Categorization Overview
We have upgraded our transaction categorization system from a 2-level hierarchy to a 3-level hierarchy as of June 2024. This new structure enhances the granularity and flexibility of categorizing transactions, allowing for more precise and customized mapping. We still support the old legacy category system.
All new customers will have access to this new system by default. Existing customers will continue to use the old 2-level categorization system unless they opt-in to switch to the new system by getting in touch with our sales team.
Key Features:
3-Level Hierarchy: Our categorization now includes three distinct levels: Parent Category, Category Group and Category Type.
Extensive Categories: Over 500 Category Types are available, which can be mapped to Category Groups, and these Category Groups can be mapped to Parent Categories.
Customization: The categorization system is flexible and can be customized to align with your specific category requirements.
Importance of the New Categorisation System
The enhanced 3-level categorisation system is crucial for several reasons:
Understanding Spending Patterns
The detailed categorization helps in identifying and analysing consumer spending patterns more accurately.
Businesses can track which categories are seeing the most spending and adjust their strategies accordingly.
Consumer Behaviour Insights
With more granular data, businesses can gain deeper insights into consumer behaviour.
This can include understanding preferences, frequent purchase categories, and seasonal trends.
Bespoke Analysis:
The enhanced categorization allows for more specific and customized analysis.
Businesses can tailor their reporting to focus on niche categories and specific consumer segments.
Targeted Offers and Campaigns:
By understanding detailed spending habits, businesses can create targeted marketing campaigns and personalized offers.
This increases the effectiveness of promotional efforts and improves customer engagement.
Fraud Detection
Improves the detection of fraudulent transactions by recognizing spending patterns that deviate from the norm.
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