Use of social data analytics for online marketing

By Aditya Abeysinghe

Social data

Social data is information users post on social media websites or applications and other data such as biographical and location data. For example, posts or tweets, images, videos, shares etc. are data shared in social media. These are available to other users through a social media platform or by using public APIs (Application Programming Interfaces). Data can also be made available to internal business users in the form of private APIs. These data are used for analysis which can then be used for business promotions, enforcing security, and improving business functions within social media organizations.

Social data analysis

Social data analysis includes analyzing data within social media platforms. It includes gathering data using an API(s) or a publicly dataset(s) and then cleaning, transforming and analyzing the data. Social media data can be real-time or past data based on how users post data. Some analyses may focus on real-time analysis on real-time data but mostly analysis is on past data. The method used for the analysis may also differ on factors such as user reach or relevance of data in which it is used. Analysis usually focuses on how entities are connected to other entities, topics mostly shared within a time range etc. 

Business uses of social data analysis

Social data analysis is used to identify how often users post or share data, connections between data and people, and what types of data are shared. Social data is easily obtainable due to public social media APIs which provide data based on user request. Due to the availability of querying before request in these APIs users can easily filter data with less cost and effort. Online businesses can enhance their marketing and the quality of their products and services using social data, without the need for data collection based on their targeted customer markets.

Social data contains data of varied types and value. During analysis, data can be filtered based on these types to make business insights more useful. A dataset of posts shared by users may include data relevant to several tags, locations, time, and media of different types. Businesses could use such a dataset to filter data based on the location then based on content to improve knowledge gained and make insights more in line with their marketing. This way business analysis is more focused towards their current targeted market as well as it can focus on new target markets. 

Limitations of social data for analysis

Data contained in social media is sometimes imperfect for analysis. An issue of using social data is that social data are not posted to be used for analysis. These data are posted by general users based on their own opinions and thoughts. Therefore, social data might not contain data they hide or do not provide access to be viewed with whom these users are not connected. Data may be also posted using fake or bot profile accounts which might cause inaccuracy in data. 

Another issue of using social data is the extremity of meaning in sentiments in social data. Some social data may contain highly positive or negative meaning which can cause algorithms used for analysis to be biased. Sentiment-based data analysis based on extreme data could make algorithms to be less accurate in their classifications which may cause inaccurate predictions. Businesses infrequently find importance on such biased data as these do not represent accurate customer opinions. 

Image Courtesy: https://towardsdatascience.com/