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Retail Analytics - Sales Dashboard
Retail Analytics - Sales Dashboard

Usage best practices for the Retail Analytics Sales Dashboard

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Written by Treez Support
Updated over a month ago

The Sales Dashboard in Treez Retail Analytics provides a comprehensive overview of your dispensary’s sales performance. It allows retailers to monitor key sales metrics, compare performance over time, and analyze sales by brand, product type, revenue source, order channel, and payment method. This dashboard can be customized by date range, stores, and order channels through the Control Panel.

Log into the Latest Version of Treez and navigate to Retail Analytics > Sales > Sales Dashboard.

Use the Date Range control to determine the sales days you'd like to include in your analysis. By default, this is set to the last 30 days of sales.

Sales Performance Overview

This section displays aggregate data for the selected date range, stores, and order channels:

  • Total Transactions: The number of completed sales transactions.

  • Units Sold: Total number of units sold during the selected period.

  • Gross Sales: The total value of all sales before discounts and returns.

  • Total Discounts: Total value of discounts applied during the sales period.

  • Total Returns: Net Sales value of all product returns.

  • Net Sales: Gross Sales minus Discounts and Returns.

  • Taxes: Total taxes collected from sales.

  • Gross Receipts: Total receipt amount from the completed sales transactions. Net Sales plus Taxes.

  • Cost of Goods Sold (COGS): The cost associated with the products sold, derived from the base cost of the units on the Invoice from when the products were purchased. This excludes any excise tax paid to Distributors (relevant for California customers, prior to Jan 1, 2023).

  • Gross Income: Net Sales minus COGS.

  • Average Order Value: The average Gross Receipts value of each sale.

  • Average Order Profit: The average Gross Profit from each sale.

  • Average Basket Size: The average number of units sold from each sale.

  • Average Customer Wait Time: For in-store purchases, this is the average time between check-in and ticket creation.

  • Average Transaction Time: For in-store purchases, this is the average time between ticket creation and ticket completion.

  • Average Customer Time in Store: For in-store purchases, this is the average time between check-in and ticket completion.

  • Gross Margin Percent: The percentage of Net Sales that is Gross Profit. (Net Sales minus Cost divided by Net Sales)

  • Average Discount Percent: The percentage of Gross Sales that are Discounted (Discounts divided by Gross Sales)

Using Period-over-period controls in the Sales Performance Overview

Users can select a period-over-period option under the date control to see trends for each KPI listed in the Sales Performance Overview.

First, select the Period-over-period option for your analysis (e.g. Last 7 Days). You'll now see trend lines added to each KPI card. The value of each KPI card now contains the last 7 days of data with a comparison to the previous 7 days. The number of periods shown on the trend line is based on the amount of data selected in the Date Range filter.

If the data on your KPI cards seems incomplete, it is likely because the Date Range selected is not set to include the entire period and the entire prior period.

For example, if I want to compare my Net Sales for this quarter over the previous quarter, make sure the date range is set to start at the beginning of the previous

quarter.

Pro tip 💡
Period-over-period comparisons are relative to the last date in the date range. For example, if a user wants to compare Q2, 2024 to Q1, 2024 and show the last 4 quarters on the trend line, they will set the Date Range filter to 7/1/2023 - 6/30/2024 and select the Period-over-period option to Quarter.

Sales by Store

The Sales by Store table contains store-by-store breakdowns of sales performance over the selected period. Clicking the plus button next to the Store name allows you to drill into the Week-by-Week performance over the selected period. From there, users can drill in further to Daily sales totals.

Sales Over Time

This visual can display trends over time (daily, weekly, monthly) based on a selected View Metric and the selected date range. For multiple stores, this visual will show each store's performance on its own line for easy comparison.

The following metrics can be selected for Analysis:

  • Average Order Profit

  • Average Order Value

  • Gross Receipts

  • Gross Sales

  • Net Sales

  • Returns

  • Taxes

  • Total Costs

  • Total Costs without Excise

  • Total Customers

  • Total Transactions (default)

  • Units Sold

Revenue Breakdown

The Revenue Breakdown allows you to dive deeper into your sales by selecting a revenue metric (e.g., Net Sales) and breaking it down by Brand, Product Type, Revenue Source, and Order Channel. This provides insights into which products or brands are driving the most sales.

