Because analyzing long lists of transactions can be cumbersome, our Statistics area’s filters and grouping options give you high-performance access to our database so that you can rapidly analyze the data at different angles to detect patterns or errors. And from your statistics results, you can use shortcuts to jump over into sub detailed lists of transactions, saving you lots of time and reducing your list to the real transactions of interest.
You can save your custom search settings so that you do not have to set up all your filters again the next time you log in. Once saved, these become your “Pre-defined” StatisticsDado que analizar largas listas de transacciones puede ser complicado, los filtros y las opciones de agrupación de nuestra área de Estadísticas le brindan acceso de alto rendimiento a nuestra base de datos para que pueda analizar rápidamente los datos desde diferentes ángulos para detectar patrones o errores. Y a partir de los resultados de sus estadísticas, puede usar accesos directos para pasar a listas de transacciones subdetalladas, lo que le ahorrará mucho tiempo y reducirá su lista a las transacciones reales de interés.
Puede guardar sus configuraciones de búsqueda personalizadas para no tener que configurar todos sus filtros nuevamente la próxima vez que inicie sesión. Una vez guardadas, estas se convierten en sus Estadísticas "Pre-definidas".
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Controls
You have the ability to control how your Statistics appear, what data is shown and for when.
Layout
The most important fields concerning the layout of your output are ‘Display’ and ‘Output mode’.
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Grouping
Grouping your statistics results helps you break your output up into smaller chunks:
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Example
Let’s look at an example in which grouping helps us use our statistics output intelligently.
We want to view the acceptance rates for our e-commerce business last month. But more specifically, we want to see how we fared among the different card issuers, and if the level of card made a difference. Therefore, we set our grouping levels accordingly:
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And now we can see the conversion ratio for each card-issuing bank. For this bank, we see that we perform better with the higher-level card:
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For the next bank, compared to the 50% acceptance seen above, we performed a bit better with the Classic level card:
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We could also compare refund success rate, the number of chargebacks coming from each issuer, our rebill success rate among the issuers, or even see which issuer most of our fraud alerts are coming from. And here we could also check if the card level has anything to do with it:
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Controles
Tiene la capacidad de controlar cómo aparecen sus Estadísticas, qué datos se muestran y cuándo
Distribución
Los campos más importantes relacionados con la distribución de sus datos son "Mostrar" y "Modo de salida".
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Agrupamiento
Agrupar los resultados de las estadísticas le ayuda a dividir el resultado en fragmentos más pequeños:
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Ejemplo
Veamos un ejemplo en el que la agrupación nos ayuda a utilizar nuestro resultado de estadísticas de forma inteligente.
Queremos ver las tasas de aceptación de nuestro negocio de comercio electrónico el mes pasado. Pero, más específicamente, queremos ver cómo nos fue entre los diferentes emisores de tarjetas y si el nivel de la tarjeta marcó una diferencia. Por lo tanto, establecemos nuestros niveles de agrupamiento en consecuencia:
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Y ahora podemos ver la tasa de conversión para cada banco emisor de tarjetas. En el caso de este banco, vemos que obtenemos mejores resultados con la tarjeta de nivel superior:
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En el caso del siguiente banco, en comparación con el 50 % de aceptación que se observó anteriormente, obtenemos un poco más de resultados con la tarjeta de nivel Classic:
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También podemos comparar la tasa de éxito de los reembolsos, la cantidad de contracargos que provienen de cada emisor, nuestra tasa de éxito de refacturación entre los emisores o incluso ver de qué emisor provienen la mayoría de nuestras alertas de fraude. Y aquí también podemos verificar si el nivel de la tarjeta tiene algo que ver:
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Además, si tenemos cuentas comerciales con más de un banco adquirente, podríamos comparar los resultados de estas estadísticas en términos de adquirente:
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We could then see which acquirer does better (or worse) with a given card issuer:
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Uncovering these type of statistics could help us determine new transaction routing rules that could be implemented in order to make our e-commerce business more successful.
Dates
Next, controlling the time period for which you want us to compute your data is also a major control:
The ‘Start’ date field is auto-filled to a week prior but you can change it via the calendar
Next to the Start date field you’ll find a switch. Use it to toggle the end date limit between a period of time or a specific stop date:
Finally, the ‘Unit’ drop-down list lets you choose the granularity of your statistical output: you can aggregate your data into chunks of one hour, one day, one week or one month.
Period details, Empty periods
If you just need to see the total statistics for your time period, and you don’t want to see them for every day, hour or week within said period, then un-check the ‘Display period details’ button:
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This button lets us visualize days, hours, or weeks etc., where there have been no transactions:
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Viewing data from a different perspective
Finally, the ‘Time zone' and ’Date type' fields allow us to look at our transaction data from the viewpoint of another time zone or type of date. For time zone, the transaction data will appear time-stamped in the time zone you select. For date type:
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‘Creation date’, the default selection, will display your transactions statistics based on the dates they were created in our system
‘Value date’: currently not available for use
‘Operation date’: This option shows you the real transaction date. This can be helpful when viewing frauds, for example, because when the frauds actually occurred is more important than when they appeared in our system
'Reconciliation date': currently not available for use
Viewing Statistics
To view a set of statistics on your transaction types:
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Tip: Click the Download button to create an Excel file of the displayed output. |
Drilling down to the transactions comprising a set of statistics
From a computed set of statistics, you can then drill down to the specific transactions for that set. In fact, there are two ways to do this:
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Another option, which lets you view an even smaller number of transactions, is to click the date or the “Total” links that appear in blue:
In the example above, clicking the first link would take us to the transactions in US Dollar for a specific date in our statistics table. The second link would show us ALL the transactions from our statistics set that were made in US Dollar.
Pre-defined Statistics
If you generate a view that you like, you can save the same criteria for your next login.
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