Monthly Sales Revenue Report by Product Type Across Branches
This document provides a step-by-step guide to generating a monthly sales revenue report based on product types across multiple branches, allowing businesses to compare the sales performance of different product groups between branches.
Using Visionade and Table Grid as the data source, managers can easily identify which product types bring the highest revenue at each branch, monitor sales trends, and make informed decisions about inventory and product strategy to maximize profitability.
Introduction
Tracking revenue by product type and comparing performance across branches is essential for inventory planning, product strategy, and overall business growth across the entire store network.
With Visionade, sales data stored in Jira is transformed into visual reports on the Jira Dashboard, allowing managers to:
Identify which product types generate the highest revenue
Compare sales performance between branches by product category
Detect product types with high demand to adjust inventory or sales strategy for each store location
Invoices are recorded as Jira issues, with detailed product information stored inside a Table Grid like this:
Prerequisites
Before generating the report, ensure the following conditions are met:
Visionade is installed and accessible within your Jira environment.
User has Jira Admin permissions to configure data source and data set
User permissions allow access to Jira Dashboards.
Jira issues include sales information with columns: Project (branch/store), Invoice resolution date
Table Grid data with columns: Product type and Total
Post-condition
A dynamic monthly sales report by product type across branches is displayed on the Jira Dashboard.
Configured report is saved in Reports list.
Use Case Flow Diagram
Step-by-Step Implementation
1. Configure Jira Data Source
Actions | |
|---|---|
| 1 | Open Data Sources tab, click on Jira source |
| 2 | Click Select Dimensions button |
| 3 | Select dimensions and then click Save Selected |
| 4 | Click Index All Dimensions button to reindex the data of all selected dimensions, ensuring it is fully up to date. |
2. Configure Table Grid Source
Actions | |
|---|---|
| 1 | Open Data Sources tab, click on Table Grid source |
| 2 | Click Select on grid “Invoice”
|
| 3 | Click Select Dimensions button
|
| 4 | Select dimensions and then click Save Selected
|
| 5 | Click Index All Dimensions button to reindex the data of all selected dimensions, ensuring it is fully up to date.
|
3. Configure Data Set
Actions | |
|---|---|
| 1 | Open Data Sets tab, click Create Data Set button
|
| 2 | Enter “Sales Performance” for Data Set Name
|
| 3 | Select “Table Grid” in Select Data Sources section
|
| 4 | In Select Grid field, select grid “Invoice”
|
| 5 | Turn on Mapping with Jira toggle
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| 6 | In Select Dimensions section, select/deselect dimensions for both Local Jira and Table Grid based on your needs. |
| 7 | Enter JQL query to narrow down the data set that you want: Project in (HA,HAC,HD)Then click “Run Query” or “Preview” button to filter and preview data in Data Preview section
|
| 8 | Click Save to save data set configuration |
4. Configure October Sales Performance Report
Actions | |
|---|---|
| 1 | Open Reports tab, click Create Report button |
| 2 | Fill in Report Name and click Next button |
| 3 | In Table View tab, select data set “Sales Performance” that we have configured |
| 4 | Open Analytics & Pivot tab to start configuring report |
| 5 | Drag dimension Product Type to section Rows to view product types as row headers The dimension Issue Key was dragged into the Values section as a guide for users to start with Analytics & Pivot. You can remove it if you don’t need it. |
| 6 | Drag dimension Project to dimension Columns to view projects as column headers
|
| 7 | Drag dimension Total to section Values to view revenue in each field of the table Select Sum in Aggregation field |
| 8 | Drag the Project dimension to section Filters to filter the projects you want to report on (in case you have other stores in your Jira instance). Click on Project dimension to select filter condition Text contains and enter value “Hacom” to filter all projects whose names contain “Hacom”. |
| 9 | Drag dimension Resolution Date to section Filters to filter invoices (issues) which are resolved on October Click on Resolution Date dimension to select filter condition Is Between and enter value “2025-10-01” for the From value and “2025-10-31” for To value Use Date format: YYYY-MM-DD |
| 10 | Select Column Chart in section Visualization |
| 11 | Click Apply Config to generate report |
| 12 | Click “Save” to save report configuration |
5. Add October Sales Performance to Jira Dashboard
Actions | |
|---|---|
| 1 | On the Navigate sidebar, click + button of Dashboards section to create a new dashboard
|
| 2 | Fill in Name and click Save |
| 3 | Click Edit button to edit the dashboard Search “Visionade” to search gadget Click Add button on Visionade Report gadget |
| 4 | Select October Sales Performance Report |
| 5 | Click “Save Changes” to save changes on gadget |
| 6 | Click “Change layout” and select “One column” |
| 7 | Click Done to save dashboard |
6. Result
Report is displayed on Jira Dashboard.
This report helps managers easily identify key insights:
Top sales revenue by product type: Desktop PCs and Laptops generate the highest revenue across all branches.
Branch comparison: Eg. Hacom – HN generally outperforms other branches in Desktop PC sales.
Branch-specific demand patterns: Eg. Desktop PC sales are particularly strong at Hacom – HN, while Monitors and External SSDs show significantly lower performance.
With these insights, store managers can make more informed decisions on inventory planning, such as:
Increasing stock for high-demand products (e.g. Desktop PCs).
Redistributing stock from low-demand branches to high-demand ones (e.g. moving External SSDs from Hacom – HCM to Hacom – HN).
Re-strategizing or reducing low-performing items (e.g. External SSDs).
As a result, inventory distribution becomes more precise, excess stock is minimized, and overall branch-level performance improves.
Conclusion
By using Visionade with Table Grid, businesses gain clear visibility into revenue distribution by product type across branches. The report highlights top-performing categories and branch-specific demand patterns, enabling managers to make data-driven inventory decisions, prioritize key products, and optimize stock allocation to minimize overstock and enhance overall sales efficiency.