Analytics
Learn how to generate custom statistics for charts and reports.
Overview
The Monite analytics empowers users with real-time insights into their accounts payable processes. It provides aggregated data with detailed breakdowns, filterws, and metrics to help finance managers make data-driven decisions efficiently.
Roles and permissions
To access the analytics using an entity user token,
this user must have a role with the payables.read
permission.
If a partner-level token is used, no special permissions are needed.
Dimensions and metrics
When working with analytics, dimensions and metrics are fundamental concepts that define how data is structured and presented.
Dimensions
Dimensions are attributes or categories used to group, segment, or filter data. They provide the “context” for the data and are often non-numeric. In charts, dimensions appear as labels for categories or axes. Dimensions help users answer questions like:
- “How many payables were paid in Q3?"
- "Which counterpart contributed the most to revenue last year?”
Metrics
Metrics are quantitative measures used to calculate and display data values. They represent the “what” of the data and are always numerical. Metrics often appear as values or data points within a chart. Metrics allow users to evaluate performance, such as:
- “What was the total overdue amount last month?"
- "What is the average payment delay for supplier invoices?”
How they work together
Dimensions and metrics are interconnected. Dimensions provide the framework, while metrics fill that framework with measurable values. For example:
- Chart example: A bar chart showing “Average payment delay” (metric) broken down by “Month” (dimension).
- Table example: A data table showing “Payable Count” (metric) grouped by “Counterpart name” (dimension).
This combination ensures that users not only see the numbers but also understand the context, enabling better decision-making.
Retrieve aggregated analytics data
The GET /analytics/payables
endpoint retrieves the aggregated analytics results for the payables. This endpoint enables users to access summarised data for various use cases, such as generating reports, visualising trends, or exporting metrics for a specified period.
The request fields are explained below:
Check the GET /analytics/payables
endpoint for additional filters. You can also use any filters from GET /payables
.
As a response, we will return not the payables models, but rather the metric values in each dimension.
Example use cases
Here are some examples of aggregated results for specific use cases:
Average amount for payables of last week
Theese are the field values to get the average price of all payables from the last week:
metric
=total_amount
aggregation_function
=average
dimension
=null
- we want to extract just total as number without any breakdownscreated_at__gt
=01.11.2024
- or seven days ago
The response returns the total amount of payables:
Number of payables in different statuses created last week
The field values to get the number of payables by status from last week:
metric
=id
aggregation_function
=count
dimension
=status
created_at__gt
=07.10.2024
- or seven days ago
The example response shows 5 payables in the new
status and 11 in the waiting_for_approval
status:
Yearly sum of payables by counterpart
The field values to get the total sum of payables for 2024, broken down by counterpart, for example:
metric
=total_amount
aggregation_function
=sum
dimension
=counterpart_id
created_at__gt
=01.01.2024
The response shows the total amount of payables (metric_value
), split by counterpart IDs (dimension_value
):
Chart of payables currently awaiting payment (not cumulative) by creation date
The field values to get a chart of payable creation dates for payables currently awaiting for payment (not cumulative):
metric
=id
aggregation_function
=count
dimension
=created_at
date_dimension_breakdown
= ‘daily’status
= ‘waiting_to_be_paid`
The response contains each payable with their creation dates: