Paper Example on Predicting Consumer Purchasing Habits Using Social Networks

Introduction

The chosen topic for this social media project is predicting consumer purchasing habits using social networks. Majority of the marketers today are using social media to predict the demand for their products based on consumer buying behavior. The conduct of market research is capable of revealing consumer plans, although going through the shroud that protects customer motivations is much better. From the initiation of big data, marketers have access to more sophisticated analytics and predictive tools to predict consumer habits. Now, marketers conduct their targeting activities, which are informed by forecasting those individuals likely to take a step and adopt a product, change on how they respond to marketing communications, and switch providers (Yahia, Al-Neama, & Kerbache, 2018). In the current era of social commerce, people connect in e-commerce websites through social networking sites like Twitter and Facebook, among others. Traditional approaches such as the mass media are not widely used in the purchase habit prediction because the majority of people have shifted to social media platforms. Therefore, there are correlations between the use of social media and consumer buying habits. This social media research project seeks to explore the manner through which marketers and businesses, in general, can predict consumer purchase behavior through social media. It is necessary to conduct this research to enable e-commerce companies, or businesses to understand what they need for their buying behavior prediction.

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Literature Review

Social Media Use

Social media is the new media through which people share information via the internet. According to the argument put forth by Lee, (2016), social media entails the platforms enhancing social interaction and communication of information which is gathered online. Erevelles, Fukawa, and Swayne (2016) stated that through social media, users use their profiles to make contributions and give feedback towards their moving subjects. There are various social media platforms, such as social networking sites, blogs, media sharing, social news, and microblogging (Hsiao, Chang, & Tang, 2016). Giampietri, Verneau, Del Giudice, Carfora, and Finco, (2018) elaborate that different social media platforms have various features and allow users' varied experiences. Therefore, the majority of social media users spend much of their time online reading the posted contents, commenting, giving feedback, and sharing certain information.

In the contemporary world, many commerce activities are conducted online. Alalwan, Rana, Dwivedi, and Algharabat, (2017) argue that many businesses have adopted the behavior of selling their products and offering services through the internet. Hence, as articulated by Tang and Cooper, (2019), e-commerce companies prefer advertising their products through social media because of the rising levels of potential customers from social media users. Besides, Jacobsen and Barnes, (2017) add that consumers and marketers have interactive profiles through social media, which they connect for the making of their product-related decisions. Through social media, Das and Mandal, (2016) argue that it is possible for marketers to advertise different products and services. Lou and Yuan, (2019) identify that consumers have access to the advertised products through social media. Nonetheless, social media enhances the connections between consumers and marketers.

Consumer Purchasing Behavior on Social Media

Social media users extract information about a product from social networks that are used or preferred by e-commerce firms. Kooti, Lerman, Aiello, Grbovic, Djuric, and Radosavljevic, (2016) postulate that users of social media look at the advertisements, like the pages and share in their profiles; therefore, spreading the information about a specific product to many people. Social media users are ford of communicating with each other concerning certain products; therefore, likely to incite each other to purchase certain products. One's previous experience regarding a particular product, as argues by Rahman, Islam, Esha, Sultana, and Chakravorty, (2018) is usually shared to friends; hence motivating them to buy the same of discouraging them not to go for a specific product. Gilani, Wang, Crowcroft, Almeida, and Farahbakhsh, (2016) argue that recommendations made from consumers encourage social media users to go for the advertised product. Culotta, Kumar, and Cutler, (2015) confirm the statement and identify that when consumers are interested in a product, they go ahead and search for it through the social media before making the final purchase decision. Simon and Tossan, (2018) identify that competitive brands market their products via social media; therefore, giving consumer alternatives. Therefore, as articulated by Roberts, (2017), consumers tend to evaluate the accessible options based on the posted information, opinions and identify the product or brand that will work out for their interests. Indeed, before buying a product, social media users analyze other people's attitudes towards the specific product and consider other situational factors to enhance their purchase intention.

