Customize and filter in Analytics
Analytics helps you analyze sales figures, identify trends and make data-driven decisions to optimize your business. Below we go through the features available for you to filter your data.
Choose between Invoice Date and Payment Date
You can choose to sort the data based on when the invoice was issued (Issue Date) or when it was paid (Payment Date).
How do you do it?
Click the Invoice Date or Payment Date button to switch between the options.
Use the Date Picker for Time Interval
With the date picker, you can select a specific time interval to analyze.
How do you do it?
Click the date picker (next to Bong Time/Payment Time).
Select a predefined interval such as "Today," "Yesterday," "This Week," "Last Week," "Last 30 Days," "This Month," "Last Month," or "Year-to-Date."
For a custom interval:
Scroll to the first day and click.
Scroll to the last day and click again to set the range.
Set the Time Frame with the Time Selector
You can specify specific times for your date range or use a daily 24-hour range.
How do you do it?
Under the time selector, select the "From" and "To" times (e.g., 00:00 - 23:00).
The "From" time applies to the first day, and the "To" time applies to the last day of the range.
Check "Fixed TIME" if you want to use the times as a daily interval for all days in the period.
Tap "+" to save a predefined time frame and share it with others or switch between saved settings.
Select Sales Locations
You can filter the data for specific sales locations if you have multiple ones.
How do you do this?
You’ll find the location option to the right of the Time Selector.
Uncheck the locations you don’t want to include (by default, all are selected).
Click “Save” to update the data.
Advanced Options
With advanced filters, you can sort and analyze data in depth.
How do you do it?
Click “Advanced.”
Select “View as” and sort the data by Staff, Payment Method, or Outlet (Point of Sale).
Add a filter under “Filter By” and choose between Staff, Payment Method, Source, Product Category, or Product.
Click the gray selector that appears (e.g., "Product" or "Payment Methods") to specify details, such as which products or payment methods to include.
Compare Data with the Compare Button
You can compare your current data with previous periods.
How do you do this?
Click the Compare button.
Select an option under “Compare with”:
"Previous date range".
"Same period, previous year".
"Specific date range" and enter the desired range.
Save/Load Report with the Cloud Icon
You can save the report and share the settings with other users.
How do you do this? - Save
Click the cloud icon.
Click “Save current report”
Give it a name, check “Share with all users” if you want to make it shared
Click “Save”
How do you do it? - Load
Click the cloud icon.
Select a shared report under “Shared Reports” or one of your own under “My Saved Reports”
Export the report
You can export the data for your own use.
How do you do it?
Click the download icon.
Select format: CSV or PDF.
Download the file to your device by clicking “Download Report.”
Discover the Features of Each Tab in Ancon Analytics
Sales
Sales gives you a clear overview of your sales data. Here you can analyze sales, discounts, refunds, tax rates, and tips.
The Sales tab presents data on:
Three graphs showing sales trends:
Sales over time (hour, day, week, month, or year).
Sales by day of the week.
Sales by time of day.
Total sales over a selected time period.
Discounts, refunds, tax rates, and tips broken down for analysis.
Trends
Trends allow you to analyze sales trends over different time periods using three graphs: Day, Week, and Year. Each graph lets you compare sales data with previous periods or specific dates.
The Trends tab helps you:
Compare sales over time to identify patterns and trends.
Analyze how sales are trending daily, weekly, or annually.
Compare current sales with previous periods, such as the same day last year or the previous week.
The three graphs are:
Day: Sales for a specific day, compared to other days:
Same day, previous week
Same day, previous year
Specific date
Week: Sales for a week, compared to other weeks.
Last week
Same week, previous year
Specific date range
Year: Sales for one year, compared to other years.
Previous year
Any sales year
Products
Products lets you analyze sales data for specific products or groups of products. You can sort, compare, and visualize data to gain insights into which products are performing best, their margins, and other key metrics.
Understanding the graph
What does the graph show? The graph displays sales data for the selected products over the specified time period, allowing you to compare their performance.
Customize view:
Choose between Order Date (when the order was placed) or Payment Date (when the payment was made) to change how the data is presented.
