Write an essay on Social Media Analytics.
Social Media Analytics (SMA) is an exercise to collect data from social media websites and other portals where personal data about people is stored using that for taking professional decisions. The customer data helps an organization to know about their customer’s choices and expectations which in turn assist the management in designing strategies accordingly to match them and use them in marketing and other customer support activities. This process is also called as Social Media Listening. This process develops various tools to accumulate, observe, recapitulate, and visualize social media information. SMA uses different types of advanced techniques to collect information from social media sites and to check about their patterns (Atwong, 2015).
SMA lends a hand in creating value to businesses, perks up their reputation in the market, adds on to profitability and improves their competitiveness in the market. Thus, it is used by many organizations these days to enable perceptive decisions. As people are becoming more active on social media nowadays and the popularity grows, it has become important for organizations to monitor social media data and use that for organization’s progress. In this report, we will design a theoretical framework that demonstrates how a financial institution can create value for its business with Social Media Analytics (Atwong, 2015). The organization that we have chosen for this case study is DBS Bank.
DBS Bank is a well-known financial services group. The headquarters of DBS Bank is located in Singapore. It has more than 250 branches all over Asia. To progress in highly competitive environment, this financial institute had to introduce some new and improved strategy to gain maximum customers and provide best financial services. DBS was positioned as Asia’s third-largest bank by market share in 2014. When Mr. Piyush Gupta was appointed as Chief Executive Officer (CEO) at DBS Bank, he judged that the bank may be grown further by providing various internet services to Asian people who are becoming tech-savvy these days. DBS invested almost S$600 million into technology, introducing internet banking, and commencing mobile banking platform. This technology service was strengthened to support customers across Asia and to meet requirements of changing Asian customers (Chadwick, 2015). In this report, we will study how the application of Social Media Analytics by DBS Bank proved beneficial for it and we will apply different theories to prove how it created value for business.
Social Media Analytics has changed the system that maximum of organizations used to provide services to their customers a decade ago. But as the time changed, people started using modern technology, smart phones, internet connections, etc. that made them active on social media. And ultimately it inspired businesses to use social media as data collection and to gain access to more people. SMA influenced the decision-making of management (Chadwick, 2015). Under this analysis, one can use social media platforms to understand the value of trends and brands mentioned by customers. Various campaigns can be launched online to target new markets, mark new customers, change people’s perception about a brand or provide timely customer complaints resolution. It also assists management in understanding the key influences and customer insights.
Earlier, few public relation companies used to evaluate online data available on social media sites to identify customers needs, understand trends and manage customers but with the booming social media sites, it becomes difficult to keep a track on individual accounts (Chadwick, 2015). Then Social Media Analysis was introduced to trail current trends. As per data available, 91% of adults who remain online use social media sites.
Social Media Analytics process has three notions:
Under Capture stage, data is collected from various social sites like facebook, twitter, youtube, Instagram, and hashtag etc. by listening to and monitoring data (He & Xu, 2016). This data is collected by companies themselves or by involving any third-party. Data modelling, record linking and extracting is done to provide it further to analyse or understand stage.
After that, required data is extracted and irrelevant data is discarded. Customers’ sentiments, interests, and trends are studied from this extracted data under the second stage of Analysing. The meaning of the data collected is analysed and clean data is extracted after removing the useless noise (He & Xu, 2016). This stage provides a clear picture about a customers’ views about a particular product. This stage is the base of the entire process.
Later, the data is presented in most valuable form under the present stage in an easy to understand format. Interface designs like visual dashboard are introduced to express and present needful information. Data Analysts help here to extract meaning, collection and use of the data (Jensen, 2015).
All the stages work hand in hand and support each other in re-collecting and analysing data.
There are a number of business uses can be summoned due to the application of Social Media Analytics. We can explain the same by adopting lifecycle analysis framework. This framework describes the life of a product or service starting from its designing till its disposal that includes all the support activities.
This cycle has four different stages:
Design development
Production
Utilization
Disposal
To strengthen the bond with online customers and to reinforce the T & O department, there was a new banking system, Finacle was introduced. This common operating system made the banking process easy among all the branches of DBS bank (Jensen, 2015). The maintenance of account ledger, capital reporting, trade, internet banking, and customer management became easy and standardised.
