{% extends "layouts/base.html" %} {% block title %} Overall {% endblock %} {% block stylesheets %}{% endblock stylesheets %} {% block content %}

Customer Analytics

Dimension selection
  • Orders - Revenue - Visitors - Discount
    Orders; Number of purchase count Revenue; Total Purchase Amount Visitors; Total Unique Visitors Count Discount; Total Discount Amount (Optional)
  • Daily Orders
    Total Number of Success Purchase Transaction per day.
  • Customer Journey
    Customers Journey Calculation; 1. Calculate average Hour difference from Download to 1st orders. 2 . Calculate average order count 3 .For each calculated average orders, calculate the average purchase amount, Example; average 2 orders, 1st orders avg 30.3£, 2nd orders avg 33.3£ Calculate average recent hours customers last order to a recent date.
  • Churn Rate
    First, the Frequency value is calculated for each user. Frequency is the time difference between each sequential order per customer. Each customer's last order date is not expected to be purchased before the average frequency day. In other words, Each customer is expected to order at most average frequency days before. A number of unique customers who have ordered between average frequency date before the current date and current date are engaged users Churn is engaged users divided by total unique ordered users.
  • Churn Rate Weekly
    It is calculated the same as the churn rate per week (each Monday of the week).
  • Top 10 Purchased Products
    The most preferred products for the customers. Each bar represents the total number of order per product.
  • Top 10 Purchased Categories
    The most preferred product categories for the customers. Each bar represents the total number of order per product category.
Orders {% if data_type['total_orders'] == False %} sample data {% endif %}

{{ kpis.total_orders }}

{% if kpis.since_last_week_orders[0] == '-' %} {{ kpis.since_last_week_orders }}% {% endif %} {% if kpis.since_last_week_orders[0] != '-' %} {{ kpis.since_last_week_orders }}% {% endif %} Since last week
Visitors {% if data_type['total_visitors'] == False %} sample data {% endif %}

{{ kpis.total_visitors }}

{% if kpis.since_last_week_total_visitors[0] == '-' %} {{ kpis.since_last_week_total_visitors }}% {% endif %} {% if kpis.since_last_week_total_visitors[0] != '-' %} {{ kpis.since_last_week_total_visitors }}% {% endif %} Since last week
Revenue {% if data_type['total_revenue'] == False %} sample data {% endif %}

{{ kpis.total_revenue }}

{% if kpis.since_last_week_revenue[0] == '-' %} {{ kpis.since_last_week_revenue }}% {% endif %} {% if kpis.since_last_week_revenue[0] != '-' %} {{ kpis.since_last_week_revenue }}% {% endif %} Since last week
Discount {% if data_type['total_discount'] == False %} sample data {% endif %}

{{ kpis.total_discount }}

{% if kpis.since_last_week_total_discount[0] == '-' %} {{ kpis.since_last_week_total_discount }}% {% endif %} {% if kpis.since_last_week_total_discount[0] != '-' %} {{ kpis.since_last_week_total_discount }}% {% endif %} Since last week
Daily Orders {% if data_type['daily_orders'] == False %} sample data {% endif %}
Churn Rate (%) {% if data_type['churn'] == False %} sample data {% endif %}
Churn Rate Weekly (%) {% if data_type['churn_weekly'] == False %} sample data {% endif %}
Customer Segmentation {% if data_type['segmentation'] == False %} sample data {% endif %}
Customer Journey {% if data_type['customer_journey'] == False %} sample data {% endif %}
Top 10 Purchased Products {% if data_type['most_ordered_products'] == False %} sample data {% endif %}
Top 10 Purchased Categories {% if data_type['most_ordered_categories'] == False %} sample data {% endif %}
{% endblock content %} {% block javascripts %} {% endblock javascripts %}