More and more companies are starting to understand the significance of the social media in their work channels. Online social media marketing has many implications for consumers because the product and the feedback is more visible than even. In addition, different sets of stakeholders would also be able to view this data as well. Therefore, consumers, channel partners, competitors, suppliers and more would be able to view the market opinions of the product under consideration. The myriad complexities and characteristics of the social media hence evokes a new set of rules and strategies with respect to marketing and more and more companies became aware of the need to reinvent their marketing. Social media is used to promote and disseminate information and the use of electronic word of mouth makes it complex.
Ludwig et al. (2012) find that the semantic content and style properties of verbatim online reviews influence online retail sites’ conversion rates. The authors employ text mining to extract changes in affective content and linguistic style properties of book reviews on Amazon.com. They find that the influence of positive affective content on conversion rates is asymmetrical, such that greater increases in positive affective content in customer reviews have a smaller effect on subsequent increases in conversion rate. No such tapering-off effect occurs for changes in negative affective content in reviews. Furthermore, positive changes in affective cues and increasing congruence with the product interest group’s typical linguistic style directly and contingently increase conversion rates.
Proper formal collection of feedbacks is hence necessary. Social media marketing structures hence have to be reinvented by the day. The characteristics of online social environment are changing by the day because of the redefinition of technology. Newer technology breeds more ways of using social media and hence more work from the end of traditional marketers. Key findings indicate that online reviews and ratings affect many different metrics, both online and offline, such as consumer ratings, consumer purchase conversion rates, brand evaluations, purchase intentions, firm performance, and firm value. The effects of online reviews and ratings on performance metrics are contingent on other characteristics, including their own, brand, consumer, and firm characteristics.
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