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Sales
Rashan avatar
Written by Rashan
Updated over 7 months ago

Mortar Reveal assists you in determining your most profitable time of year. Your sales data is broken down into quarterly, monthly, daily, and hourly sales. With this knowledge, the Mortar team develops marketing campaigns to increase customer engagement and sales both during and outside of key sales periods.

Average Hourly Sales

  • This graph depicts the average revenue generated at a specific hour!

  • When you move your cursor over the graph, a pop-up will appear with your sales ($) and the time (hour) they were made!

The horizontal axis denotes the time of day and is divided into 24 hours beginning at 12 a.m., while the vertical axis denotes the cost of sales made during that hour. Consider sending marketing communications during peak periods.

Average Daily Sales

  • This graph depicts the day of the week when your customers, on average, are purchasing your products online.

  • A pop-up box will appear while your cursor is over the graph, displaying your sales ($) and the day on which they were made!

Average Monthly Sales

  • This graph depicts the average monthly customer sales for the year.

  • A pop-up will appear while the cursor is over the graph that shows sales ($) for that month over the prior 12 months!

Yearly Sales by Quarter

  • This graph aids in analysing revenue from one yearly quarter to the next.

  • This metric provides a trend over time rather than just a few weeks to enable future planning for marketing activities!

  • While you hover your cursor over the graph, a pop-up box will appear showing you a breakdown of your quarterly sales ($) for the quarters of the year shown at the bottom of the graph!

Additionally, Mortar enables customers to export sales data for a selected time frame. By clicking "All Time," the consumer can apply a date filter if they desire. The following date ranges can be extracted as an excel by the customer:

  • All available data.

  • data for the previous seven days.

  • 30 days' worth of data.

  • Custom date range.

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