Abstract
A recent informational phenomenon has emerged as one of the considerable innovations in information systems, commonly referred to as "Big Data". The latter is currently trendy, both in academia and industry, and is used to describe a wide range of concepts, from data extraction, storage, and management, to data processing and analysis using well-known schemas, to extract patterns in hidden relationships in order to make better decisions and to derive new knowledge using analytical techniques and solutions. The technology that enables the potential of big data to be exploited is called "Big Data Analytics". Big data analytics is a major challenge that enables researchers, analysts and business users to make better decisions faster. Big Data became an important part of marketing research and marketing strategies. The e-commerce industry is one of the industries that currently benefits most from the potential of big data collection and analysis. This paper therefore aims to demonstrate the use of big data to understand customers and to improve and facilitate the decision making process. In this research, we apply multiple machine learning (ML) models on large dataset present in the e-commerce area by studying several practical cases on online markets.
Highlights
The world has become an information society that is highly dependent on data
This paper aims to answer the following questions: how to reduce large-scale problems to a scale that humans can understand and act upon? What role can big data play in digital marketing success? And how big data can help e-commerce industry to better understand customers? Based on concrete studies about online markets
Rooted in recent literature [43][44][45], we focused on the landscape of big data analysis through the lens of a marketing mix framework [43]
Summary
The world has become an information society that is highly dependent on data. Due to this technological revolution, millions of people generate huge amounts of data every day, every second due to the increased use of devices (smartphone, iot.). Before the big data era began, companies placed relatively low value on the data they collected that had no immediate value. Big Data [1] holds great potential for science and industry. It can bring about a lasting change in the way companies make decisions and in the way they conduct research in a wide range of scientific disciplines. Big Data will create scientific progress and innovations and increase the competitiveness of our science and our companies. The 3-V model distinguishes three challenges of data growth: volume, velocity and variety. Big data can be defined as: "highvolume information assets or varieties that require costefficient and innovative ways of processing information and enable better understanding, manufacturing and automation of decision-making processes”
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