Digital Media Marketing using Trend Analysis On Social Media

Abstract : Social Media has quickly gained prominence as it provides people with the opportunity to communicate and share posts and topics. Tremendous value lies in automated analysing and reasoning about such data in order to derive meaningful insights, which carries potential opportunities for businesses, users, and consumers. Many events in the world are accompanied by the Hash-Tag trends on social media. The whole idea behind this is to create such an application that would help in marketing of products and services over social media platforms. The technique is known as Social Media Marketing and is a sub-set of Digital Media Marketing. As of now there is no personalize engagement between marketers and clients. We aim to provide such data by Personal Engagement by providing a deep insight into the user's’ content and thus would generate quality data resulting in better customer base, high conversion and lower bounce rates.

 EXISTING SYSTEM :

 The concept of Digital Media Marketing has become very popular in the recent times mainly because of the increasing use of social media by more and more people day by day. With the growing usage of social media platforms, the digital media marketing importance has increased over the time. Hence, there are a number of marketing tools that helps the marketing agencies to target users and sell their products and services. There exists a number of applications that provides analysis of the social media usage. A good example of such a system is Google Analytics, Facebook Insight and Audience Insights by Twitter. Google Analytics tracks down the activities of a website where as Facebook or Twitter Analytic Tool use social science and computer science together to show the valuable insights gathered from stakeholders and use the same for business development decisions. The available online platforms such as Google Trends provides a complete generalized analysis for the data of the social media platforms available. It shows how often a particular search-term is entered relative to the total search-volume across various regions of the world, and in various languages. The horizontal axis of the main graph represents time (starting from 2004), and the vertical is how often a term is searched for relative to the total number of searches, globally but it doesn’t provide how well a potential or existing customer has interacted with it.

 DISADVANTAGE :

 It shows how often a particular search-term is entered relative to the total search-volume across various regions of the world, and in various languages. The horizontal axis of the main graph represents time (starting from 2004), and the vertical is how often a term is searched for relative to the total number of searches, globally but it doesn’t provide how well a potential or existing customer has interacted with it.

 PROPOSED SYSTEM :

 The proposed system aims at utilizing the data collected from the three of the most popular social media platforms that are Facebook, Twitter and Instagram[5]. The users would be classified into different categories based on the preferences. The sufficient data for classification is obtained from the APIs from all the three platforms. The data from all the three platforms is integrated and combined for a specific user.

 ADVANTAGE :

 The Proposed System also provides a unique historical view of the data acquired and gathered from various social media platforms. This would be ensured by storing the classified user information in the database. This would also reduce the number of API calls that are made to fetch the data. Thus, a vast majority of users can be obtained for targeted marketing. The presence of multiple social media platforms ensures the abundance of data. This would provide a greater number of users as compared to an application that uses just one social media platform.