1. Facebook Financial Services
Norman Niemer
Used Facebook Graph API to analyze metrics on Financial Services fan pages and posts
Top 10 US financials, 200 recent posts = 2000 data points. Another 1,200 for Citibank global
Stack: Preprocessing Python + Graph API, Storage SQL, Processing R, Excel
Ran a number of experiments:
#1: Potential for financial institutions to interact with customers. Only 3% penetration
#2: Potential for Facebook to gain share of $17bn buget. Only 3% penetration?
#3: A global opportunity. Citibank’s engaged emerging market communities
#4: Who runs the most effective pages? MetLife and B of A. Laggards need to catch up
1
#5: When to post? Mondays are best, as are afternoon and evening hours
Additional experiments TBD:
Outliers analysis – what defines the viral post?
Weekly reports for clients – what’s on consumers mind?
Solution selling: build relationships with financial institutions by providing advice and solutions
Help them run an effective social media strategy
Norman Niemer: 8 years experience in quantitative data analysis at financial institutions
Entrepreneurial: drove improvements at both small and large companies
Tech affinity: founded tech company in high-school, running SaaS startup now

2. Experiment #1: Potential for Financial
Institutions to Interact with Customers
Significant potential for financial institutions to interact with Facebook users
Chase, Blackrock do not even have a page
494.3
400.0
500.0
# of Customersvs # of Facebook Likes
(Top10 US Financial Insitutions)
2
12.6
-
100.0
200.0
300.0
400.0
Top 10 Financial Institutions
# Customers (MM) # Likes (MM)
Only 3%
penetration
Top 10 US Financial Institutions include: Amex, Capital One, MetLife, Wells Fargo, B of A,
Citibank US, Fidelity, U.S. Bank, Schwab, PNC Bank, Travelers Insurance

3. Experiment #2: Potential for Facebook to Gain
Wallet Share
If user penetration = wallet share penetration, significant potential for Facebook to gain share
within large marketing budgets
Top 10 US Financial Institutions command $17bn marketing budget
16.8
14.0
16.0
18.0
Marketing Spend vs Facebook US FS Sales
(Top10 US Financial Insitutions)
3
0.4
-
2.0
4.0
6.0
8.0
10.0
12.0
Marketing Spend ($bn) Facebook US FS Sales ($bn)
Only 3%
penetration?

4. Experiment #3: A Global Opportunity
Citibank has a very vibrant emerging market online community
Sharing rates in Singapore significantly higher than in the US (see appendix)
Sharing Rates for International Citibank Pages
4

5. Experiment #4: Who runs an effective Facebook
Page?
Sharing is the highest form of user engagement
Travelers off the chart due to agents
B of A and MetLife register high number of shares, likely shares related to sports events
Capital One needs to catch up with Amex and Charles Schwab with Fidelity
Sharing Rates for Top 10 US FS Pages
5

6. Experiment #5: When to post?
# shares the highest on Mondays
Evening and lunch as well as afternoon hours see highest shares
Companies avoid posting in the morning already
Sharing Rates by Weekday Sharing Rates by Hour
6

7. “A Tale of Two Cities”
Users post both positive and negative comments
Resources have to be set aside to handle feedback
7

8. Solution Selling to Financial Institutions
Low Facebook penetration provides both challenges and opportunities
Challenges financial services customers are facing:
Regulatory concerns – some institutions seems to have solved them
Process for providing customer service via Facebook – see previous slide
New medium, still trying to figure out how to use it
Solutions:
Help them run an effective social media strategy
– Not just ads but integrate with their marketing campaign
8
Help them understand their customers
– Provide regular analytics e.g. sentiment analysis and what’s trending with customers
Provide regular analytics on Facebook campaigns and discuss with clients
Tailor to sub-industry, i.e. banks vs asset managers vs brokers

9. Appendix: Significance Test for Sharing Rates
Across Citibank Country Pages
Test if post sharing in emerging economies differs from US
Result: share rates in Singapore is significantly different but not in other countries
Tests conducted: F-test for combined means and t-test for pairwise means
Challenge: highly non-normal distribution with many values concentrated around zero
Comparison of % Shares in Different Countries
(Bonferroni Test)
9
(Bonferroni Test)
India Malaysia Philippines Singapore
Malaysia (0.21)
1.00
Philippines (0.05) 0.16
1.00 1.00
Singapore 1.47 1.68 1.52
0.00 - 0.00
US (0.06) 0.15 (0.00) (1.53)
1.00 1.00 1.00 0.00