IdoSell | Feed Octopus Help Center

1. Introduction

This documentation describes the process of collecting data from the IdoSell e-commerce platform within the Data Octopus application system. The integration includes obtaining data from several key endpoints, processing it, and storing it in BigQuery structures, which enables further analysis and use in business processes.

2. Data Sources

As part of the integration with the IdoSell platform, we collect data from the following endpoints:

Orders - https://idosell.readme.io/v3.0/reference/ordersordersgetpost-1
Products - https://idosell.readme.io/v3.0/reference/productsproductsget-1
Returns - https://idosell.readme.io/v3.0/reference/returnsreturnsget-1

3. Data Processing

Data collected from IdoSell goes through a multi-stage processing workflow that includes:

Retrieving raw data from the IdoSell API
Transforming data for business analytics
Enriching data with additional indicators and metrics
Storing data in target tables in BigQuery

4. Orders Table - Data Structure

The table contains combined data from the orders and products endpoints.

Column Name	Data Type	Description
client_id	STRING	Client identifier
order_id	INTEGER	Order identifier
has_invoice	BOOLEAN	Information whether an invoice was issued for the order
courier_name	STRING	Courier name
dropshipping_order_status	STRING	Dropshipping order status
order_add_date	DATE	Order creation date
order_add_year	INTEGER	Order creation year
order_add_month	INTEGER	Order creation month
order_add_week	INTEGER	Order creation week
order_dispatch_date	DATE	Order shipping date
order_source_type	STRING	Order source type
order_source_name	STRING	Order source name
order_source	STRING	Order source
shop_id	STRING	Shop identifier
stock_id	STRING	Warehouse identifier
order_status	STRING	Order status
order_base_billing_currency	STRING	Base billing currency of the order
currency_id	STRING	Currency identifier
purchase_date	DATE	Purchase date
basket_position	INTEGER	Position in the basket
bundle_id	STRING	Bundle identifier
id	STRING	Unique identifier
item_group_id	STRING	Product group identifier
size_id	STRING	Size identifier
product_size_code_external	STRING	External product size code
title	STRING	Product name
brand	STRING	Product brand
category_name	STRING	Category name
category_1	STRING	First category in the hierarchy
category_2	STRING	Second category in the hierarchy
category_3	STRING	Third category in the hierarchy
category_4	STRING	Fourth category in the hierarchy
category_5	STRING	Fifth category in the hierarchy
product_age_days	INTEGER	Product age in days
order_base_currency_order_products_cost	FLOAT	Cost of products in the order's base currency
billing_currency_rate	STRING	Billing currency exchange rate
order_currency_order_products_cost	FLOAT	Cost of products in the order currency
product_vat	STRING	Product VAT rate
product_quantity	FLOAT	Product quantity
product_order_price	FLOAT	Gross price of the product in the order
product_order_price_net	FLOAT	Net price of the product in the order
gross_revenue	FLOAT	Gross revenue
net_revenue	FLOAT	Net revenue
product_order_price_base_currency	FLOAT	Gross price of the product in the base currency
product_order_price_net_base_currency	FLOAT	Net price of the product in the base currency
client_delivery_address_street	STRING	Street of the client's delivery address
client_delivery_address_city	STRING	City of the client's delivery address
client_delivery_address_zip_code	STRING	Postal code of the client's delivery address
client_delivery_address_country	STRING	Country of the client's delivery address
client_delivery_address_country_id	STRING	Country identifier of the client's delivery address
client_delivery_address_type	STRING	Type of the client's delivery address

5. Products Table - Data Structure

The table contains data that is processed from the products endpoint.

Column Name	Data Type	Description
id	STRING	Unique product identifier
item_group_id	STRING	Product group identifier
product_is_deleted	STRING	Information whether the product has been deleted
product_is_visible	STRING	Information whether the product is visible
size	STRING	Product size
title	STRING	Product name
brand	STRING	Product brand
category_name	STRING	Product category name
category_path	STRING	Product category path
category_1	STRING	First category in the hierarchy
category_2	STRING	Second category in the hierarchy
category_3	STRING	Third category in the hierarchy
category_4	STRING	Fourth category in the hierarchy
category_5	STRING	Fifth category in the hierarchy
product_minimal_price	FLOAT	Minimum product price
product_wholesale_price	FLOAT	Wholesale product price
product_retail_price	FLOAT	Retail product price
product_purchase_price_net_last	FLOAT	Last net purchase price of the product
product_purchase_price_gross_last	FLOAT	Last gross purchase price of the product
product_purchase_price_net_average	FLOAT	Average net purchase price of the product
product_purchase_price_gross_average	FLOAT	Average gross purchase price of the product
currency	STRING	Product currency
vat_rate	FLOAT	Product VAT rate
product_adding_time	DATE	Product addition date
product_age_days	INTEGER	Product age in days
product_price_changed_time	DATE	Date of the last product price change
product_availability_management_type	STRING	Product availability management type

6. Clients Table - Data Structure

The table contains client data based on combined data from the orders and products tables.

Column Name	Data Type	Description
client_email	STRING	Client email address
client_phone	STRING	Client phone number
client_first_name	STRING	Client first name
client_last_name	STRING	Client last name
hashed_client_email	BYTES	Encrypted client email address
hashed_client_phone	BYTES	Encrypted client phone number
hashed_client_first_name	BYTES	Encrypted client first name
hashed_client_last_name	BYTES	Encrypted client last name
client_delivery_address_zip_code	STRING	Postal code of the client's delivery address
client_delivery_address_country_code	STRING	Country code of the client's delivery address
days_since_first_order	INTEGER	Number of days since the client's first order
days_since_last_order	INTEGER	Number of days since the client's last order
min_product_net_price	FLOAT	Minimum net price of a product purchased by the client
max_product_net_price	FLOAT	Maximum net price of a product purchased by the client
has_invoice	BOOLEAN	Information whether the client has ever requested an invoice
order_count	INTEGER	Number of client orders
unique_item_count	INTEGER	Number of unique products purchased by the client
total_net_revenue	FLOAT	Total net revenue generated by the client
recency_score	INTEGER	Recency score (RFM)
frequency_score	INTEGER	Frequency score (RFM)
monetary_score	INTEGER	Monetary value score (RFM)
customer_segment	STRING	Client segment (e.g., 'Champions', 'Loyal Customers', 'At Risk')
quantity_of_purchased_brands	INTEGER	Number of different brands purchased by the client
purchased_brands	STRING	List of purchased brands
quantity_of_purchased_categories	INTEGER	Number of different categories purchased by the client
purchased_categories	STRING	List of purchased categories

7. Returns Table - Data Structure

The table is in preparation. It will be added to the Data Octopus application on June 1, 2025.

8. Data Update Cycle

Data is collected daily at night between 00:00 and 2:00.

9. Summary

Integration with the IdoSell platform enables comprehensive e-commerce data analysis, including:

Tracking orders and their statuses
Analysis of customer behavior and segmentation
Analysis of returns
Monitoring product and category performance
Analysis of revenue and sales trends

The Data Octopus system processes this data into a form that allows for deep business analyses, which can support strategic and operational decisions.

Mapping rules and conditions

Idosell Data Schema

Brands