You can download demo data here.

In order to load data to Inventoro, you can either use one of our connectors if your data reside on the connected platforms or use this general import to include your data into the Inventoro platform. The data should contain your product and sales information for optimum at least last 2 years in order to perfectly compute seasonality or any other trends.

This article describes the data structure exactly how we need it in order for Inventoro to work correctly. Once you have the structure ready, you will be ready to upload the data and create a connection. If you are ready to do so, please read this article on how it is done. But first:

Data spaces

There are 2 data spaces for the Inventoro. 

  • Sales Data 
  • Promotion Data

Sales Data contains all your product, warehouse and transaction information. Based on past transactions we can forecast future sales and based on product-warehouse data (current state of amount on stock for example) we can tell you what to order and when. 

In order for perfectly analyse sales and predict future we need information about your promotions. Past promotions serve as a benchmark to see if the high sales are due to higher demand or due to promotion, future promotion serves us to higher the expected forecast because of it. In the best scenario both past and planned promotions will help us compute better forecast and orders.

Entity types

There are several entity types we import in order to compute all necessary data. Each fits into its own .csv file.

  • Warehouse - this entity holds information about warehouse or any other place where we store items (point of sales etc) 
  • Product - basic information about product - name, category 
  • Supplier - basic information about suppliers 
  • Category - categorisation of the products (like product lines, brands etc.) - Inventoro currently supports only one level of categories (so no nested or parent-child categories are taken into account) 
  • Warehouse-product - In warehouse product connecting data are specific data for each product on given warehouse (so for example product A on Warehouse 1 has different inventory on hand or price than on Warehouse 2) 
  • Transactions - Each transaction is one sales item, so if one order has 2 products sold, it is 2 transactions in Inventoro. Data can be grouped per item per day (so all sold Product A per day from Warehouse 1)
  • Currency - Indicating primary and (if applicable) secondary currency of the system to be displayed.


Currency (currency.csv)

currency_idISO code of currencyfor example USD
defaulttinyint0/1 There should be only one default currency per file (the default one)

Warehouse (warehouse.csv)

warehouse_idgenerated id [0-9a-zA-Z_-]
nameVarchar 64
parent_warehouse_idgenerated id [0-9a-zA-Z_-]ID of parent warehouse, for use in case of supplying your warehouse/shop from central warehouse for example

Product (product.csv)

product_idgenerated id [0-9a-zA-Z_-]
nameVarchar 64
category_idFK - category_idFK = Foreign key - link to category based on the category_id (that category must exist)
shortcutVarchar 255ID that is displayed to the user in the app as id of the product, if empty, it is filled with product_id
brandVarchar 255
tags which will help you to cluster your portfolio by brands (you can use it on the replenishment as a filter etc.)
collectionVarchar 255
especially useful for fashion industry (limited collections etc)
product_id_by_supplierVarchar 255
Product ID which is helping your suppliers to identify items on the purchase orders
eanVarchar 255
EAN code (European Article Number (International Article Number))

Supplier (supplier.csv)

supplier_idgenerated id [0-9a-zA-Z_-]
nameVarchar 64
currency_idISO code of currency

Category (category.csv)

category_idgenerated id [0-9a-zA-Z_-]
nameVarchar 64

Warehouse product (warehouse_product.csv)

warehouse_idFK - warehouse_idlink to warehouse via ID
product_idFK - product_idlink to product via ID
available_supplyDecimalavailable amount of this goods on stock
stock_priceDecimalprice of cost for this unit
sale_priceDecimalusual selling price of this goods
supplier_idFK - supplier_id
minimal_order_quantityDecimalminimal order quantity for this product, if not available empty value (as NULL)
minimal_order_setDecimalminimal order set (for example packaging) for this product, if not available empty value (as NULL)  If the minimal quantity is 100 and minimal set is 10 the orders will be 100,110,120 etc. if minimal quantity is 0, the orders are in multiply of minimal_order_set (10,20,30..)
visibletinyintif 1 then product is processed by Inventoro (is active), if 0 then product is skipped completely
ordertinyintif 1 then product can be proposed in replenishment, if 0 product cannot be proposed
created_atstringthe exact date when the SKU/item was created,
Format W3C Y-m-d\TH:i:sP
example: 2005-08-15T15:52:01+00:00
similar_product_idFK - product_id
ID of the predecessor, Inventoro will automatically utilize the sales history from this predecessor
basestock_minDecimalminimum inventory you would like to keep
basestock_maxDecimalmaximum inventory you would like to keep
expiration_in_daysDecimalreal expiration in days after delivery to your warehouse
minimal_periodDecimalpurchase order period in days
leadtimeDecimallead time in days

Transaction (transaction.csv)

transaction_idgenerated id [0-9a-zA-Z_-]usually line number
transaction_type_idsee transaction types
warehouse_idFK - warehouse_idwarehouse from which this product was sold
product_idFK - product_id
amountDecimalamount sold in units
priceDecimalunit price of transaction, in case of sales transaction it is unit sell price, in case of other transactions it is unit stock price
stock_priceDecimalcost of this goods (per unit)
supplier_idFK - supplier_idif the transaction is of type Purchase
promo_sale0,1If this sale had some discount or other promo
extreme_sale0,1if the sale is extreme(1) it is not used for forecasting
date_of_orderYYYY-MM-DDif the transaction os of type Purchase, empty otherwise

Transaction types: 

In Inventoro we can import multiple types of transaction (sales, purchase, stock-taking, transfer of goods etc.). The must for the integration are sales and purchase transaction. For explanation of the rest please contact us.  

