Regression Analysis On Organic Social Media Marketing And Return On Marketing Investment (Case Study: Gagasmedia Book Publisher)

Giovanni, Joshua and Purnama, James and Anthony, Randy (2017) Regression Analysis On Organic Social Media Marketing And Return On Marketing Investment (Case Study: Gagasmedia Book Publisher). Bachelor thesis, Swiss German University.

[img]
Preview
Text
Joshua Giovanni 11302008 TOC.pdf

Download (289kB) | Preview
[img] Text
Joshua Giovanni 11302008 1.pdf
Restricted to Registered users only

Download (191kB)
[img] Text
Joshua Giovanni 11302008 2.pdf
Restricted to Registered users only

Download (1MB)
[img] Text
Joshua Giovanni 11302008 3.pdf
Restricted to Registered users only

Download (318kB)
[img] Text
Joshua Giovanni 11302008 4.pdf
Restricted to Registered users only

Download (1MB)
[img] Text
Joshua Giovanni 11302008 5.pdf
Restricted to Registered users only

Download (195kB)
[img]
Preview
Text
Joshua Giovanni 11302008 Ref.pdf

Download (221kB) | Preview

Abstract

Social media marketing is a way to utilize social media by the company to post or promote their product and service in the social media. Social media can be categorized into organic and paid; either of the categories will help the company to increase their brand awareness via social media to their current potential customer. Regression analysis, in more specific Multi-linear Regression, will be used to find if they are any relation between the variable in the social media marketing with the return on marketing investment (ROMI). In this thesis, the research will use regression to provide an analysis whether there is any relation between Organic social media marketing with ROMI.

Item Type: Thesis (Bachelor)
Uncontrolled Keywords: Social Media Marketing; Organic Marketing; Paid Marketing; Return on Marketing Investment
Subjects: Q Science > QA Mathematics > QA76 Computer software >
Divisions: Faculty of Engineering and Information Technology > Department of Information Technology
Depositing User: Astuti Kusumaningrum
Date Deposited: 11 May 2020 06:37
Last Modified: 11 May 2020 06:37
URI: http://repository.sgu.ac.id/id/eprint/265

Actions (login required)

View Item View Item