Coventry University Can big data help to improvesales & profits of consumer products? BSc(Hons) Computing (FullTime) Author: Chan Ka Wai Academic Year:2017/2018Student ID: 177102394SID: 82939651Modules: A300CAW Abstract The purpose of this study isto explore is to explore the impact of big data for sales and profits ofconsumer products and to answer the following The literature reviewexamined both the concept of the operating of big data, also the relationshipbetween the big data and improve the sales and profits, as well as big data howcan help to improve sales & profits of consumer products.
This study is secondary research from the literature and academicarticles. For these research to show the big data boost up the sales andprofits of consumer products. And discuss the opportunities and benefits of bigdata to improve the consumer products. This research confirmed the big data can boost up the salesand profits of consumer products. Using the big data to analytics thecustomer’s need, aim to meet the market demand. 1. 1. IntroductionBig data mean major includes a large of information, this sizesbeyond the human and ordinary software tools to handle and process data withina tolerable elapsed time.
According to the big data, how can improve sales of consumer products? Due to Big data always to update the informationand moving target. For the big data, how to impact the marketing activitiesfrom the physical, human, and organizational capital. First, the process ofcollecting and storing of consumer activity as Big Data. Also, the process ofextracting consumer insight, and the process of utilizing consumer insight toenhance dynamic/adaptive capabilities.
The goal of this report is to discuss big data how canimpact sales and profits of consumer products. The report includes theliterature and academic articles about the definition of big data. This report also compares tradition sales method todetermine the big data importance. the conclusion of opportunities and benefitsof big data to consumer products.
and recommendations how to use efficientlybig data bring the advantage. 2. Review of Literature About the review ofliterature of big data. most of the literature confirms the importance of bigdata. The purpose of this section is to provid the definition of big data.Moreover, the evidence of the big data how can improve the sales and profit ofconsumer products. 2.1 The definition of big dataAbout the definition,the explanation of Andrea De Mauro said that Big data is a concept and it hasuncertain origins.
(Andrea De Mauro,2015) However, much conceptual vaguenessstill shrouds its meaning. This term is described the concept is approved,identifying emerging trends and suggesting opportunities for future developmentand provide a consensual definition by mixing common themes of now existingworks and patterns in previous definitions. Another the definitionsof the explanation are from Amir Gandomi. Big data require specific technologyand analytical methods to transform into value. (Amir Gandomi,2015). Big data potential valueis only when leveraged to drive decision making. The organizations need moreefficient to process high volumes of fast-moving and diverse data intomeaningful insights. (Amir Gandomi,2014).
Big data can be broken down into fivestages for the overall process of extracting insights. The two majorsub-processes of these five stages are data management and analytics. For thedata management, it involves processes and supporting technologies to receive,also store data to intend and retrieve it for analysis. On the other hand,Analytics refers to techniques used to analyze and receive information from bigdata. So, Big data analytics can be thought as a sub-process in the overallprocess of insight extraction from big data.A summary of definitionof big data is specified in Figure 1 below Figure 1: Big DataProcess (Gandomi and Haider, 2015)2.2 Current of using Big data improve consumerproducts for sales and profits In this moment, Big datais getting more popular.
as the result, big data analytic the marketing needs,and targeted products and service can then be offered through personalizedmessages specific to each stage of the consumer cycle such as awareness,engagement, consideration, conversion, and loyalty. For example, some peopleoptions in to receive marketing messages from a retailer who has an outlet inthe local message. GPS tracking detects that the customer is near the store,and sends the message to the customer alerting them have a special discount.
Theoffer is driven by what the retailer already knows about this customer, basedon personalized messages. Aim to the customer’s interest, customer into thestore and purchases using the coupon code in the text message. In this case, itcan improve the opportunity for consumer products for sales and profits. (MichaelAbramow,2014) Big data can get thereal-time insights on product demand. The retailers can visit data on productdemand levels on a minute-to-minute basis across their stores. In this moment,the retailers can real-time adjustment (Barbara Thau,2016).
Big data also canget the information for customer’s store loyalty details and the credit cardpurchases. this information can be used to foresee customer’s needs ahead oftime. For example, the grocers can use big data to analytics to determine howoften customers buy milk, condiments, or different products, and then send eachdifferent coupon based on their specific purchasing habits.
(Barbara Thau,2016) At the market competitiveness of manufacturing,integrating data from research and development, engineering, and manufacturingunits to enable concurrent engineering can significantly save time to market andraise quality. For the Sales revenues and profitability,McKinsey said that the retailers using big data analytics can improve theoperating margins by more than 60%. Figure2. Big DataAnalytics Industry Value.(Michael Abramow,2014)3. DiscussionThe 4. Outline Plan Steps Analysis 1.
Circle the directive verbs, if there are any. Think about what they are asking you to do. 2. Underline the main content words.
Think about what they mean. 3. Think about what kind of information you will need to participate in the discussion in order to support your point of view. 4. Make the points into headings for your note-taking 5. Think about what kinds of text would have the information you are looking for.
In this paper, the definitions of big data.