Founded in 1984, Haier Group is the world's leading provider of home appliances. Haier’s SCRM has stored billions of users’ data. Social Touch facilitated the update of Haier Interaction, the software with the function of users interactions

The Challenge

Haier Interaction was designed to discover the value of Haier’s active member clients and enable innovative interactions. However, the system had the following shortcomings. Firstly, as the data analysis process was non-automated, the system did not enable user integrations and real-time data analysis. Secondly, the analysis results cannot be seamlessly integrated with other IT systems. Thirdly, the database of user portrait was insufficient therefore required external data supplement

The Solution

To upgrade Haier Integration, Social Touch created a framework of consumer-oriented data applications. The framework integrates demand analysis, product R&D, product launch channels, production of promotion content, consumer feedbacks and consumer behaviour analysis

• Scenario-driven: we designed a scenario-based product experience process on Haier Interaction. Through the association rule algorithm, we defined the most important product features that satisfied targeted consumers’ demands. Based on the above analysis, we were able to develop a comprehensive user portrait and determine accurate communication contents and channels

• Intelligent prediction: with the in-built marketing scene analysis model, Haier Integration was enabled with the functions of data visualization and real-time data analysis. With this advanced analysis tools, the system could forecast the market demands of specific product features and proceeded the corresponding product updates
  
  

• Clear actions: we ensured that the analysis results of Haier Interaction are clear and executable, and can be seamlessly integrated with other data appliances. Based on the association rule and crowd feature analysis, the system was able to visualize potential consumer groups that are sorted by their buying intention.

The Result

• Connected to 140 million offline user data and 1.9 billion online user data

• Established a 360-degree user portrait system, constructed by 7 levels, 143 dimensions and 5,236 nodes

• Created over 1.1 billion data labels

• Established 10 data models under three categories to quantitatively define users’ consumption needs