Social Media Analytics – BFSI (Part II)

bfsi-social-media-analytics-fusion-analytics-world

Bankers: Understand and improve your brand through social media sentiments

If a bank could figure out that one its clients just got married or had a kid or met with an accident, those real life events could produce selling opportunities for that banking institution. If it could understand its customers’ real life situations, they would be able to market specific products and services tailor made to suit customer’s unique requirements.

Gone are those periods of queuing up in a branch or over the telephone to speak to the bank. Currently, customers are able to speedily raise their through social media, and it has turned out to be a major medium for banks to strengthen bonding with their clients and also to reach out to the youth. These days more and more banks are revamping their social media teams indicating the rising strategic relevance of social channels.

Using social media analytics tools, technology savvy banks are continuously monitoring useful insights from social media conversations. Within the huge volume of conversations happening round the clock lies a wealth of relevant information for banks like insights into their weakness areas related to customer services; websites, products and mobile applications clients hating or loving; understanding their customer’s voice and further mapping with its competitors; thereby being able to make informed decisions.

To showcase the real impact, Kalyan Banga, Founder & Principal Analytics Consultant of Fusion Analytics World now analyzes the sentiments flowing around major banks:

  1. Sentiment Balance:

Sentiment balance shows the proportionate balance of positive and negative sentiments expressed in conversations from social media. Fusion Analytics World automatically categorizes data under positive, negative and neutral sentiment using advanced text analysis and natural language processing.bfsi-sentiment-balance-social-media-analytics-fusion-analytics-world

The chart clearly indicates that Sberbank has the overall best sentiment balance followed neck and neck by Standard Chartered Bank and Bank of China. On the other hand, China Construction Bank has the worst sentiment balance followed by ICBC since difference between their positive and negative sentiments is negative indicating much higher negative sentiments for both the banks in comparison to positive sentiments that Fusion Analytics World is tracking.

Visa with high volume and high negative sentiment indicates most of the conversations are not what their PR and Marketing teams would like to see. Insights like these help brands take immediate actions before things go out of control, especially by knowing the topics of discussion elaborated in the next section.

  1. Understanding the Conversation Map:

The Fusion Analytics World analysis goes deeper into the data to understand through conversation map about what customers talk on social media. For the convenience of bankers, bubble shows the size of each conversation topic, and lines connecting the bubbles show how frequently these different topics were discussed together on the same mention (i.e., tweets or blogs etc). –conversation-map-network-graph-bfsi-fusion-analytics-world

Mortgage and Payments, Loans and Mortgage, Credit Checks and Loans, Online Banking and Loans, Credit Cards and Rewards were some of the top conversation topics discussed on the same mention around banks. Understanding relative proportions of discussion with the help of above visualizations can help marketers’ device appropriate promotions. For example understanding that discussions around Online Banking is 2 times more popular than Banking, discussions related to Mortgage are way more popular than Interest Rates etc., can help in leveraging appropriate topics for their next marketing campaign. conversation-themes-social-media-analytics-fusion-analytics-world

To recognize the causes responsible, we have used advanced deep text analytic techniques to identify the common negative themes present in these mentions. Image above shows a word cloud of the most common positive and negative themes present in mentions for banks.

The top negative themes emerging from the above analysis for banks are related to bad loans, issue with risk officer, commercial mortgages, poor investment advice, flawed mortgages, absurd cashback related experiences. It looks like their customers are not really enjoying these as much as Bankers would want them to. Looking further, we also find that people are showing displeasure related to bad mortgage deals, financial crimes, service disruption and terrorism money related experiences. The key positive mentions are regarding great offers, gift cards, savings accounts, SME lending, commercial banking and so on. Interesting to note while customers are happy with residential mortgage loan, however, they have shown concern regarding commercial mortgages, mortgage deals and flawed mortgages. Insights like these can help banks take immediate action so as to increase satisfaction of customers thereby reducing negative sentiments flowing.

 

Profile Status
ACTIVE
Profile Info
 

Kalyan Banga204 Posts

I am Kalyan Banga, a Post Graduate in Business Analytics from Indian Institute of Management (IIM) Calcutta, a premier management institute, ranked best B-School in Asia in FT Masters management global rankings. I have spent 6 years in field of Analytics.

1 Comment

Leave a Comment

9 − 2 =