Banks are looking for ways to transform their internet banking from “Transaction Oriented” to “Sales & Service Oriented”.
However, anything that is too sales oriented are at risk of losing customers’ trust and loyalty. What bank customers want on a bank’s web site are tools/services that give customers better insight, control, and enable them to make better decisions (Gartner 2009). Banks have to response and build innovative selling techniques that focus more on helping their customers better manage their money and less on “direct” selling.
Our solution solves this problem and accelerates the banks’ transformation in an innovative approach through social empathy selling. Empathy selling, people like people who are like themselves, used around the world as a systematic method of closing sales effectively and quickly. As for social empathy selling, we leverage the massive customers to “do empathy selling” for customers by using their past REAL behaviors. For example, we can mining financial communities/ consumption communities and roles inside each community, such as peers/experts/pioneers, etc, and then help customers to better manage their money or optimize their spendings by presenting peers/experts/pioneers’ financial actions and investment to current user in an interactive process.
This year, we are working on a FOAK project with one of the largest banks in China, consolidating and evaluating our solution based on 30M+ customers data. By doing this, we've gained very positive feedbacks from customers, and also made great achivements from two aspects:
In financial domain, we proved that Social Empathy Selling is an effective way to help banking customers expand their financial vision and optimize portfolio by leveraging collective intelligence of massive users; we also provide 1-to-1 financial suggestions to banks’ financial advisors when they facing every customers in a real-time manner. In consumption domain, we leverage the cutting-edge 1-to-1 recommendation technologies to model customers’ changing preference based on their credit card transactions, thus greatly boosted the quality of merchandise recommendation by 30% comparing with state-of-art works in industry.