Customize the time interval in the graph (e.g., daily, weekly) if available.
Colors: Each product is assigned a unique color in the graph. You can see which color corresponds to which product in the list below
Tip: Hover your mouse over the graph to see exact sales figures for a specific product and time.
Analyze key metrics
Below the graph, a table displays the following key metrics for all selected products within the selected period:
Average net price: Average sales price per product (excl. VAT).
Cost of goods sold: Total cost of raw materials for the products sold.
Number of products: Total number of units sold.
Average profit margin: Average profit margin per product.
Profit margin ratio: The ratio of profit to sales (in percent).
Total sales: Total sales for the period (excluding VAT).
Tip: Use these key figures to identify which products are most profitable or have the highest cost of raw materials.
Product list
Below the key figures, a list of all selected products is displayed.
The following details are displayed for each product:
Product category: The category to which the product belongs (e.g., beverages, food).
Average net price: Average price per unit sold (excl. VAT).
Cost of Goods Sold: Cost of raw materials per product.
Number sold: Number of units of the product sold.
Average margin: The profit margin for the product.
Profit margin ratio: The ratio of profit to sales for the product.
Sales excl. VAT: Total sales for the product (excl. VAT).
Customize the graph:
Select or deselect products in the list to show or hide them in the graph.
Product Groups
Product groups allow you to analyze sales data at the product group level, for example, for categories such as food, beverages, or desserts. This feature is similar to Products, but focuses on groups of products rather than individual items.
The Product Groups tab helps you:
Analyze sales by product group within a selected time period.
Compare product groups in a graph to view their sales trends.
Review key metrics such as number of units sold, total discounts, and net sales per product group.
Option Groups
Option Groups lets you analyze sales data for Option Groups, such as categories like sauces, beverages, or doneness. The feature is similar to Product Groups/Products, but focuses on option groups instead of individual items.
The Option Groups tab helps you:
Analyze sales by option group and associated options within a selected time period.
Compare option groups in a graph to view their sales trends.
Review key metrics such as number of units sold and sales per option group and/or option.
Staff
Provides an overview of staff performance, such as sales per employee, tips, and average check, to support team management.
A graph visualizing the performance of selected staff members, such as sales trends over time.
Summary key metrics for the entire period: Total Sales, Discounts, Repurchases, EXCL VAT, Tips, Number of Sales, Average Check, Hours Worked, and Sales/Hour.
A list of employees with detailed columns: Name, Sales, Discounts, Repurchases, EXCL. VAT, Tips, Number of Sales, and Average Check.
Work Hours vs. Sales*
Working Hours vs. Sales helps you compare hours worked with sales to optimize scheduling and keep track of costs. This is a perfect tool for ensuring that staffing levels match sales levels in your business.
*What is required to use the “Work Hours vs. Sales” tab?
To view data in this tab, you need an active integration with a personnel system, such as Personalkollen. The integration automatically retrieves staff hours, which are then compared with your sales figures for the selected period.
What does the tab show?
You get a clear overview of key metrics for the period, including:
Percentage of net sales attributed to working hours: What portion of sales is attributed to working hours.
Excl. VAT: Sales excluding VAT to provide a clearer picture.
Personnel costs: Total personnel costs during the period.
Regular: Cost of regular working hours.
OB1: Cost of overtime category 1 (e.g., evenings).
OB2: Cost of overtime category 2 (e.g., weekends or holidays).
Customers
Customers lets you review sales broken down by guest, similar to how you analyze products, product groups, and add-on groups. This tool helps you understand customer behavior, identify loyal guests, and optimize your service based on data
What does the Customers tab show?
A colored graph that visualizes sales per guest, where different colors represent different guests or groups for an easy overview.
A list of columns:
Guest Name: Name of the guest or customer (if registered).
Number of Guests: Total number of guests associated with the sales.
Sales EXCL. Tax: Total sales per guest excluding tax for the selected period.
Forecast
Forecast helps you create predictions for future sales based on historical data. Here you can compare actual figures with set goals, view deviations, and optimize costs for staff and ingredients. It’s a great tool for better budgeting and planning, especially for restaurants or stores with seasonal variations. If data is missing (e.g., for certain outlets), a warning will appear—click "Enter Data" to fill in the information.
