Through the application of the MAD framework (Monitor, Analysis & Detail), we can monitor and analyse these factors in detail, allowing us to gain valuable insights that contribute to revenue optimisation strategies. By closely examining transaction volume and its value, we can identify trends and patterns that reveal opportunities for growth and efficiency improvements. Additionally, analysing commission rates enables us to assess the profitability of merchant partnerships and determine whether adjustments are necessary. Identifying the top payment modes helps us understand customer preferences, enabling us to optimise payment processing systems for enhanced convenience and customer satisfaction. By evaluating product performance, we can identify high-performing products and promote them strategically, while also identifying areas of improvement for underperforming products. Furthermore, analysing the top merchant categories and sub-categories allows us to identify potential market segments that can be targeted for increased revenue.

### Answer Key Business Questions

* What are the top-performing merchant categories/geo segments?
* How are our transaction and merchant bases segmented by geographies and payment methods over time?
* What is the average ticket size and how has it changed over time for various market segments/geos?
* What is the failure % on transactions over time across payment methods?
* What categories are customers spending on?

### Monitor and Improve KPIs

* Transaction Value – total value of transactions in a given period
* Transaction Count – total number of transactions in a given period
* Average Ticket Size – average ticket size of transactions in a given period
* Commission Due/Earned – commission calculated on transactions processed, by payment method
* Transaction Success/Failure % – transaction failure or success rate, by payment method
* Top Merchants and Merchant Categories – top-performing merchants, categories and subcategories
* Commission by Payment Mode – commission charged by payment mode

### Required Data Attributes

* Week (numeric)
* Date (date)
* Merchant Catergory (string)
* Merchant ID (numeric)
* Merchant Sub Category (string)
* Merchant Name (string)
* Transaction Amount (numeric)
* Transaction Count (numeric)
* Payment Mode (string)
* Card Type (string)
* Payment Status (string)
* Product (string)
* Country (string)
* State (string)
* City (String)
* District (string)
* PinCode (numeric)
* Charge (numeric)

Merchant Analytics - Payment Provider

Identify trends revealing opportunities for growth & efficiency improvements