Understanding sales trends throughout the day starts with tracking sales by the hour. This summary may incorporate additional data indicators, useful for tracking the store's business performance.
Effortlessly observe how the sales rate changes for each hour your store is open. Compare current data with past time ranges, and use the reporting tool's functionalities to identify trends in key sales indicators.
The default configuration of the report provides data on general patterns of the store's financial operations by displaying columns such as the number of orders, gross sales, total sales, taxes, discounts, and returns.
Executive managers can use filters to tailor the sales data to their needs. For example, they might want to see the hour with the highest sales for the current month, track the hour with the lowest number of orders for the past year, or compare sales by the hour with previous periods. Such information can be useful for inventory planning and marketing purposes.
This summary provides a list of all orders placed within a specified date range, split by the days of the week. It can be used to get a high-level overview of daily sales trends.
The data it presents can answer questions such as:
You can expand this list of insights by using additional data columns and filters.
Use the data summary provided by the Mipler reporting app to stay informed about your store's key sales statistics, broken down by hours of the day.
Add additional columns to gain a detailed understanding of your store's business performance.
For example, you can determine which countries your customers come from and which hours of the day they most frequently make purchases. You can get this information for a default 30-day period or adjust the range to any other time period.
The summary provides information for each hour, such as:
Use these sections to understand the current financial status and fulfillment of orders within the selected date range.
The rundown on sales can be tracked through another data viewpoint if required. The installed store reporting plugin allows you to switch to other time periods. The report can be generated for a day of the week, week, year, quarter, or any other specific time frame.
In conjunction with the day of week sales report, a store manager can often use the following summaries:
However, you are not limited to splitting sales into the above time periods. Generate the report on sales based on other factors, like sales by customer group, to get more insights.
By default, the table with the information on occurred deals for every hour of the day comprises the following sections:
The user of this generated summary is totally free to exclude any of the existing columns from its default configuration or add several additional ones. Simply choose available columns from the list.
Here is how some of the key columns in the default report are calculated:
REFUNDS Returns: It is calculated through Refunds Total Gross Amount and Order Adjustments Total Amount data columns.
[REFUNDS Returns] = [REFUNDS Total Gross Amount] – [ORDER ADJUSTMENTS Total Amount]
ORDERS Net Sales: It is used to display what is left after the discounts and refunds are extracted from gross sales.
[ORDERS Net Sales] = [ORDERS Gross Sales] – [ORDERS Discounts] – [REFUNDS Returns]
ORDERS Shipping: Allows tracking the sums on order shipping.
[ORDERS Shipping] = [ORDERS Shipping amount] – [ORDER ADJUSTMENTS Total Shipping Amount]
ORDERS Tax: Depicts the sum of taxes excluding the taxes on the refunded items.
[ORDERS Tax] = [ORDERS Taxes] – [REFUND ITEMS Total Tax Amount]
ORDERS Total Sales: It is the final default column of the report, which sums net sales, shipping, and tax.
[ORDERS Total Sales] = [ORDERS Net Sales] + [ORDERS Shipping] + [ORDERS Tax]
You can get one more view on deals adjacent to the hour-by-hour report with metrics on deals configured by default. Utilizing varieties of the available data from the store database, you can acquire a clearer understanding of how well the business is performing in your store.
One of the simplest report variations and an easy way to glance at the business success is to compare a specific date range to a previous period.
Using filters and sorting options, you can get answers to some other questions regarding sales. Here are some examples of the report variations.
You can easily see the trends in the usage of payment infrastructure when generating the hourly sales summary. Add a SALES Gateway column in order to display such data.
Add a TRANSACTIONS Source Name to see the name of the transaction’s origin and add a TRANSACTIONS Status to see if the transaction was completed successfully.
You can easily see the sales data for each hour of the sale day with the data on customers' geographical distribution.
See what provinces, cities, and countries you have the most or least purchases for each hour during the day.
It is well known that existing customers cost less than attracting new ones for a store. Depending on the purchases each customer makes, they set their individual value for a store.
You can easily see the customer lifetime value with the CUSTOMERS CLV data column. Use it to monitor signs of shoppers' attrition in your store.
Gross margin is one of the parameters for the business performance, which shows how much financial funds the store retains. The higher this indicator is, the more capital is available to pay for other costs.
See the gross margin in percent by activating a corresponding column.
[ORDERS Gross Margin, %] = ([ORDERS Net Sales] - [ORDERS COGS]) ÷ [ORDERS Net Sales] × 100
The result is rounded to two numbers after the comma sign. If the calculation result is negative, the report shows zero value in the table.
The sales overview can be extended with the data columns on transactions. You can get such information as:
The total cost of ordered items in the order is calculated as:
[ORDER ITEMS Total Cost] = [ORDER ITEMS Quantity] × [INVENTORY ITEMS Cost]
A store can have both new and recurring customers, the latter being preferable. Merchants can easily see what types of customers buy in their stores with the ORDERS Customer Type column.
In case the date of the customer’s first order is equal to the order processing date, then the customer is considered a first-time buyer. Otherwise, they are assigned to a Returning type. If the report cannot detect the customer ID, it will display the Unknown value.
For each order, get the shipping price calculation:
[ORDER ITEMS Total Shipping Price] = [ORDERS Shipping Price] ÷ [ORDER FACTS Quantity] × [ORDER ITEMS Quantity]
Get the sum of total sales calculated as:
[[ORDERS Total Sales] = [ORDERS Net Sales] + [ORDERS Shipping] + [ORDERS Tax]
The ORDERS Net Sales are obtained as:
[[ORDERS Net Sales] = [ORDERS Gross Amount] - [ORDERS Discounts] - [REFUNDS Returns]
The ORDERS Shipping is obtained as:
[[ORDERS Shipping] = [ORDERS Shipping amount] - [ORDER ADJUSTMENTS Total Shipping Amount]
The ORDERS Shipping is obtained as:
[[ORDERS Tax] = [ORDERS Taxes] – [REFUND ITEMS Total Tax Amount]
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