Table of Contents:
Filter Options in the Supplier Insights Dashboard
The Supplier Performance Dashboard includes several filters to help you refine the data you’re viewing, such as date ranges, account manager, region, and GST settings. By applying these filters, you can drill in further to the data you want to report on.
For a detailed explanation of each filter and how to use them, click here.
Key Metrics at a Glance
At the top of the dashboard, you can see four key metrics that summarise performance at a high level:
Total Sales ($725.70K): The total revenue generated during the selected period.
Active Customers (375): The number of customers who placed orders during the time frame.
Orders (1,198): The total number of orders processed.
Average Order Value ($605.76): The average value of each order placed.
Daily Sales Chart
This bar chart displays daily sales figures over a selected time frame. It shows the total cost sum (revenue) for each day, helping you track daily sales trends and identify peak sales days.
Each bar represents a single day, and the height of the bar indicates the sales total for that day.
The x-axis represents the delivery date, while the y-axis shows the total sales value.
Product Category Penetration
This chart breaks down how many customers have purchased from each category.
The x-axis displays the product category names, such as Coffee Roasters, Dairy, Tea, and more.
The y-axis represents the number of customers who purchased products from these categories.
Categories with higher customer engagement are placed on the left, indicating higher popularity.
Sales Performance Over Time (Hourly)
The final section of the dashboard shows the cumulative sales performance across different time frames:
Today, Yesterday, the last 7 days, and the last 28 days.
The line chart plots the running total of sales by hour, starting from 00:00 to 24:00.
Different lines represent different time frames:
Today (blue line)
Yesterday (orange line)
Last 7 days (purple line)
Last 28 days (red line)
This graph helps identify sales patterns throughout the day, allowing you to see when peak sales typically occur.
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