Handling Missing Sales Data in the Forecast
If an outlet is missing sales data in the Forecast tab, click "Enter sales data" to add information. Follow these steps:
Select Outlet Select the outlet that is missing data.
Select Initial Data Set
Use past sales figures: Select a previous outlet and year. Manually fill in any gaps in the data if there are any.
Enter sales figures manually: Enter amounts for each day (Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday). Use "Advanced" to save only certain months (e.g., January, March).
Set Initial Goals (Step 3) Set goals:
Sales Target %: Total or per product group (via Advanced).
Labor Cost %: Target as a percentage of net sales.
Raw Material Cost %: Target as a percentage of net sales.
Once the data is entered, the forecast is automatically updated to provide a complete overview.
What does the Forecast tab show?
A line graph at the top that visualizes trends over time (e.g., months):
Net Sales: Actual net sales (blue line).
Target Net Sales: Target net sales (orange line).
Labour Cost: Actual labour cost (orange dotted line).
Target Labor Cost: Target labor cost (yellow line).
Cost of Goods: Actual cost of goods (yellow dotted line).
Target Cost of Goods: Target cost of goods (yellow line). Hover over the points for exact monthly values.
Sales targets and advanced settings below the graph: Here you can set targets for sales, labor costs, and raw material costs as a percentage of net sales. Use "Advanced" to specify targets by product group (e.g., 30% for food, 20% for beverages).
List by outlet: A table summarizing performance for each store or unit:
Excl. VAT: Sales excluding VAT.
Target: Set sales target.
Variance: Difference between actual and target sales.
Variance %: Variance as a percentage.
Labor costs: Total labor costs.
Percentage of net sales: Labor costs as a percentage of sales.
Target as a percentage of net sales: Target for labor costs in %.
Variance and Variance % for labor costs.
Raw material cost: Total raw material cost.
Percentage of net sales: Raw material costs as a percentage of sales.
Target as a percentage of net sales: Target for raw material cost in %.
Variance and Variance % for raw material cost. Example: If an outlet has 47,773 SEK in sales excl. VAT and a 0% variance, it is highlighted in green to indicate a positive trend.
Calendar overview at the bottom: A calendar view showing daily values for each month.
Gray numbers: Actual values (e.g., daily sales).
Under each day: A red or green number indicating deviation (red for negative, green for positive). Click on months to zoom in and view daily details.
Outlet Overview*
Outlet Overview is perfect for customers with multiple sales locations (e.g., stores or restaurants in a chain). Here you get a summary table with all your units as rows, so you can easily compare performance metrics such as total sales, number of transactions, or costs. You can add up to 6 custom columns with filters to tailor the view. *Only available if you have more than one point of sale in your Tenant.
What does the Outlet Overview tab show?
A table with all your outlets as rows. Each row displays basic data such as the name of the outlet (e.g., "Pub à la William," "NewOutlet").
Ability to add columns with calculated values, such as total sales, average per transaction, or cost of goods sold.
How do you create filters/columns?
Add columns for data Click the "+" next to "New Column" to create a new column (up to 6).
Select Base Filter: Start with "Total Sales," "Product," "Product Group," "Payment Method," or "Staff."
Add Order Type (if relevant): Select "Dine-in," "Takeout," or similar.
Add Platform: Select "Ancon Order App (AOA)", "Ancon Order Web (AOW)", "POS", or "Express".
If "POS" is selected: Specify individual POS terminals or POS groups.
Select Function (if the base filter is not Total Sales): "Total," "Quantity," "Average," "Cost of Goods," "% Cost of Goods."
Click "Available Filter" to save. The column is updated with calculated values per outlet.
Create combined filters Click "Add Filter" in the column settings to build advanced combinations.
Example: Filter "Total Sales" by "Product Group: Beverages" + "Platform: AOA" + "Function: Total".
Use the dropdown menus to combine—perfect for viewing sales of specific products via the app on a particular device.
Export data Click the download icon to save as a CSV or PDF and share with your team.