With increasing competition within cosmetics industry, CRM is no longer welcomed by consumers due to large quantity of blind pushing. Customer relationship management CRM only involves actual customers’ purchasing without understanding their life preferences. So we tried to use SNS. Meanwhile, SNS operation only involves potential customers’ interests and hobbies but not purchasing; usually the two types of resources are managed by different departments within client (CRM in Sales Department and SNS in Advertising Department), and the data do not relate to each other either, thus cannot play an effective role.

In our opinion, for continuous business development, it is a challenge for us whether we can newly integrate the originally unrelated CRM and SNS data, thereby developing new customer relationship management system S-CRM based on customers ’life preferences and social behaviors, making customers take initiative to perceive the brand voluntarily and be attracted by the brand, and achieving purchasing at the same time.

Our plan is divided into the following five steps:

1) Find out quality customers’ purchasing data from customers’ existing CRM database.

2) Based on the purchasing data of quality customers, find whether they use microblog.

3) Through Text Mining, summarize the lifestyle and interests of quality customers.

4) We have found out the people in what life status prefer purchasing what products of customers, and define this feature cluster as the new standards of communication. Establish S-CRM guide line for mining of new customers

5) S-CRM system will find people with the conforming lifestyle from potential people, and automatically define them as people with high purchasing possibility. Communicate customers’ activities information with them and trigger new purchasing behaviors.

The purchasing and social behaviors of past customers (CRM) and potential customers (SNS) have all been included in S-CRM communication system, forming a new dynamic and effective cycle. S-CRM Campaign lasted for one month, with 8 times of increase in both click rate and shop visiting rate.