Enriching User Experience by Transforming Consumer Data Into Deeper Insights

Enriching User Experience by Transforming Consumer Data Into Deeper Insights

Devesh Bathla (Chitkara Business School, Chitkara University, India), Shraddha Awasthi (Chitkara Business School, Chitkara University, India) and Kuber Singh (University of Waterloo, Canada)
DOI: 10.4018/978-1-7998-7231-3.ch001
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Abstract

In every field, during a particular era, there is someone who stands up to a cause. There is a “North Star” in the sky to guide the “navigator” who might erringly go astray to reach the destination. The star gives direction through sheer stability. Consumer analytics as such is widely accepted throughout the world. It especially has a firm footing in enriching user experience thanks to the gigantic data collection exercise. The popularity seems to have stemmed from the fact that analytics is the real “navigator” based on data facts and the panacea for the business problems and leads the way forward whenever required. Customer journey analytics is a key instrument in the profitability framework. It also aims to provide a view of customers that is essentially dynamic in nature and other key data points observed during the life cycle of a customer. It further covers ahead of the prevailing product ownership and user data for inculcating the information such as digital channel interactions, social media, voice-of-the-consumer interactions, sentiment analysis, and more.
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Introduction

Huge set of information are these days gathered and stored by organisations, with the desire for being valuable later on. This represents the test of overseeing such heaps of information and separating from it fitting information for supporting choices. Huge Data is right now internationally spread and broadly acknowledged, speaking to likewise an equivalent word of vanguard as far as data the executives, in spite of the fact that this doesn't come without contention (Fan and Bifet, 2013). Actually, as Chen, Chiang, and Story (2012) contended, specialists need to step forward “from Big Data to Big Impact” for adequately profiting by the focal points gave by Big Data. The help of dynamic is a key issue for advertisers, by giving bits of knowledge to help with responding to basic inquiries, for example, the best fit item pertaining to a specific market; ways to publicize such item in corresponding showcase; via which correspondence channels; with given focuses in time and for the decided cost; and bolstered by which sort of limited time and promotional activity. Given these premises, it is with nothing unexpected that Marketing has proven from the beginning an area for tries of different things with Big Data draws near (Bendle and Wang, 2016). Ongoing wellsprings of heaps of information incorporate internet based life and portable applications: both have demonstrated to majorly affect clients' choices, straightforwardly influencing brand building (Moro, Rita, and Vala, 2016).

This paper draws a research review of literature analysing the Big Data in Marketing confined in second decade of this ongoing century. Considering Big Data itself possibly holds esteem on the off chance that it is bridled targeting removing adroit information, examination has developed as a vital pattern to answer the difficulties of Big Data in Marketing. Actually, promoting examination arrangements are presently being spread all through associations trying to profit by Big Data arrangements (Laurent, 2013), albeit most executions are not yet accomplished to adequately exploit from such coordinated Marketing-Big Data arrangements (Chen et al., 2012). As the analytics likewise apply to miniscule volumes, developing difficulties in regards to huge volumes have as of late risen, for example, coordinating a wide number of unmistakable sources, managing both organized and unstructured information, and execution issues. Along these lines, examination have additionally been incorporated inside this investigation. All things considered, it ought to be featured that the primary focal point of study is to see how Big Data is being overseen and handled to use Marketing difficulties. Along these lines, by dissecting research led in this area, the current investigation gives a general image of the momentum best in class, adding to a superior comprehension of this subject. With the point of covering a huge range of the writing, a semi-robotized content mining approach utilizing theme displaying was embraced. The points found give the required research bits of knowledge on Big Data in Marketing that helps to enrich the user experience by leveraging the available insights.

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