Sales Trend Reports

The Sales Trend Report shows how your sales performance changes over time. By grouping transactions into daily, weekly, monthly, quarterly, or yearly periods, this report reveals patterns, seasonal trends, and growth trajectories that are not visible in a single-period snapshot.

How to Access

Open the Sales Trend Report from the main menu:

• Reports > Receivables > Sales > Sales by Time Period — opens with the Monthly preset selected
• Reports > Receivables > Sales > Average Ticket / Basket Analysis — opens with the Daily preset selected and focuses on average transaction metrics

Both menu entries open the same report form. You can switch between any preset at any time using the Preset dropdown.

Required Permission

You must have the RPT_VIEW_SALES permission to access this report. Super Admins and Location Admins have this permission by default.

Filters

The report provides the following filter controls along the top of the window:

After changing any filter, click Refresh or press F5 to reload the data.

Report Columns

The data grid displays the following columns:

Understanding the Five Presets

Daily

Each row represents one calendar day. This is the most granular view and is best for short date ranges (a week or two) where you want to see day-by-day patterns. Use this to spot which days of the week are busiest, identify slow days, or investigate a specific date.

Weekly

Each row represents one calendar week (Monday through Sunday). This is ideal for comparing performance week over week, especially for businesses with weekly promotional cycles or staffing patterns.

Monthly

Each row represents one calendar month. This is the most commonly used preset and is the default when opening from the Sales by Time Period menu entry. Monthly trends are useful for budgeting, comparing against targets, and identifying seasonal patterns.

Quarterly

Each row represents one fiscal quarter (Q1 = Jan-Mar, Q2 = Apr-Jun, Q3 = Jul-Sep, Q4 = Oct-Dec). Quarterly views are useful for high-level business reviews and board-level reporting where monthly detail is not needed.

Yearly

Each row represents one full calendar year. This preset is only useful when your date range spans multiple years. It provides a long-range growth perspective and is ideal for year-over-year comparisons.

The POS Only Filter

When the POS Only checkbox is checked, the report includes only transactions that originated at the point of sale register. This excludes:

• Manually created invoices
• Invoices created from work orders
• Invoices created via the invoice management screen

This filter is useful when you want to analyze strictly retail walk-in performance without service or back-office invoices affecting the numbers.

When POS Only is unchecked (the default), all completed invoice types are included in the totals.

How Time Period Grouping Works

The report groups transactions by the date the invoice was completed (closed). If a date range spans partial periods, those partial periods are still shown but may have lower totals than full periods. For example, if your date range starts on February 15 and you use the Monthly preset, the February row will only contain data from the 15th onward.

Keep this in mind when comparing the first and last periods in your date range against the periods in the middle.

Common Use Cases

1. Seasonal analysis — Set the date range to the past 12 months, select Monthly, and look for peaks and valleys that correspond to seasonal patterns in your industry
2. Day-of-week comparison — Set the date range to a single week, select Daily, and compare each day's performance to see your busiest and slowest days
3. Year-over-year growth — Set the date range to span two or more years, select Yearly, and compare Total Sales across rows to measure growth
4. Average ticket monitoring — Use the Daily preset for the past month to track whether your average ticket size is trending up or down
5. POS retail focus — Check POS Only and use Monthly to track strictly retail sales, excluding service invoices and manual entries
6. Basket size optimization — Monitor the Avg Items/Ticket column to evaluate whether upselling and cross-selling strategies are working

Tips

• Choose the right granularity — Daily works for days to weeks, Weekly for weeks to months, Monthly for months to a year, Quarterly and Yearly for multi-year spans
• Watch for partial periods — The first and last rows may represent partial time periods if your date range does not align with period boundaries
• Combine with Sales Analysis — Use the Sales Analysis Report to understand the composition of a specific period that stands out in the trend
• Export for charting — Export to CSV and create line charts in Excel or Google Sheets to visualize trends graphically
• Compare locations — Run the report once per location (or use All Locations) to compare how trends differ across stores
• Max/Min Ticket outliers — If Max Ticket is significantly higher than Avg Ticket, investigate that transaction to understand if it represents a bulk order or a pricing anomaly

Related Articles

• Sales Analysis Reports
• Top & Bottom Performer Reports
• Getting Started with Reports & Analytics