1. IBM Big data applications
Prepared by: Celeste Ng
Date: 2016
Direct Quotes from Source: as indicated in the slides

2. Source: http://www.ibm.com/big-data/us/en/

3. Source: http://www.ibm.com/analytics/us/en/business/

4. Source: http://www. ibm

5. Source: http://www. ibm

6. IBM customer big data analytics – Slovenský plynárenský priemysel, a. s. Source: click here
Who: Slovenský plynárenský priemysel, a.s. (SPP) has more than 150 years of experience in the gas industry. In 2012, ... SPP entered the electricity market. Today, SPP is one of the largest energy suppliers in Slovakia, offering both natural gas and electricity.
What: Using customer segmentation, achieved by analytical modeling, SPP can reach the right customers with the right product offers. A new, targeted multichannel campaign strategy helps it cross-sell交叉銷售electricity to its gas customers and offer new customers special incentives for switching to either its gas or electric services.
How: A customer-loyalty index and early warning indicators help the company reduce churn by quickly reaching out to less-than-satisfied customers with new offers and better customer service.
Churn-reduction campaigns are now 50 percent more efficient thanks to early warning indicators and alerts,

7. IBM customer big data analytics – BBVA seamlessly monitors and improves its online reputation --- (1) Source: click here
Who: BBVA is a global group that offers individual and corporate customers a comprehensive range of financial and non-financial products and services. It enjoys a solid leadership position in the Spanish market, where it first began its activities over 150 years ago BBVA employs approximately 104,000 people in over 30 countries around the world, and has more than 47 million customers and 900,000 shareholders.
What: the bank has implemented an automated solution to monitor and measure the impact of brand perception online – whether this be customer comments on social media sites (Twitter, Facebook, forums, blogs, etc.), the voices of experts in online articles about BBVA and its competitors, or references to BBVA on news sites – to detect possible risks to its reputation or to possible business opportunities.
How: the bank can now respond to negative (or positive) brand perception by focusing its communication strategies on particular Internet sites, countering – or backing up – the most outspoken authors on Twitter, boards and blogs.

8. IBM customer big data analytics – BBVA seamlessly monitors and improves its online reputation --- (2) Source: click here
How: IBM Social Media Analytics will allow BBVA to monitor the voices of current and potential clients on social media websites such as Twitter, Facebook and message boards, identify expert opinions about BBVA and its competitors on blogs, and control the presence of the bank in news channels to gain insights and detect possible reputational risks.
How: The content of the comments is subsequently analysed using custom Spanish and English dictionaries, in order to identify whether the sentiments expressed are positive or negative.
How: “When BBVA detects a negative comment, a reputational risk arises,” explains Miguel Iza Moreno, Business Analytics and Optimisation Consultant at IBM Global Business Services, “Social Media Analytics provides a reporting system which identifies the origin of a negative statement and BBVA sets up an internal protocol to decide how to react. This can happen through press releases, direct communication with users or, in some cases, no action is deemed to be required; the solution also highlights those cases in which the negative comment is considered ‘irrelevant’ or ‘harmless’. The same procedure applies to positive comments – the solution allows the bank to follow a standard and structured process, which, based on positive insights, enables it to strengthen its reputation.”