Strengths and Limitations of Social Media Analytics Tools

Strengths and Limitations of Social Media Analytics Tools

Dražena Gašpar (University of Mostar, Bosnia and Herzegovina) and Mirela Mabić (University of Mostar, Bosnia and Herzegovina)
Copyright: © 2017 |Pages: 22
DOI: 10.4018/978-1-5225-2148-8.ch012
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Abstract

The aim of this chapter is to research and present strengths and limitations of social media analytics tools used in the financial sector. Emphasis is on the business point of view that sees the social media analytics as a collection of tools that transform semi-structured and unstructured social data into noteworthy business insight. There are two main aspects of social media analytics: the technology aspect which covers identifying, extracting, and analyzing social media data using sophisticated tools and techniques; and the business aspect which interprets the data findings and aligns them with business goals. Namely, it is simply not enough to have a social media analytics tool; the tool should be strategically aligned to support existing business goals. The chapter offers a framework for easier adoption and implementation of these tools in the financial sector.
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Introduction

Social media analytics is a relatively new, but fast-growing, field. The term appeared in 2009, and since then it has become a buzz word used to describe the practice of gathering data from social networks and blogs to analyze them and make business decisions. Businesses view the chance to use the vast amounts of data produced by social media users to increase brand loyalty, generate leads, drive traffic, and more. Very soon, social media analytics has become successful in finding:Which customers use social media to comment about brand or a new product launch; which posted contents on social media resonate better with customers; which social media conversations about company, product, or services are positive, negative, or neutral; who are the most influential social media followers, fans, or friends; which social media nodesare influential; which social media platforms are generating the most traffic; which keywords and terms are trending.

The early implementations of social media analytics were related to marketing and brand management. Namely, consumer and brand discussions became the basis that enabled marketers and brand managers to create value from social media analytics.

The financial sector did not stay immune to the explosive growth of social media. Whether financial institutions like it or not, their customers have discussed their reputations and brands within social networks. However, as a highly regulated industry, the financial sector was slower in the implementation of social media analytics. The first adopters of social media analytics in finance were small private hedge funds. The growth of discussion around capital markets, equities, macroeconomic indicators, and breaking news was the basis that enabled the creation of value by social analytics for financial services. Since 2013, the implementation of social media analytics in the financial sector has evolved significantly regarding structure, depth, and breadth.

The massive use of social media analytics could not be possible without different software tools that support it. The early software tools enabled companies to monitor, listen, and measure their social media efforts. Nevertheless, the market for social media analytics tools has grown rapidly. Indeed, since 2012 it had started to consolidate when large IT providers entered the market with significant acquisitions of smaller, independent companies.

Social media analytics tools are becoming a huge business and can be divided into two broad categories: comprehensive platforms and specific solutions focused on one particular feature, like social monitoring, sentiment analysis, community responsiveness, content analysis, competitive benchmarking, and similar.

The financial sector started with social media monitoring, slowly changing focus on applying advanced social media analytics to create scores, signals, and other derived data from social media. Now, the implementation of social media analytics tools in the finance sector is oriented to the integration of social data, calculation of sentiment index, and use of text analysis as a part of risk assessment. Through intelligent use of social media analytics tools, the financial institutions can ensure enormous values for themselves. Applying these tools to the social data (tweets, blogs, posts, etc.) enable financial institutions to derive customer intelligence, understand the need for specific services or products, develop adequate marketing strategies, and transform customer relationship management into social customer relationship management.

However, besides huge potential benefits offered by social media analytics, some challenges remain. One of the big issues is a lack of standards and methods for mining social data, especially non-Cashtag data. Despite all social media potential, organizations that have implemented social media analytics tools still state complexity and lack of tangible return on investment (ROI) as a big challenge. The main question is how to make effective use of collected social media data. Also, as highly regulated organizations, financial institutions have to ensure that their implementation of social media analytics is in compliance with existing regulations and guidance.

The practical implementation shows that just using of social media analytics software is not enough, that organizations have to consider individuals in the process of analysis and interpretation of collected data. Since software tools are still in the process of maturing, organizations need to understand the limitations and risk that come with investing in these tools.

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