The Sales Analysis dashboard shows you how your business is performing right now: revenue, profitability, order patterns, discounting, fulfilment speed, and product mix in a single view. It is built on invoice-line-level transaction data, making it the most granular sales dataset in Analytics.
This is your go-to dashboard for answering "how is the business performing right now?" at both an overall level and across specific dimensions such as product group, warehouse, or customer. Unlike the segmentation dashboards that classify customers and products into tiers, Sales Analysis shows raw performance metrics; what is actually happening in your business day to day.
Review the Sales Analysis dashboard
KPI cards
Six headline metrics appear at the top of the dashboard, giving you an instant health check before you explore the charts and breakdowns below.
KPI | What it shows | What to watch for |
Revenue (invoice only) | Total invoiced revenue and gross profit with margin %. This is your top-line business performance number. | Margin declining while revenue holds steady indicates a pricing or cost issue that needs investigation. |
Avg. markup % | COGS vs profit ratio: how effectively you convert costs into revenue. | Declining markup suggests competitive pressure, discount creep, or rising costs not being passed on in pricing. |
Order count | Total orders, average orders per customer, and active customer count. | Falling order count with stable revenue means larger but fewer orders, a sign of customer concentration risk. A rising count with falling revenue means smaller orders. |
Avg. revenue per customer | Total revenue divided by active customer count. A useful benchmark for customer health. | A declining average suggests your customer base is growing with lower-value accounts, or that existing customers are spending less. |
Avg. order to ship | Average days from order placement to shipment, with order-to-invoice and invoice cycle detail. | Increasing ship times signal warehouse bottlenecks, production delays, or stock availability issues affecting fulfilment. |
High discount sales (>30%) | Count of sales with more than 30% discount off list price. Also shows negative-profit and low-margin transaction counts. | High numbers indicate aggressive discounting or pricing policy failures. Cross-reference with salesperson data to identify who is giving the deepest discounts. |
Charts
Revenue, profit, and avg. revenue per order
A monthly trend showing whether revenue and profit move together over time. A widening gap between the revenue and profit lines means margins are eroding even as sales grow. The average revenue per order line reveals whether individual order sizes are stable, growing, or shrinking; useful for spotting whether growth is coming from more orders or larger ones.
Customer orders and revenue
Monthly active customer count overlaid with average revenue per customer and average orders per customer. This reveals whether growth is coming from more customers, which is healthy diversification, or more spending per existing customer, which can indicate concentration risk.
Revenue per product group
A horizontal bar chart showing which product categories drive the most revenue. Quickly identifies your dominant categories and any long tail of low-revenue groups that may warrant a portfolio review.
Revenue per product
Individual product-level revenue bars, identifying your top-selling individual SKUs.
🤓 Tip: You can toggle between bar and line chart views using the icons in the top-left of each chart panel.
Using Copilot with Sales Analysis
Example prompts
Below are a few prompt examples for using Copilot with the Analytics' Sales Analysis dashboard
Prompt | What it returns |
"Show me all invoice lines with negative margin in the last six months" | Every loss-making transaction with customer, product, warehouse, and margin detail. Export for pricing review. |
"What is our average order-to-ship days by warehouse?" | Grouped by warehouse, immediately identifies which locations are slowest to fulfil. |
"Which salesperson has the highest average discount percentage?" | Surfaces pricing policy issues per sales representative, so you can target coaching or policy enforcement. |
"Show me products where the discount percentage exceeds 30%" | Filtered list of heavily discounted products for cross-referencing with Product ABC to check if key products are being over-discounted. |
Custom insights you can build
Discount abuse monitor
To build this insight, use the following metrics and filters:
Select Source: Unleashed_Sales_KPI.
Filter: High_discount_flag = 1, for the current quarter.
Group: by salesperson name.
Value: count of transactions.
This monitors which representatives give the deepest discounts, enabling pricing policy enforcement.
Margin erosion tracker
To build this insight, use the following metrics and filters:
Source: Unleashed_Sales_KPI.
Group: by invoice month.
Value: avg margin percentage.
Add a calculated field for revenue minus profit to trend margin over time and catch erosion before it impacts the bottom line.