Data analytics center
Customer analysis is based on the statistics and analysis of customer characteristics. It can be used to conduct group profile, answer the group characteristics of the customer group that the brand pays attention to, and support the judgment of the effectiveness of marketing strategies, such as: which channels bring the most customers ? At what stage are customers currently concentrated? Which event brought the largest new passenger flow?
Count the number of people, visits and trends of each behavior. Behavior analysis can understand the following similar information:
- How often users visit a certain page
- Recent order volume and turnover
- Which customer group has the most orders
- Comparison of the number of people who have followed/unfollowed the official account in the past period of time
Time distribution analysis can help brands understand customer behaviors in a specified time window. Data Kanban can be presented according to week and 24-hour distribution heat maps to intuitively understand the characteristics of different customer behaviors in time distribution.
Funnel analysis can help brands measure the conversion and loss of customers at each step of a certain business process, and then optimize the design of the customer experience journey in marketing strategies by analyzing the conversion data of each step, and improve customer experience and conversion rate.
Path analysis can help brands understand the sequence of customer behaviors, so as to clearly understand what related behaviors will occur before and after a certain behavior (such as placing an order).
Conversion interval analysis can be used to find out what characteristics of the associated time interval two potentially related behaviors have and perform correlation analysis. For example, how long does it take for new WeChat fans to complete membership registration; how long does it take for a customer to complete an order after adding a shopping cart.
DM Hub provides a set of analysis tools for order data, which can help companies effectively analyze the characteristics of customer transaction behaviors, including:
- order analysis
- return order analysis
- RFM analysis
- repurchase analysis
The data Kanban can aggregate and manage all analysis items, and display the analysis results in a centralized manner. All the above analyses can be used as one of the analysis components of the data Kanban, and aggregated and displayed here.