Other than this, a new wealth management system was applied to the facilities of private banking. It attracted all the customer markets from medium class to high-end customers. It resulted in better customer experience that encouraged people to contact bank not only for retail transactions but also for other financial services (Jensen, 2015). They started using the bank for their growing asset management. Due to this, the wealth management income of DBS bank augmented from S$506 million to S$1.1 billion within a period of four years from 2010 till 2014.
The Internet and mobile banking platforms for business were also launched in 2012 that offered facilities to businessmen to manage their cash and trade transactions. DBS started a Customer Experience Council to check the Asian Service agenda. This step resulted in gaining more customer focus and enabled digital experience.
Other than this, DBS started keeping a check on points that forced maximum of its customers to contact their call centres. The results mentioned that huge numbers of customers contact them just to check their remaining balance, online amount transfers, and various other reasons like bill payments, etc. Another use of SMA that the bank took was introducing the ATMs. The use of the machine by customers also accumulated data about the pattern of using the machine, the reason behind its use and the time when it is being used maximum. It helped management to decide about the additional facilities to be provided within ATMs and the best time to reload a machine.
The customer relationship was benefited with the use of social media and data collected from other mediums. The frequent investments in the technology help DBS bank a lot by giving monetary benefits, profitability, and customer satisfaction.
Investments in social media analytics can lead to value add to the business and the competitiveness. The three main concepts of Social Media Analytics Value Framework are given below:
Social media is an important aspect of marketing. There are a number of awareness benefits that DBS gained through application of SMA. A number of communication channels open if we consider social media as a means of marketing campaigns. It creates a platform for customers to interact with each other and share their views. Bank got a better level of customer satisfaction, improved engagement of customers into the business and better understanding of the sentiments and views of customers. It helps an organization to understand the impact of marketing campaigns that they have launched. Whenever DBS bank starts any new campaign, it is important for them to understand whether it is providing any benefits to its customers or not (Perrotta & Williamson, 2016). Monitoring the data regularly and then analysing the collected data with the help of economists and analyses may provide a clear message to decision makers about further steps. The marketing campaigns can be then amended or altered as per study of impacts. Three main reasons why awareness motivation is considered: better understanding of customers’ values, checking result of online marketing campaigns, and to decide about new ideas for brand reputation.
Third party vendors can be introduced to source, store and analyse data. As DBS Bank reformed the strategies based on sentiments and trends that had been captured from social media sites. With the help of sentiment analysis, the new customer base was formed (Perrotta & Williamson, 2016). This was considered as a measure to check the success of campaigns. It also helped in identifying new opportunities through the customers and banking staff. SMA helps in understanding customer’s behaviours and the impact of online marketing campaigns. After understanding the customers’ behaviours, the bank can easily design new strategies to develop and outsource the IT department. It also leads to brand awareness and other awareness benefits. A combination of hardware, software and networks create the base of all IT services. Social Media Analytics helps to develop improved business performance. IT assets help in analyzing technologies for a database that is unstructured and thus assist in integrating the system. If the SMA resources and assets are used, major organizational practices: customer, process and performance management can be practiced easily and effectively.
The customer benefits, financial benefits, and organizations benefits are all that have been grown through it. Various methods were used by the bank to check about the impact of a marketing campaign on the society. The major success was the increase in a number of new customers. Maximum of these new customers joined the bank after looking at the marketing campaigns on the online social media sites (Philip Chen, Tao, & You, 2016). Customer satisfaction level was also increasing as the complaints were sorted out fast by looking at online sites and also, it helped the bank to come in contact with customers easily and readily. Financial benefits included reduced costs and increased profitability. Organizational benefits include less time taken in expanding the markets, improvement in services and success of marketing campaigns.
DBS Bank and Singapore Management University (SMU) have joined hands to operate a laboratory that will help the management analysing fresh trends and patterns followed by customers which in result will help the bank to understand about the requirement of new measures to be taken. It will help the bank analyse customer data based on new digital innovations. This will increase the understanding of the requirement of new products and offers (Philip Chen, Tao, & You, 2016). The lab will be using special software to showcase different activities on social media sites which are frequently accessed by customers. The management has taken this step to make a record of customers complaints that they prefer to mention on social sites instead of bank’s own portal.
