Big Data Marketing Innovation

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

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.

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).
Source: https://goo.gl/6ciVPo

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

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)

Characteristics of Big Data
The 4Vs of Big data
6 ICCMI 2016 | 4th International Conference on Contemporary Marketing Issues, 22-24 June
Source: http://www.ibmbigdatahub.com/infographic/four-vs-big-data

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) .

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

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.

Data – driven decisions
10
•Data Acquisition & recording
•Extraction, cleaning & Annotation
•Integration, aggregation &
representation
Data Management
•Modelling & Analysis
•Interpretation
Data Analytics
Data Driven Decision
 Processes of leveraging big
data are divided into 2
phases:
 Data Management
 Data Analysis
(Gandomi & Haider, 2014).

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.

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

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)

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).

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
(Fan et al., 2015).

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?

Thank you for your
attention!
ICCMI 2016 | 4th International Conference on Contemporary Marketing
Issues, 22-24 June 2016, Heraklion, Greece

Big Data Marketing Innovation

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (9)

Similar to Big Data Marketing Innovation

Similar to Big Data Marketing Innovation (20)

More from e-Bi Lab

More from e-Bi Lab (20)

Recently uploaded

Recently uploaded (20)

Big Data Marketing Innovation

Editor's Notes