This part focuses on exploring the in-depth information on major domains of the research topic by reviewing past researchers, books, journals, internet blogs and related articles. Mentioned theories will be the foundation for the research because major domains of research are about social media marketing and its attributions. The review of literature will revolve around these.
Hongshaung (Alice) LI and P.K. Kannan, “Attributing Conversions in a Multichannel Online Marketing Environment: An Empirical Model and a Field Experiment”, where the authors have focused on different touchpoints in attributing the conversions from for website. The authors have introduced a new methodology to attribute the incremental value of each social media marketing channel in an online environment using customers' touches. They have introduced three different stages in the hierarchy method, such as: (i) Consideration Stage, (ii) Visit Stage and (iii) Purchase Stage. Both carryover and spillover from the existing metrics are calculated in this new approach to attribute the conversions. They have used empirical analysis using the data from a franchise firm to capture all the customers' touches. They even tracked all the customers history till 68 days that contained information about their searches, whether the touches were made multiple times every-day or in particular intervals. Even-though the authors were able to model customer visits using a static framework that has a broader application beyond the business to customer context, they didn't not focus on the other attribution methods to find which one can yield the maximum results.
Vibhanshu Abhishek, Peter S. Fader, and Kartik Hosanagar, 2012, “Media Exposure through the Funnel: A Model of Multi-Stage Attribution”, where the authors have analysed how the consumers behave when they are exposed to online advertisements. They show that display advertisement carries high weightage among all the touchpoints, even though they do not have an immediate impact on the conversion. The problem of advertisements is showcased and by using HMM – Hidden Markov Model. Firstly, they have used conversion funnel method in order to find the individual consumers behaviour. It is shown that consumers decision process is driven based on various factors of touch points. It is found that only a fraction of online conversions is driven by online advertisements. So, they propose a new attribution methodology that attributes credit based on marginal effect they have on consumer's conversions. This research will be using this new attribution methodology along with other methodologies in order to find the best one.
Holly Paquette, 2013, “Social Media as Marketing Tool: A Literature Review”, the authors have reviewed the literature focusing on the importance of social media marketing to be used by a company. It is focused on mainly explanation of new terminology and foundations of social media marketing and the impact of social media on consumer behaviour. They have studied four important themes: Virtual Brand Communities, Consumers Attributes and Motives, User Generated Content and Viral Advertising. The authors have studied the four themes and stresses on how important it is to use social media marketing for a company as more than half retailers are using social media platforms like Facebook, Instagram, LinkedIn, etc. They also tell us how important is the data collected from these online platforms in order to learn the consumer behaviour. Though this paper doesn't talk about any attribution of sales connecting to the revenue, but it does focuses on consumer behaviour and how we can use the data to learn about the consumers. It is recommended for the marketers to know before carving marketing strategies to know how we can use the methodologies and this can help in attributing returns from the right methods.
Simona Vinerean, Iuliana Cetina, Luigi Dumitrescu & Mihai Tichindelean, 2013, “The Effects of Social Media Marketing on Online Consumer Behaviour”, the authors have focused on finding the users who interact with social media posts and how they interact. They have used exploratory research along with data sampling where the data was collected from Internet – FreeOnlineSurveys and used a statistical analysis tool SPSS to analyse the data. After cluster analysis, the authors have used automatic linear modelling to forecast the continuous target variable based on linear relationships between the target variable and designated predictors. The authors predicted and analysed four new types of social media consumers, such as: Engagers, Expressers, Networkers, and Watchers and Listeners. This study becomes important to learn about the consumer behaviour on social media platforms in order to strategise marketing campaigns to provide positive reactions to online advertisements. Though this paper doesn't speak about any attribution models for return of investment, it still becomes important to learn about consumer behaviour and how to use the data sampling to predict the behavioural pattern. I believe this helps in planning better marketing strategies and attributing the returns perfectly.
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