To discuss the analysis of SMA application by DBS bank in its operations, we will talk about the lessons that we have learnt from this case study.
SMA assets and capabilities can be outsourced
DBS bank has proved that the organization needs not to have a personalised team or department to apply Social Media Analytics and to accumulate date from social sites, but it can be done by involving a third party that is by outsourcing the task to other company that is specialized in doing this task. Thus, specialized assets and capabilities are not required. There is no risk of getting the data copied as the information is available online and anyone can get it. The data itself does not provide any value to the business but it is the interpretation and understanding of data accumulated which matters the most. It can be said that the ability of an organization to act on the SMA results is the main task and that is what contributes to a company’s success (Teodorescu, 2015). DBS bank is specialized in making use of information gathered from other sources and designs the strategies and alters the processes as per requirement of the market which has been assessed with the help of customers’ remarks and behaviour on social media. The bank has the ability to join the outsourced data and non-outsourced results and thus take an appropriate action accordingly.
Dynamic Capabilities are important in using SMA
To introduce the new technologies and innovations in an organization, it is mandatory to have dynamic capabilities. DBS Bank has a specified department to apply the new strategies that have been designed following the data accumulated through SMA (Teodorescu, 2015). It helped the bank to keep a check on the response that has been shown by customers on the introduction of new marketing strategies. The department is quite efficient to address the complaints timely that have been recorded from social media. Organizations that plan to use Social Media Analytics should have a strong team, mature management, and decision makers to make use of the opportunities available through the application of SMA in their business.
Early adopters get competitive advantage
DBS Bank made full and timely use of SMA by checking how successful the marketing campaign launched by it is. By this, the bank came to know about the outcome timely. The response from customers was noted and the impacts were considered immediately to apply into further decisions and campaigns. It helped the management to make the alterations and increase the effectiveness of champagne accordingly (Teodorescu, 2015). It also helped them understand if further investing in SMA will be beneficial or not. It resulted in a hike in the number of visitors on the bank’s blog and social site. The launched campaign became a hit and attracted a large number of people to the blog. It can be judged that the proper and effective use of available data results in a competitive advantage. The change in the customers’ behaviour and perception lead to high customer satisfaction level and thus attracted more customers. The bank also profited by a number of repeat customers for other financial services and a considerable number of referral customers.
Conclusion
Social Media Analytics helps an organization accumulate rough data from social media sites and thus use the sentiments taken out from that data to apply into the strategy formation and product designing as per customer’s expectations. It also helps an organization become high service provider by timely addressing to the customers’ issues. This paper discusses the Social Media Analytics framework, its function, life-cycle and the process in business organizations. This explains how it helps any organization to grow and bring values to it (Teodorescu, 2015). The process was explained by different theories like organizational motivation theory and resource-based theory. We have taken a leading Asian financial Institute, DBS Bank as our case study to apply SMA on it and check the value that has been added to it by the application of SMA.
References
Atwong, C. (2015). A Social Media Practicum: An Action-Learning Approach to Social Media Marketing and Analytics. Marketing Education Review, 25(1), 27-31.
Chadwick, A. (2015). The “Social Media” Maneuver. Social Media + Society, 1(1).
He, W. & Xu, G. (2016). Social media analytics: unveiling the value, impact and implications of social media analytics for the management and use of online information. Online Information Review,40(1).
Jensen, K. (2015). What’s Social About Social Media?. Social Media + Society, 1(1).
Perrotta, C. & Williamson, B. (2016). The social life of Learning Analytics: cluster analysis and the ‘performance’ of algorithmic education. Learning, Media And Technology, 1-14.
Philip Chen, C., Tao, D., & You, X. (2016). Big learning in social media analytics. Neurocomputing.
Philip Chen, C., Tao, D., & You, X. (2016). Big learning in social media analytics. Neurocomputing.
Teodorescu, H. (2015). Using Analytics and Social Media for Monitoring and Mitigation of Social Disasters. Procedia Engineering, 107, 325-334.
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