Sales Dashboard
In the Insights section, this Dashboard shows sales-related data, based on the activity generated in your online store (it is essential to previously connect your e-commerce as a Data source).
The dashboard has the option to filter by dates and shows:
General metrics on sales and recurrence
-Orders
-Customers
-Total revenue
-Average revenue per order
-Average revenue per customer
-Orders per period
-Revenue per period
-Frequent customers ratio: shows new sales over total orders
This is a very interesting piece of information since it answers the question: "of the total orders, how many have been made by old and new customers? And, of the total revenue, what percentage do orders from new and old customers represent?"
-New sales (of the selected period) compared to total sales:
Taking this information as an example, for a period of time, we can conclude:
*5 new customers have placed 5 orders for the first time, accounting a total of 212.25€. Their average cart is 42.45€ and coincides with the average billing of each customer.
*There are 8 customers who have made their second order. In total, they have made 9 orders (a customer has made 2 orders in the last 30 days). The total invoiced is 425.89€, the average cart is 47.32€ and the average spent by each customer is 53.24€
*5 customers have made their 5th or higher purchase. Between all of them, they have placed 47 new orders, representing an income of 2257.47€. The average cart is 48.03€ and on average, each customer has spent 451.49€
Sales attribution by channel and campaign
-Orders impacted by campaigns
-Sales attribution according to UTMs
-By source: Instasent and others, such as Instagram, etc.
-By medium: SMS and others, such as email, display, etc.
-By campaign: from highest to lowest sales and revenue.
Sales detail by product, geographical area, customer segments, demographics and timel
-Top Sales by customer tag
-Top sales by customer segment
-Top sales by category
-Top sales by country
-Top sales by state/region
-Top sales by city
-Sales by customer age
-Sales by customer gender
-Sales by customer language
-Sales by day of the week: the chart is displayed by days and below, the list is ordered from highest to lowest.
-Sales by time of day: shows at what hours the highest number of sales occurs.
This information is incredibly valuable for optimizing marketing strategies. Let's consider a scenario where we launch a promotion for a specific product. To achieve the best results, we recommend selecting that product exclusively, analyzing the day and time when it generates the highest sales, and scheduling the campaign accordingly.
For instance, based on the data, it would be ideal to schedule the campaign on a Tuesday, starting from 7 PM, as it aligns with the peak activity of your customers.
Moreover, you can combine this data with the insights available in the Audience and Segments section. By leveraging these insights, you can effectively target various customer groups such as current customers, lost customers, exclusive product customers, or even customers who have never purchased the product. This allows you to create highly personalized and targeted campaigns, resulting in significantly improved conversion rates.