The first step is to select a Revenue Metric to analyze, and the following visuals will help you understand the drivers of success for that metric, whether it be the types of products or the sources of orders. By default, this is set to Net Sales.

Revenue Breakdown by Brand

For the selected revenue metric, this table will show the most popular Brands over the selected date range. Users are able to see the % of the total sales that can be attributed to products of a given brand, as well as the costs and margins associated to these sales.

High concentrations of sales tied to brands with higher gross margins will lead to more profit. The Average Cost of each brand is the average unit cost for each product sold over the selected date range. These two metrics can be used to determine if there's a case to be made to increase prices to improve margins, or if there could be an opportunity to negotiate for better wholesale pricing agreements with vendors.

Revenue Breakdown by Product Type

For the selected revenue metric, this visual will show the breakdown of sales across the various product types in a retailer's assortment. It is important to ensure that a breakdown of current inventory by product type (available in the Current Inventory dashboard) is generally consistent with the sales volume by product type.

To see which Product Sub Types are most popular in a given category, click on a Product Type in the legend of the visual and click "Drill down to Product Sub Type". Or, to see which Product Sub Types are most popular across the board, click anywhere on the visual to display the visual options. Then click the down arrow in the upper-right hand corner to "Drill down from Product Type" across the entire chart.

Revenue Breakdown by Revenue Source

A Revenue Source in Treez is the source of orders that come from outside Ecommerce solutions, including Treez Ecommerce. This is a useful way to see whether spend on marketplace solutions like Weedmaps is delivering the volume and quality of orders you would expect.

Revenue Breakdown by Order Channel

This visual is used to see the high-level breakdown of sales across the various methods of ordering, regardless of which source the sale came from. This is a useful way to see how channels like Delivery or Kiosks (Express orders) are impacting overall sales.

Payments Analysis

Payment Trends

Analyze customer payment patterns to see which payment methods lead to higher order values or understand payment adoption over the last 6 months by analyzing the count of customers, transactions, or payment utilization percentage (percentage of receipts paid by a given payment type).

To compare two payment types, select the payment types from the list of Payment Types on the left-hand side of the visual. Ensure the "Split Out Payment Types" dropdown is set to "Split Out Payment Types".

To compare a payment type to all others (i.e. ACH Payments compared to every other payment type), select "Group Payment Types Together" option in the "Split Out Payment Types" dropdown and then click the Payment type you're interested in within the payment types list.

To re-set any selections, click the "Reset" button on the lower left-hand side of the visual.

% of Gross Receipts by Payment Type

This visual serves as a breakdown of total receipts paid by payment type.

Customer Utilization of Payment Types by Order Channel

This visual serves as a breakdown of the number of customers leveraging different Payment Types across Order Channels. Hovering over the bars on the chart will allow you to compare Customer Counts and Average Order Values for different payment types across each Order Channel.

Order Channel Analysis

View patterns of order frequency and order value trends by hour, by hour for each day in the selected date range, or by hour for each weekday. We suggest using the Order Channel filter in the Control Panel to understand trends for different channels to help staff front of house and fulfillment adequately.

Average Number of Orders by Hour

Across the selected date range, this is the average number of orders per hour along with the average order value by hour. If the average order value dips when sales volume increases, it can be an indication that the customer experience may be impacted negatively due to employee bandwidth or a lack of sellable inventory for high demand products.

Daily Order Volume by Hour

This visual contains a heatmap for spikes of increased order volume for each day in the selected date range. This can be used to understand how promotional events or increases in traffic due to external events (i.e. concert, or sporting event) may have led to spikes in order volume. This can be used to inform staffing decisions around similar events in the future.

Order Volume by Hour by Weekday

This visual contains a heatmap for spikes of increased order volume across the weekdays in the selected date range. This can be used to understand the variance in order volume across weekdays vs. weekends to drive staffing decisions or promotional strategies to increase volume during slower periods.

Customizing Your View

The dashboard includes filters for adjusting your view:

Date Range: Select any custom date range to analyze sales performance.

Stores: Filter the data to view sales for specific stores.

Order Channels: Focus on specific order channels, such as in-store sales or online orders.

For detailed metric definitions, visit the Retail Analytics Glossary.

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