Sales Report
Key metrics
The initial part of the sales report is intended to give the user a quick overview of their current sales. Here it is possible to find statistics covering the number of new customers that has been acquired during the selected timeframe, the AOV the number of orders and the total revenue.
Overall sales
Sometime all you need it the sales numbers for a specific time period aggregated on a daily level. This is exactly the purpose of graph covering the sales numbers. Here the user have the possibility to select whether the statistics should present revenue, number of orders or AOV.
Sales data aggregated on different time periods
Sales by weekday
Analyzing sales data on a weekday basis can provide valuable insights into the patterns of customer behavior and purchasing habits. Below are a couple of examples why you might want to consider to use this analysis:
Optimize marketing strategies: Knowing which days of the week are busiest can also help you optimize your marketing strategies. You can use this data to schedule promotional campaigns on days that typically see lower sales, or adjust your ad spending to target customers on the days when they are most likely to make a purchase.
Understand customer behavior: By analyzing sales data by weekday, you can gain insights into customer behavior patterns. For example, you might notice that customers tend to make larger purchases on weekends or that they are more likely to browse on weekdays. This information can help you adjust your website design and user experience to better meet your customers' needs.
Optimize inventory and fulfillment: By analyzing sales data by weekday, you can determine which days of the week are busiest and adjust your inventory and fulfillment processes accordingly. For example, if you notice that Mondays are consistently busy, you might want to schedule extra staff to handle order processing and shipping on those days.
Improve customer service: Understanding which days of the week are busiest can also help you anticipate and manage customer service needs. For example, you might want to schedule extra staff to handle customer inquiries and support on busier days, or adjust your support hours to better align with when customers are most active on your site.
Sales by hour
Aggregating sales data on an hourly basis will provide valuable insights into customer behavior and purchasing habits. Below are some use cases listed.
Understand trends and patterns: Looking at sales data over time can help you identify trends and patterns in customer behavior at different times of the day. For example, you might notice that sales tend to be higher in the morning or in the evening, or that certain products sell better at certain times of the day. By understanding these patterns, you can adjust your marketing and promotional strategies to better target your customers and drive sales.
Compare performance across different times: Aggregating sales data on an hourly basis also makes it easy to compare performance across different hours of the day. This can help you identify areas of improvement and adjust your sales and marketing strategies accordingly.
Optimize pricing and promotions: By understanding when customers are most likely to make a purchase, you can adjust your pricing and promotional strategies to better target those times. For example, you might offer a time-limited discount during a slow period of the day to encourage more purchases.
Identify peak sales hours: By aggregating sales data on an hourly basis, you can quickly see which hours of the day are the busiest and which are the slowest. This can help you plan staffing and inventory levels accordingly, so you can optimize your resources and avoid over or under-staffing during certain hours.
Overall, aggregating sales data on an daily or hourly basis can provide valuable insights into your ecommerce business and help you make data-driven decisions to improve sales and customer satisfaction.
Requirements
Active sources
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