With the advancement of the digital strategy, major banks continue to increase investment in online multi-channel construction, and customer access is becoming more mobile and intelligent. At the same time, the rapid development of mobile banking has generated and accumulated a large amount of customer behavior data, which is characterized by diversification and massive quantity, and will play an important role in user experience, customer management, and mobile banking operations. The establishment of a unified customer journey analysis and management platform has become an important part of the bank's digital transformation to better meet the needs of refined operations and journey analysis, so as to provide customers with a better experience and achieve rapid user conversion. Business scenarios such as retention and customer segmentation.
#01 Industry Status and Pain Points
Major banks are actively developing and operating online channels, such as online banking, mobile banking, mini programs, official accounts, etc., hoping to integrate different online and offline channels to achieve "omni-channel" (omni-channel) coordinated development. In this process, how to analyze the data in the marketing link, improve marketing efficiency, and increase user retention and conversion has become the key for banks to do a good job in retail business.
With the growing demand for data analysis and management, the shortcomings of traditional data analysis solutions are highlighted:
- Omni-channel coverage is wide and deep, data sources are diverse, and analysis is difficult: According to statistics, customers now need to go through more than 9 touchpoints for a transaction, including internal and external digital products and offline physical touchpoints. The collected data includes not only traditional transaction data, but also customer data, behavior data, and business data, among which there are both structured data and unstructured data, which require a certain degree of integration before query analysis can be performed.
- It is difficult to meet the needs of business departments for rapid response and agile analysis: traditional data analysis methods and architectures can no longer meet the business needs of refined operations. Business personnel hope that the analysis results can be found immediately, and various types of data analysis can be performed flexibly according to business needs .
- The timeliness of the data is poor, and it is impossible to quickly grasp the operation status: a large amount of data needs to be integrated and processed by professionals, and the time cost and labor cost remain high. Business personnel also hope to realize real-time data analysis, so as to quickly obtain the effect of marketing activities and adjust marketing strategies in a timely manner.
#02 Customer-centric, build a unified customer journey analysis and management platform
Kyligence provides customer journey analysis and management solutions, and has helped leading joint-stock banks build a unified customer journey analysis and management platform to optimize business goals, behaviors and methods around customer journeys and improve customer experience.
The platform abstracts user behavior, captures the multi-dimensional attributes of each behavior, updates customer tag information in real time, stores event and user data in Hive and Kudu respectively, establishes a unified "event and user" data model, and integrates mobile banking, online Data from various channels such as banks, customer service marketing, etc. are connected through ID Mapping to realize data sharing among multiple projects. The customer journey analysis and management solution architecture is as follows:
At the query engine layer, Kyligence uses the storage and parallel computing capabilities of the big data platform to pre-calculate the event+user dual-table data model to improve query efficiency; at the application layer, the platform realizes the decoupling of technology and business, and the data structure The change does not affect business analysis, and business personnel can conduct data analysis conveniently, flexibly and in real time, improve operational efficiency, and help the bank create "customer-centric" products. Currently, Kyligence customer journey analysis solution supports enterprises:
- Construct 9 major analysis scenarios: such as event analysis, funnel analysis, customer path analysis, attribution analysis, etc., analyze customer acquisition and conversion rates of different channels, optimize product core processes, and tap high-quality channel resources;
- Analyze the scene to lock the target user group: deep drill-down analysis to gain insight into the 360º panoramic characteristics of a single customer to achieve refined operations;
- Adopt innovative local aggregation and bitmap accurate deduplication technology: realize real-time second-level response of full analysis scenarios, fast and agile in-depth analysis, and continuously improve operational efficiency;
- Visual multi-scenario and custom analysis: realize self-service analysis of business personnel, reduce development cycle and cost;
- Supports privatized deployment: adopts a simple service architecture different from microservices, and has no dependencies between analysis modules, enabling easy and simple deployment, maintenance, development, and upgrades;
- Multi-dimensional data security control: Realize dual security control of business modules and data access to ensure data security.
#03 Real Case
At present, Kyligence helps the country's leading joint-stock banks to build a unified customer journey analysis and management platform. The platform has been launched for one year and has been promoted to multiple projects and business scenarios in the head office and branches. The project has achieved remarkable results:
- In the case of customer journey data increment of 100 million pieces per day and dozens of concurrency , second-level query response is achieved; real-time update query of customer data is supported under high concurrency, and the delay of customer behavior data is controlled within half an hour within;
- It can input and output large-scale grouping data in a timely manner, and can effectively link with the marketing system, breaking the data sharing barrier between different systems;
- In terms of marketing , the customer journey platform can track traffic, identify quality, identify clues, and group users to carry out targeted marketing to improve user stickiness and return rate;
- In terms of product operation , the customer journey platform can analyze the core conversion process, find churn problems, improve user conversion, improve user retention, and track user behavior paths to effectively improve user experience;
- In terms of operational decision-making , the customer journey platform can be deeply combined with cross-analysis of operational data to gain insights into core user characteristics and draw accurate user portraits. It can also help managers grasp the core indicators of multiple departments and business lines in real time, discover problems, and make timely decisions.
The data product "Customer Journey Kaleidoscope" created by Kyligence has realized data-driven insight into customer journeys, which can effectively improve mobile banking management level and customer experience, dig deep into customers' potential needs and optimize marketing strategies. Has enormous meaning and value.
——Head of Big Data System of Leading Joint Stock Bank
About Kyligence
Shanghai Kyligence Information Technology Co., Ltd. (Kyligence) was founded by the founding team of Apache Kylin in 2016. It is committed to building the next generation of enterprise-level intelligent multidimensional databases and simplifying multidimensional data analysis (OLAP) on data lakes for enterprises. Through AI-enhanced high-performance analysis engine, unified SQL service interface, business semantic layer and other functions, Kyligence provides cost-optimized multi-dimensional data analysis capabilities, supporting enterprise business intelligence (BI) analysis, flexible query and Internet-level data services, etc. Application scenarios help enterprises build a more reliable indicator system and unleash the potential of business self-service analysis.
Kyligence has served many customers in banking, securities, insurance, manufacturing, retail and other industries in China, the United States, Europe and Asia Pacific, including China Construction Bank, Shanghai Pudong Development Bank, China Merchants Bank, Ping An Bank, Bank of Ningbo, Pacific Insurance, China UnionPay, SAIC, Costa, UBS, MetLife and other world-renowned companies, and reached global partnerships with technology leaders such as Microsoft, Amazon, Huawei, and Tableau. At present, the company has opened branches or offices in Shanghai, Beijing, Shenzhen, Xiamen, Wuhan, Silicon Valley, New York, Seattle, etc. in the United States.