For the initial import, please consider using sales and purchase transactions - each has its own transaction_type_id. 

1 = Sales Transaction (if the amount is <0 than it is Cancellation of the sales) 

2 = Purchase Transaction (if the amount is <0 than it is Cancellation) - you are purchasing the product from your supplier

If you want to include cancelations (return of the goods) use the same transaction_type_id but use negative value in the amount field. The logic is always - positive amount = succesful transaction, negative amount = return or cancelation.  Inventoro does not calculate the cancelation exactly in the month as it occurred but tries to find the transaction which is cancelled and negate that previous sales. So that if you on 2020-31-07 sell 10 items and 1.8 Inventoro see -10 items, you will see 0 sell in month 07 and 08 as well.

More information about transactions (and more deeper transaction types) you can find in


If you have multiple warehouses and want the orders to be generated only to the central warehouse please fill in the data as follows:

1) Central warehouse should be first in the warehouse file and its parent_warehouse_id should be empty

2) All stores which are replenished through central warehouse should : 

  • in warehouse.csv have filled in parent_warehouse_id as central warehouse
  • for each item in warehouse_product which is replenished through central warehouse the "supplier_id" field should be empty
  • for each item in warehouse_product which is supplied directly - supplier_id should be filled in

3) please make sure that each good in replenished warehouse there is the same product on central warehouse.  

Optional Delivery Data

In order to tell Inventoro that you are already expecting some goods (goods in transit) you can fill data for future_delivery. Please put in future_delivery only the goods which might come in near future. If the order was partially fulfilled we expect that the fulfilled part is in transactions as transaction_type_id=2 and the unfulfilled amount (should it still arrive) should be inserted into future_delivery data. The second type is customer order you are expecting in the future to be delivered.

Future delivery or Inventory in transit or Customer Orders (future_delivery.csv)

future_delivery_idgenerated id [0-9a-zA-Z_-]Unique identifier of Inventory in transit
use SUPPLIER_ORDER for Purchase Orders in Transit or
CLIENT_ORDER for Customer Orders
Optional. If you don't use column future_delivery_type at all. All records are considered type=SUPPLIER_ORDER
product_idFK - product_idlink to the product - must exist in products and warehouse_product
warehouse_idFK - warehouse_idlink to warehouse where the goods will be delivered
supplier_idFK - supplier_idlink to supplier (empty if the order is between two locations (warehouses)
parent_warehouse_idFK - warehouse_idlink to warehouse(empty if the order is from the supplier)
date_of_orderYYYY-MM-DDwhen the purchase order was created
estimated_date_of_deliveryYYYY-MM-DDwhen the purchase order will be delivered
amountDecimalamount of goods in transit
purchase_priceDecimalpurchasing unit price

If you wish to give us during the integration phase your minimal periods (how often you buy such goods) and leadtimes (how fast you can receive goods upon placing an order) you can give us data in this format

Supplier configuration (supplier_configuration.csv)

supplier_idFK - supplier_id
minimal_periodintminimal purchase period
leadtimeintusual lead time in days for this provider/supplier
leadtime_stdintdays of standard deviation for lead time

Later it is recommended to update the values in the Inventoro application.

Promotion Data (promotion.csv)

promotion_typecoupon, gift, discount, other, listing, delisting
promotion_idgenerated id [0-9a-zA-Z_-]identifier of promotion to separate multiple promotions
product_idFK - product_id
warehouse_idFK - warehouse_idif empty applies to products on all warehouses
promotion_date_fromYYYY-MM-DDstart of the promotion
promotion_date_toYYYY-MM-DDend of the promotion
powerDecimalpower of the promotion (for example 10 represents 10% discount)
estimated_amountDecimalif you know how many you expect to sell during that promotion

Forecast only Sales data

If you need to compute only forecast and do not need to compute orders or help with stock, the minimal amount of information we need to get from you is this information.

The format of the files should be the same, the information not in the table below should be empty column or 0 for numbering fields. 







generated id [0-9a-zA-Z_-]


Varchar 64



generated id [0-9a-zA-Z_-]


Varchar 64


FK category_id



generated id [0-9a-zA-Z_-]


Varchar 64



FK - warehouse_id


FK - product_id



generated ID 

usually line number


see transaction types


FK - warehouse_id

warehouse from which this product was sold


FK - product





amount sold in units



If this sale had some discount or other promo



if the sale is extreme(1) it is not used in forecasting

Data Import CSV

Data are sent as CSV files. Entity type (entity type is for example Warehouse or Product) consists of all records of that entity type (so all warehouses are lines in one file warehouse.csv, we do not support multiple csv per type - for example it is not possible to send half of the products in one csv file and half in other csv file). 

Foreign key - FK fields(connections between entities - like for example category to product link) must be filled and must match foreign entity, otherwise the row will not be inserted. For example if we find transaction which does not have product attached we ignore it for both forecast and orders suggestions. 

Filename for each entity type is a possible to set up in initial setting, but should follow these naming conventions: 

  • warehouse.csv 
  • product.csv 
  • supplier.csv 
  • category.csv 
  • warehouse_product.csv 
  • transaction.csv 
  • supplier_configuration.csv
  • currency.csv

Please also check

You can download demo data here.


This document describes the data structure in following version: 

  • Version of sales data  - 1.5
  • Version of promotion data - 1.5