Payment Source Analytics

Paytm has now powered its merchant dashboard offerings with enhanced success analytics views that will let you analyze and benchmark the performance of your transactions across various time periods.

Major highlights of the success analytics dashboard are given below:

• It will help you gauge your recent success rate performance of your transactions
• It will help you drill down to the specific paymodes, issuing banks, channels or payment flows with lower success rates as compared to the benchmarks (temporal and industry)
• It will highlight the most significant reasons behind these failures
• Under certain scenarios, it also suggests corrective measures to rectify these failures

The success analytics dashboard generally uses some metrics across its views to gauge the performance of your transactions. The details of these metrics have been postulated below:

• Transaction Count: It is the sum of the number of transactions initiated (successful, failed, and pending) by the merchant in a selected time period.
• Transaction Share: Transaction share of a payment attribute (eg. Payment Source) is the ratio of the number of transactions for that particular attribute to the total number of overall transactions.
  For example: If the total number of merchant transactions are 1.5K for 30th March and the total number of credit card transactions for the same merchant on 30th March is 150 then:
  
  Transaction Share of Credit Card (30th Mar) = (Total number of merchant credit card transactions on 30th Mar)/(Total number of merchant transactions on 30th Mar)
                                                                          = 150/1,500
                                                                          = 10%

• Failure Share: Failure share of a payment attribute (eg. specific failure reason) is the ratio of the number of failed transactions for that particular attribute to the total number of failed transactions.
  For example: If the total number of merchant failed transactions are 150 for 30th March and the total number of transactions failed due to "Incorrect PIN" for the same merchant on 30th March is 30 then:
  
  Failure Share of Incorrect PIN (30th Mar) =  (Total number of merchant transactions failed due to Incorrect PIN on 30th Mar)/(Total number of merchant failed transactions on 30th Mar)
                                                                       =  30/150
                                                                       =  20%

  Note:
  In case the value of one or more of the past 3 data points are missing then the Moving Average will be computed based on the data points available. For example: In case of calculating the Moving Average of data point 30th Mar in Yesterday View, the value of 29th Mar is not available then Moving Average will be calculated based on the average of 28th & 30th Mar (2 data points) data.

• Moving Average: Moving Average of a point in any trend line graph of the success analytics dashboard would be the average of the last 3 data points on the trend line graph. 
  • Yesterday: If yesterday was 30th Mar, the moving avg. values over 30th Mar data point on X-Axis will consist of data for a simple average of 28th, 29th and 30th Mar. 
  • Current Week: If yesterday was 30th Mar, the moving avg. values over 28th to 30th Mar data point on X-Axis will consist of data for a simple average of 15 Mar to 21 Mar, 22 to 28 Mar and 29th to 30th Mar. 
  • Current Month: If yesterday was 30th Mar, the moving avg. values over Mar data point on X-Axis will consist of data for a simple average of Jan, Feb & Mar.

• Industry Average: Industry Average of an attribute (eg. Success Rate) is the average of that attribute value considering transactions belonging to all the merchants who have the same industry as the merchant.
• Benchmarking: Benchmarking with respect to a time period means comparing your performance in the current time period with the same tenure in the previous time period to provide an insight into an improvement or deterrent observed in recent transactions.
  
  The benchmarking is generally done across the below three views:
  • Yesterday: The benchmarking in this view compares the performance of yesterday with the same day last week. For example: if yesterday is Sunday, 28th Mar then benchmarking should be done on Sunday 21st Mar. 
  • Current Week: The benchmarking in this view compares the performance of days within this week (Monday to yesterday) with the corresponding days last week. For example: If yesterday was 30th Mar (Tuesday) then the benchmarking would compare the performance of 29th & 30th Mar to that of 22nd & 23rd Mar.
  • Current Month: The benchmarking in this view compares the performance of days within this month (1st to yesterday) with the corresponding days last month. For example, If yesterday was 27th Mar then the benchmarking would compare the performance of 1st to 27th Mar to that of 1st to 27th Feb.
• Success Rate: Success rate is defined as the ratio of successful merchant transactions to that of all transactions of the merchant.  
• Drop Rate: Drop rate is defined as the ratio of transactions where the customer dropped off on the cashier page to all transactions initiated (successful, pending & failed).
• View: This is a filter that you can use to change the time period of your trendline/doughnut graphs.

You can choose from the options below:

The Overall Summary tab is designed to provide a high-level view of the recent performance of your transactions and to highlight the key areas (failure reasons and paymodes) responsible for the drop in your overall performance.

You can see below the key highlights of this dashboard: 

1. It helps you gauge your recent performance of your overall transactions and compare it with prior time periods and industry performance.
2. It highlights the details of the top reasons for the failure of your transactions.
3. It provides the breakup of your transactions across all paymodes.
4. It helps you compare the performance of your transactions across paymodes.

Success Rate Performance

This section helps you analyze the recent success rate performance of all your transactions and benchmark it with the prior time periods. All success rates and benchmarks have been rounded off to the nearest integer.