Predicting Consumer Purchase Behavior through Social Media

When marketing, marketers target specific customers. Therefore, the message used to advertise a product must focus on enticing and motivating the targeted audience. Pittman and Reich, (2016)argue that for a company to predict the buying habits on social media, the firm needs to pay attention to the possibility of the target audience of making a purchase. After posting an advert, Mikalef, Giannakos, and Pappas, (2017) identify that a company can forecast the buying behavior through the likes, comments, sharing rate, feedbacks, opinions, and questions asked about the particular product. Nofer and Hinz, (2015) agree with the statement and add that marketers have to focus on understanding the consumers, their preferences, and ways of delivering consumer satisfaction. Consumers' behavior when buying products online can be realized through social media necessary information; for instance, the liked pages, opinions, and demographics. Noguti, Singh, and Waller, (2019) emphasize that a marketer can understand the behavior of customers by analyzing the responses and likes made against the particular product or company in different social media platforms. For example, a product might receive many tweets, and less likes vial Facebook. The analysis of such information, as articulated by Im and Ha, (2015) can enable marketers to predict consumers' purchasing habit. Also, the feedback acquired from the customers based on their experience with the bought product can help in the prediction of their purchasing behavior. Therefore, histories of purchased items and perceptions of social media users about media advertisements enhance efficient production of purchase behavior.

Based on the available literature, there is still a gap in how to effectively predict consumer purchasing habit on social media. Therefore, this research project seeks to answer the following research question "How can social media users' profile information be used to predict one's purchase behavior?"

Methodology

Data Sampling and Collection Method

This study will entail the collection data from Twitter as one of the social media platforms. Twitter will be used because millions of people connect through a particular network; therefore, making it possible to know how consumers behave towards a specific product on social media. Data sampling will be done through random sampling of tweets about product 'J.' The sample size for this study will be 100. The selection of the sample will be relevant in making the conclusion valid given that a product is likely to get very many tweets against it. Besides, a sample size that is greater than 30 and less than 500 is usually identified to be appropriate for most studies. Therefore, tweets of 100 twitter users will be used on the collection of the intended data. The sample will be taken irrespective of the geographic location, gender, and age. Therefore, this study will be done using 100 tweeter handles and specifically the tweets about product J.

There will be a collection of data through quantitative and qualitative methods since numerical data will be used at the same time with clear statements. The use of the quantitative approach will be necessary since it helps understand the number of social media users with positive and those with negative sentiments about the product. Besides, it will be required to follow the number of times an individual repeats the tweets about that product (Kharde, & Sonawane, 2016). On the other hand, the qualitative method will be used to help in realizing the behavior of consumers towards the product based on their opinions, comments, emotions, and interactions between different social media users. For this research, there will be an observation of the views raised by social media users towards product J.

Data Analysis Methods

Data extraction will be done through an API key. The technique is used to extract the data that corresponds to the specific product. The tool will help in getting all the intended tweets in a clear way for proper analysis (Larsen, Boonstra, Batterham, O'Dea, Paris, & Christensen, 2015). Besides, it is easily accessible when doing research using Twitter data. The extracted tweets will be downloaded for analysis purposes. The data analysis method to be used in this research project will be Microsoft Excel where tweets will be categorized into three columns, source, target, and weight.

The source column will represent the social media user making the tweet while target column will show the user who has been directed the tweet. Moreover, the weight column will indicate the number of times the author has tweeted at the target. By looking at the weight, it will be possible to recognize those social media users who interact with each other more often. Besides, the excel spreadsheet will aid in filtering the tweets, and therefore an excel sheet will be used to illustrate the conversation held between different social media users regarding product J. Using Microsoft Excel, there will be the presentation of the same data using graphs, which will be directly prepared on the excel sheet. There will also be the analysis of the tweet data in percentage for an active discussion of the findings (Culotta, Kumar, & Cutler, 2015). Furthermore, charts will be prepared to illustrate the pattern of use of interaction between different social media users and more specific the information they share about product J.

Related tweets will be coded differently with those tweets that will seem to be unique or dissimilar from others. All the tweets will be reviewed and categorized based on the number of times a particular tweet has been repeated. Since the study focuses on predicting consumer behavior on social media, there will be an analysis of the specific opinions from users through tweets. Tweets will be coded as either positive or negative. Therefore a table will be prepared to demonstrate the positive and negative views of consumers concerning product J. The analysis will be used in concluding how it is possible to predict the consumer behavior on social media. It will be possible to understand the attitudes and how they contribute to the purchasing decision-making process (Roberts, 2017). Indeed, the entire data analysis practice will be carried out to make it easy for the research to discuss the study findings and the making of a relevant conclusion.

Ethical Stance

Ethical challenges usually are encountered when researching social media because users have the right to the privacy of thei...