BD is a major resource for enterprises to obtain new knowledge, present added value, foster new products, processes and markets. Hence, the ability to manage, analyse and act on data is significant to enterprises  An asset for enterprises’ indicating the significance of data- driven approach within enterprises (Microsoft, 2016) ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  6. 6. Characteristics of Big Data The 4Vs of Big data 6 ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece Source: http://www.ibmbigdatahub.com/infographic/four-vs-big-data
  7. 7. Significance of Big Data 7  The increased use of digital services and Internet has transformed all the sectors in the economy. Through DDI, almost all the sectors including retail, manufacturing and agriculture has become more service-centred, adopting the term “servicification” (Lodefalk, 2013)  The exploitation of big data provides enterprises in several industry sectors, not only ICT firms (Tambe, 2014) -> added value through the improvement in resources (physical & human) supervision and allocation, reduction of waste, greater transparency and facilitation of new insights.  Εconomic benefits of big data in UK private and public sector businesses: increase from £25.1 billion in 2011 to £216 billion in 2017, while data-driven innovation will lead to £24,1 billion contribution to UK economy during 2012-2017 (Cebr, 2012) . ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  8. 8. Contribution-limitations 8  Big data, similar to IT, has the ability to bring significant cost reductions, delivery time, enhanced R&D and new/improved products or services.  However, little evidence exists on ROI for big data applications in enterprises, showing promising issues (Davenport & Dyché, 2013)  Empirical evidence related to the impact of data-driven approach and its impact to enterprises performance are scarce and limited mainly in research for large-multinational companies  In addition, no research exists in the impact of big data-driven approach in marketing innovation ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  9. 9. Significance of study 9  It is observed growing attention to big data and data-driven approach from academics and professionals, since the analysis of “big data” leads on valuable knowledge, promotion of innovative activity transforming economy of countries (OECD, 2015).  There is evidence that data-driven approach has a positive impact in enterprises’ performance (Brynjolfsson, 2011; Davenport & Harris, 2007; Lavalle, 2010; Bakhshi et al., 2014).  The scope of this study is to provide a theoretical framework examining the impact of big data exploitation to enterprises marketing innovation performance. ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  10. 10. Data – driven decisions 10 •Data Acquisition & recording •Extraction, cleaning & Annotation •Integration, aggregation & representation Data Management •Modelling & Analysis •Interpretation Data Analytics Data Driven Decision ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece  Processes of leveraging big data are divided into 2 phases:  Data Management  Data Analysis (Gandomi & Haider, 2014).
  11. 11. Data-driven performance Impact in enterprises’ performance 11  Brynjolfsson et al. (2011) examine how adoption of data-driven decision making induces firm performance using a dataset of 179 large publicly traded firms and concluded that adoption of data-driven decision making approach provide 5-6% higher performance (in terms of productivity) to firms. In addition, these firms present better performance in asset utilisation, return on equity and market value.  McAfee & Brynjolfsson (2012) examined the performance of data-driven companies and whether big data intelligently improves business performance. Conducting interviews with 330 executives of North American companies and combining them with companies’ financial performance, found that top performers in the use of data-driven decision making have 5% higher production and 6% higher profitability than their rivals.  Bakhshi & Mateos-Garcia (2012) in their empirical study for 500 UK businesses from various industries operating on-line. Data sample divided into 2 categories: data- driven decision making enterprises and experience-driven enterprises. They found that data-driven companies present higher level of innovativeness launching new products and services and making disruptive changes to their business processes. ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  12. 12. Applications of Big Data in Marketing 12  Using online tools to provide trending topics i.e. Google trends  Monitoring trends to make Informed Decisions on Marketing Strategy  Maximize ROI via Budget management  Defining Ideal Customer Profile -> personalized marketing to optimize customer engagement  Target Audience at the Right Time  Efficient content marketing attracting customers  Market & competitors analysis  Predictive Analysis ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  13. 13. DDI in Marketing 13  “Data-Driven Marketing Creates Consumer-Driven Companies: what customers want and need and engineering the company to provide it. The more firms can use data to develop a 360 degree, multi-channel view of what customers think and want, the more the customer will truly be king” (Deighton and Johnson, 2013) .  'Organizations that are ‘leaders’ in data-driven marketing report far higher levels of customer engagement and market growth than their ‘laggard’ counterparts. In fact, leaders are three times more likely than laggards to say they have achieved competitive advantage in customer engagement/loyalty (74% vs. 24%) and almost three times more likely to have increased revenues (55% vs. 20%).‘(Forbes, 2015) ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  14. 14. Big data & Marketing Intelligence 14  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.  Therefore, leveraging big data can create the prerequisites for marketing innovation -> the implementation of a new marketing method involving significant changes in product design or packaging, product placement, product promotion or pricing (OECD, 2005).  Recent evidence shows that 5Ps (People, Product, Promotion, Price and Place) marketing mix (Goi, 2009) can be used in Big Data management for marketing intelligence (Fan, 2015). ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  15. 15. Big Data & 5Ps Marketing mix Developing insights from data for marketing decision-making 15 ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece (Fan et al., 2015).
  16. 16. Conclusions – further research 16  In the data-driven era, transformed by the rapidly large streams of data generated through ICT and IoT, knowledge originates from big data processes provides the decision makers the capability to innovate and increase their performance gaining a competitive advantage against rivals.  The insights by leveraging big data in marketing prospects provide a competitive advantage in enterprise through new ways of growth and consumer surplus  What happened with SMEs? What are the obstacles facing in adopting data-driven approach in marketing? What happened with the ROI in data-driven marketing processes? Is marketing innovation a result of data-driven approach? ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  17. 17. Thank you for your attention! ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece

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