You can see below the details of various time periods: 

1. Yesterday: This view provides the success rate data for all yesterday's transactions. The benchmarking is done with respect to the rules mentioned in the above section.
2. Current Week: This view provides the success rate data for all transactions from Monday to yesterday this week. The benchmarking is done with respect to the rules mentioned in the above section.

   Note: If today is Monday then the current week data comprises of last week's data from Monday to Sunday.

3. Current Month: This view provides the success rate data for all transactions from 1st to yesterday this month. The benchmarking is done with respect to the rules mentioned in the above section.

   Note: If today is the 1st of a month then the current month data comprises of last month's data from 1st to 30th (or 2nd to 31st).

Success Rate Trend

This graph has been designed to showcase the success rate trends of your transactions across the chosen time-period and compare it with the average trend, industry trend or the transaction count trend in the same time period.

You can see below the filters provided for the success rate trend graph: 

1. View: This filter helps you choose the time period across which you would want to observe the success rate trendline of your transactions. Details of this filter have been provided here.
2. Overlay: This multi-select filter helps you choose the metrics you would want to overlay on the success rate trend graph. The available metrics that can be chosen from are given below:
   1. Moving Average
   2. Transaction Count
   3. Industry Average

Failure Reason

This section helps you understand the overall top 5 reasons for the failure of your transactions. These failures may have happened by the user, bank or Paytm. It also highlights the rise/fall of these failures in recent times as compared to the previous time period.

You can see below the details of the graph present in this section: 

1. Failure Breakup: This is a doughnut chart that highlights the breakup of failure share across the top 5 five failure reasons and others (which comprises of all the remaining failure reasons) in the selected time period. This doughnut chart is sorted with respect to the failure share of each failure reason.
   
   You can see below the filter available for this doughnut chart: 
   1. View: This filter decides the time period for which the "Failure Breakup" chart will be created. Details on this filter have been provided here. 
       
2. Top Failure Reasons: This table highlights the top 5 failure reasons (and others)  for the merchant transactions that happened yesterday. The table also highlights each of these failures if it happened due to the user, bank or Paytm (Wallet). The failure share/transaction share of these transactions are showcased for the below three time periods:
   1. Yesterday: This view provides the failure share/transaction share data for all failed transactions of yesterday due to that failure reason. The benchmarking is done with respect to the rules mentioned here.
   2. Current Week: This view provides the failure share/transaction share data for all failed transactions from Monday to yesterday this week due to that failure reason. The benchmarking is done with respect to the rules mentioned here.

      Note: If today is Monday then the current week data comprises of last week's data from Monday to Sunday.

   3. Current Month: This view provides the failure share/transaction share data for all failed transactions from 1st to yesterday this month due to that failure reason. The benchmarking is done with respect to the rules mentioned here.

      Note: If today is the 1st of a month then the current month data comprises of last month's data from 1st to 30th (or 2nd to 31st).

Payment Sources

This section helps you to find the top payment sources with respect to the share across all your transactions and the corresponding success rate performance for all these payment sources. Thus, it can be utilized to find the recent success rate performance of the payment sources which are of the highest importance.

1. Transaction Share: Transaction share is a doughnut chart that provides the breakup of the share of the top payment sources across all your transactions. These payment sources are organized in the chart in the descending order of the transaction share. The graph provides a breakup of a maximum of the top 5 payment sources while the rest of the payment sources have been clubbed in "Other". The only filter provided for this doughnut chart is:
   1. View: This filter decides the time period for which the "Transaction Share" chart will be created. Details on this filter have been provided here.
       
2. Success Rate Benchmark: This table provides the recent success rate performance of the top payment sources based on the transaction share across all your yesterday transactions.
   1. The payment sources are sorted in descending order based on the transaction share across your yesterday's transactions.
   2. The benchmarking rules for these payment sources across various time periods would be the same as listed here.
   3. The arrow color scheme would be the same as that of this section.
   4. Each of the below payment source if present in your top 5 payment sources (based on transaction share) have a corresponding arrow which when clicked would take you to the detailed analytics for that payment source: 
      • Credit Card 
      • Debit Card
      • Netbanking
      • UPI
      • Wallet

The Cashier Page Drop tab analyzes the recent increase/decrease in the trends of a customer dropping off on the cashier page without choosing the payment source to be used for completing the transaction. This section also provides you with the capability to find if the customer drop rate is higher/lower for a particular channel or payment flow.

Note: In case you do not have any customer drops on the cashier page for the past 6 months then this tab will not be visible.

Recent Drop Rates

This section helps you analyze the recent cashier page drop rate performance of all your transactions and benchmark it with the prior time periods. All drop rates and benchmarks have been rounded off to the nearest integer. Below are the details for various time periods: 

1. Yesterday: This view provides the drop rate data for all transactions of yesterday. The benchmarking is done with respect to the rules mentioned here.
2. Current Week: This view provides the drop rate data for all transactions from Monday to yesterday this week. The benchmarking is done with respect to the rules mentioned here.

   Note: If today is Monday then the current week data comprises of last week's data from Monday to Sunday.

