
Data Analytics in Marketing, Entrepreneurship, and Innovation
CRC Press
1st Edition
Published on 13. January 2021
Book
Hardback
182 pages
978-0-367-18483-4 (ISBN)
Description
Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences. Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics. It features case studies that provide realistic examples of applications. This multifaceted examination of data analytics looks at:
Business analytics
Applying predictive analytics
Using discrete choice analysis for decision-making
Marketing and customer analytics
Developing new products
Technopreneurship
Disruptive versus incremental innovation
The book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing. Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery. Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques. Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.
Business analytics
Applying predictive analytics
Using discrete choice analysis for decision-making
Marketing and customer analytics
Developing new products
Technopreneurship
Disruptive versus incremental innovation
The book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing. Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery. Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques. Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Academic
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 15 mm
Weight
461 gr
ISBN-13
978-0-367-18483-4 (9780367184834)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Mounir Kehal | Shahira El Alfy
Data Analytics in Marketing, Entrepreneurship, and Innovation
Book
09/2023
1st Edition
CRC Press
€77.80
Shipment within 15-20 days

Mounir Kehal | Shahira El Alfy
Data Analytics in Marketing, Entrepreneurship, and Innovation
E-Book
01/2021
1st Edition
Auerbach
€72.49
Available for download

Mounir Kehal | Shahira El Alfy
Data Analytics in Marketing, Entrepreneurship, and Innovation
E-Book
01/2021
1st Edition
Auerbach
€72.49
Available for download
Persons
Mounir Kehal teaches and researches business analytics at the Higher Colleges of Technology, Dubai. Prior to which he was associate professor of management information systens and dean at the College of Business Administration, American University in the Emirates, Dubai.
Shahira El Alfy, DBA, PHD Ed, FHEA, ECBA is an Assistant Professor at the Higher Colleges of Technology, Dubai.
Shahira El Alfy, DBA, PHD Ed, FHEA, ECBA is an Assistant Professor at the Higher Colleges of Technology, Dubai.
Content
1 Business Analytics: Through SIoT and SIoV. 2 Innovation Analytics. 3 Business Predictive Analytics: Tools and Technologies. 4 Hospitality Analytics: Use of Discrete Choice Analysis for Decision Support. 5 Data Analytics in Marketing and Customer Analytics. 6 Marketing Analytics. 7 Big Data Analytics. 8 New Product Development and Entrepreneurship Analytics. 9 Predictive Learning Analytics in Higher Education.