Recency, Frequency, Monetary
Customer clusters are grouped as it is wanted and named based on RFM values: fanatic, loyal, active, etc.
Validating and controling the accuracy of the customer data with different approaches by providing reports to understand the data quality issues easily: logical data control reports, wrong data entry detection reports, and repeating records.
Reports and dashboards show sales and purchase patterns of customers depending on demographics.
Analysis of where and which product groups are being purchased, shopping profile of customers based on gender, hours they spend shopping, days of the week, and their job.
Segment Migration Analysis
RFM and customer value segmentation is being made within certain periods. We can track, monitor, and analyze transitions among segments.
You can easily monitor the previous segment and trend of lost customers and predict the losing risk of valuable customers.