3. Current Month: This view provides the drop rate data for all failed transactions from the 1st to yesterday of this month. The benchmarking is done with respect to the rules mentioned here.

   Note: If today is the1st of a month then the current month data comprises of last month's data from 1st to 30th (or 2nd to 31st).

Drop rate historic trend

This graph has been designed to showcase the customer drop rate trends of your transactions across the chosen time-period. The combination of filters could also be used to analyze if there is a particular set of parameters for which the customer drop rates are higher for your transactions. Subsequently, intelligent steps can be taken to reduce these customer drops to improve your overall payment experience.

You can see below the details on the filters provided for the graph: 

Payment Source level summary tab provides you with the capability to analyze your transaction performance for specific payment sources. Only those payment sources from which you have had transactions in the past 6 months are visible for selections.

You can see below the set of payment sources available as sub-tabs for selection: 

• Credit Card 
• Debit Card
• Netbanking
• UPI
• Wallet

Access to the Payment Source-specific tabs

The payment source-specific tabs can be accessed via the below two methods: 

1. Overall Summary tab: Use the below steps to access the payment source-specific tabs from Overall Summary:
   1. Go to the Payment Source level summary section.
   2. Visit the Recent Performance table.
   3. Among the listed payment sources click on the right arrow of the payment source for which you want to see the detailed analytics.
2. Payment Source Level Summary tab: The payment source can be chosen as a sub-tab on the Payment Source level summary tab.

Recent Performance

This section helps you to understand the recent success rate trends of your selected payment source at an overall level. It also helps you benchmark the payment source success rate across time periods to highlight if there is a sudden rise/dip in the performance of that paymode in recent times.

You can see below some salient pointers on this section: 

1. The benchmarking rules are as per the ones mentioned here.
2. The arrow schemes used here follow the same rules as given here.

Success Rate Historic Trend

This graph has been designed to showcase the success rate trends of your payment source-specific transactions across the chosen time-period and compare it with the average temporal trend and industry trends. Additionally, a set of filters have been provided to check if the performance is uniform or there are a set of parameters that have significantly lower success rates. Targeted steps can then be taken for improving the success rates for such transactions.

You can see below the set of filters available for the success rate historic trend graph: 

Failure Reasons Summary

This section helps you understand the overall top 5 reasons for the failure of your transactions specific to the chosen payment source. These failures may have happened by the user, bank, or Paytm. It also highlights the rise/fall of these failures in recent times as compared to the previous time period.

You can see below the list of filters available for this section: 

You can see below the set of graphs available in this section: 

1. Top Failure Reasons: This table highlights recent transaction/failure share of the top 5 failure reasons (based on failure share) for transactions specific to the chosen payment source that happened yesterday. It also compares the failure/transaction share of these failures with their corresponding values in previous time periods. All the other failure reasons are clubbed in the "Other" bucket.
   You can see below some salient pointers on the graph: 
   1. These failure reasons are sorted in descending order based on the failure share of these reasons in all your transactions that happened yesterday.
   2. The table highlights if the failure occurred due to the user, bank or Paytm (Wallet).
   3. The time periods used in the graph are the same as here.
   4. The benchmarking rules used are the same as mentioned in the Benchmarking pointer here.
   5. The arrow color scheme is the same as that used here.
2. Recommendations to reduce Authentication Failure: In case the top failure reasons for your credit card/debit card transactions have high shares of Drop out on the bank/PSP app and Incorrect OTP then this table would be available to you. This table would provide you with a set of Paytm offerings that can help you reduce the aforementioned failure occurrences and improve your customer experience. 
   
   You can see below the set of products recommended by Paytm in case you have high percentages of Drop out on the bank/PSP app and Incorrect OTP: 
   1. Paytm powered OTP Pages: This flow will enable you to complete card payments without a single redirection from our APP/Website minimizing customer drop-out failures.
   2. Auto-OTP capture via Assist: Among many things, Assist SDK will enable auto-capture during card transactions. This prevents the need for user shuffling between different APPs to get the transaction OTP, hence minimizing dropouts.
   3. OTP less payments: This flow removes the requirement of OTP authentications from the card transaction making the transaction ONE CLICK.
      
      The below metrics are provided for each of these Paytm offerings: 
      • Impact: The potential impact that the Paytm offering can have on the success rate of your credit/debit card transactions
      • Effort: The effort required Large, Medium, Low to integrate the solution into your current systems
         
3. Failure Share: This is a doughnut chart that highlights the breakup of failure share across the top 5 five failure reasons and others (which comprises of all the remaining failure reasons) in the selected time period for the chosen payment source. This doughnut chart would be available for only the below cases: 
   1. For payment sources other than credit card/debit card
   2. For debit card/credit card cases when the failure share of Drop out on bank/PSP app and Incorrect OTP is less than 10%

Historic Trend of Failures

This graph depicts the trend of transaction/failure for the selected failure reason across the chosen time period. It can be utilized to further drill down to the specific failure reason trends to find a sudden dip/rise in the failure/transaction share.

You can see below the available filters for the graph: