CSV Data Format
SkuBrain requires as little as 6 data fields in CSV format to generate high quality forecasts from your sales history. However, when you provide more data, SkuBrain can create even better forecasts, for example by taking into account category hierarchies. Please see below for the required, optional and recommended fields when uploading data with CSV.
Note: The maximum CSV size is 20 MB.
|OrderDate|| 2016-10-24 (ISO)|
| The date of the order in YYYY-MM-DD format, where YYYY is the four digit year, MM is the month and DD is the day of the month.|
So our example date corresponds to the 24th of October 2016.
|SKU||CH-0234|| The Stock Keeping Unit - a Unique identifier for the product that was sold. Probably you’ll have unique identifiers for the products|
you sell in your accounting or inventory management system.
|Quantity||5||The number of items that were sold. This must be a positive whole number.|
|UnitPrice||10.99|| The price that each individual unit was sold for. This column should contain either an integer or a decimal value (don’t include any|
currency signs or currency codes). If you are only interested in forecasting quantities, you may leave this field empty and
SkuBrain will automatically set the Unit Price to 1.0.
| The reference number of the order that the sale relates to. This information will allow us to establish patterns|
for items that are commonly sold together (which can be used for assortment planning).
This column must be present in your input file, but it may be left empty, in which case a unique value will be automatically generated.
|LineReference||323676-1|| The Line Reference should uniquely identify an order item. This is used to prevent duplicate order data from being imported.|
If you upload two sales with the same line reference, the first sale will be overwritten by the second.
You should be able to get an appropriate Line Reference from your ERP
If the system that you’re exporting your data from does not assign line references, you can simply use the order reference plus
We also provide special support for certain fields. Although not required, we strongly recommend you try to include these columns in the CSV files that you upload. If these fields are present then you will be able to access some more advanced analysis features in the software.
|The product category of this SKU. It is usually useful to forecast by Product Category, which often detects a sales seasonality that is not found at the SKU level.|
|Brand|| Wicked Widgets|
| The brand of this SKU. It is often useful to analyse forecasts by Product Brand. If both Product Category and Product Brand are provided, new forecasts will automatically|
use this hierarchy:
Category / Brand / SKU
| A unique reference for the customer. This might be a customer ID from your ERP or|
CRM platform or it could be some other value that uniquely identifies your
customers, such as their full name or email address.
We can use this information to analyze customer retention rates (or conversely churn rates).
|UnitCost||5.45|| The cost price of each of the products that was sold - this is the price that you purchased the goods for. This column should contain either an|
integer or a decimal value (don’t include any currency signs or currency codes).
If present, we can use this to calculate sales margins and profitability. This is often important when you believe you will have demand
|UnitOfMeasure||0.04|| An optional conversion factor for quantities. If specified, SkuBrain will calculate Unit x UnitOfMeasure to enable you to view your Sales in|
Eaches or another Unit. The UnitOfMeasure should convert all SKUs to the same Unit. For example, to also display Beer Sales in
barrels, specify a conversion factor of 0.04 for Case SKU’s and 0.0167 for Gallon SKU’s. Units of Measure for each SKU can usually be extracted directly from your ERP.
In addition to the fields/columns that are explicitly supported, you can include columns for any custom fields that you would like to report on. So, for example, you could include columns for the product “Category”, “Subcategory” and “Model”. This would allow you to generate hierarchical forecasts, organizing products by Category / Subcategory/ Model / SKU.
You might include fields such as the Category (recommended), Brand (recommended), Store, Country, Region, Sales Person or anything else you think is relevant to the products you sell.