NuORDER offers data integration between our cloud-based application and your retailer back office systems. As an enterprise retailer using NuORDER Assortments to plan your buys, you will have the ability to automate data to and from NuORDER.
Just as your NuORDER Assortment configuration will be customized to meet your requirements, our Product & Technology team will work with you to set up the appropriate data feeds. Some of these feeds will be customized to your specific data structure, while others will follow standard NuORDER formats.
- Data feeds supported
- Retailer reference data (inbound)
- Post market assortment data
- FTP import / export process
- Appendix: Sample formats
Data feeds supported
You can integrate any or all of the following data feeds to and from assortments, as applicable to your business.
Retailer reference data
From Retailer to NuORDER – CSV via SFTP
- Internal hierarchy
- Other reference lists, for example: vendor codes, exchange rates, etc.
- Size curves
Post-market assortment data
From NuORDER to Retailer – JSON via SFTP
- Item creation
- Purchase orders (POs)
From Retailer to NuORDER – via API
- Feedback on item/PO sync
Retailer reference data (inbound)
You can send a variety of reference lists from your internal systems to NuORDER for buying teams to utilize within their assortments.
Internal hierarchy
Hierarchy data will typically consist of the codes and descriptions of your business divisions, the structure for how buys are budgeted and reviewed, and how products are classified. This data is often critical to have in the assortment for analytic and leadership review purposes, comparing to financial targets, or facilitating integration back into your system post-market for item setup and PO creation.
Typically this data might include (but is not limited to) some combination of:
- Department, class, subclass
- Division
- Buyer
- DMM, GMM
- Other planning categories
Other reference data
Additional lists and data tables can be provided from your system for any other purpose that buying teams may need to complete their assortments, or to facilitate a seamless downstream integration to your system. As part of your onboarding process we will review any macros or lookups in your current buy sheet, which of those will be relevant to bring into NuORDER, and any required formats.
Examples of additional reference data:
- Vendor/brand codes and descriptions
- Exchange rates
- Product types
- Vendor terms
- Color codes
- NRF or HTS codes
- UDA field lists
- And more!
User experience
Within the assortment, your users will be able to search and pick from each lookup list to populate data fields using the internal data from your system. Once populated, these fields can then be used for filtering, calculations, pivot tables, reviewing against targets, and more.
Related fields
Below are a few examples of related fields we have done with existing partners. If you have another type of relationship needed, please review this with your NuORDER Product Manager.
Type | Description | Examples |
---|---|---|
Code + description | Users can search by either the code or description. After selecting a result from the list, the code and description auto-populate in their respective fields. | Example: After selecting the department, the Department Name and Department Number populate in their respective fields. |
Tree or nested structure | Users are forced to choose fields in a specific sequence; each selection filters the options available for the next field. |
Example A: User selects a Department. This dictates the options they have to choose for Class, which then dictates the options for Subclass. Example B: User selects a Department. This dictates the list of values to choose from in field UDA 1, which is being used for each department’s seasonal buying trends. |
Auto-populate | After selecting one field, additional fields auto-populate based on a 1-1 relationship. | Example A: After selecting Buyer, the Division, DMM, and GMM fields are auto populated. Example B: After selecting the vendor’s currency, an FX Rate field is auto populated and used to calculate pricing/totals in your local operating currency. |
Integrated data tables vs. hard-coded dropdowns
For basic lists that never change, this can usually be configured into the assortment schema as a simple hard-coded dropdown. Integrated data tables are typically recommended for more complex data, multi-field relationships, and lists that change regularly. The FTP upload process will allow you to self manage updates without needing to submit a request to the NuORDER team.
Data format & frequency
Format: For common hierarchy and data tables, NuORDER has standard CSV templates (see Appendix for examples). Customized data tables/headers via CSV can also be supported; please review the details of your requirements with your NuORDER Product Manager.
Frequency: On the NuORDER side, we typically schedule our system to check the FTP folder 1-4x daily, however many retailers generate and send files less frequently according to their internal business processes, e.g. weekly or ad hoc when that system has been updated.
Size curve data
Size curve data will include your distribution ratios per size per location, at whatever level of granularity you are maintaining them, e.g. vendor, department, class, subclass, etc.
NuORDER will configure your size curve lookups to work with your specific internal hierarchy. If your curves are maintained at varying levels of granularity, NuORDER can configure a fallback pattern to look first for the most specific curve, and if that is not available, fall back to the next level up, and so on. For example, some departments may maintain size curves at the Vendor-Class-Subclass level, while others may be more generally based on Vendor-Class, or Class alone.
Your size curve data file will include:
- Lookup hierarchy (this may be one or multiple fields)
- Name of curve
- Size range included in the curve
- Size
- Store number (ID of the location)
- Distribution ratio (% per size x location)
How do we ensure your size data matches each brand’s values?
To account for varying size terminology from one vendor to another (e.g. “Small” vs “SM” vs “S”), NuORDER performs a normalization on the brand’s product data to ensure sizes are standardized and consistent. The same transformation can be set up to make sure the values in your size curve data will match NuORDER’s standard size families.
User experience
Within the assortment, your buying teams will be able to apply size curves to the entire assortment or selected items via easy bulk actions. Using the internal hierarchy that has been filled out for each item in the assortment, NuORDER will find the best matching size curve from your data and distribute the bulk units in each location based on that door’s distribution ratio.
Learn more about applying size curves in assortments.
Data format & frequency
Format: NuORDER has standard field headers for the name of the curve, size, store number, and distribution ratio. The fields that correlate to your internal hierarchy will be customized. Please see the Appendix for an example.
Frequency: On the NuORDER side, we typically schedule our system to check the FTP folder 1-4x daily, however many retailers generate and send files less frequently according to their internal business processes, e.g. weekly or ad hoc when that system has been updated.
Post market assortment data
Items & Purchase Orders (outbound)
As your buying teams complete their buys in NuORDER, users can initiate sending their assortment data to your back office system for item setup and purchase order (PO) creation.
This integration is a user-initiated push from within the UI that will generate a JSON export of the selected assortment data, which will be placed on your FTP for ingestion.
The JSON file includes:
- All fields from your custom assortment schema
- Header information, including the assortment name, user, and process indicator to distinguish between Item/PO actions
- Store locations (aka “doors”) from the assortment, including associated cost/retail fields and door attributes
- Deliveries from the assortment
- Size level item data, including UPCs
- Units per size x location x delivery
User experience
Within the assortment, users will be able to export selected items or the entire assortment using the specific export process(es) we have set up for you. Each export process will have a corresponding validation step based on your requirements to ensure data compliance and completeness prior to exporting. For PO creation, users can fill out additional data such as the specific doors and deliveries applicable to each PO, ship/cancel dates, and a PO Description.
Learn more about exporting assortment items and exporting assortment POs.
Learn more about data validation on Item and PO exports.
Data format & frequency
Format: NuORDER provides a standard JSON file format. This format is not customizable, however the specific assortment fields will reflect your customized schema.
Download a sample JSON populated with dummy data. (Please note, the specific fields will vary according to your assortment schema.)
Frequency: User-initiated via the assortment UI
Item & PO feedback messages (inbound)
NuORDER offers an API integration for sending feedback messages, such as ingestion errors, from your internal system to be displayed within the assortment UI for the user.
This process is intended to be used in conjunction with our outbound Item and PO feeds. After retrieving the item or PO creation file, your system can send back a response to let the user know if the ingestion was successful, or any specific errors or warnings that need to be addressed.
User experience
Within each assortment, users will be able to view an Export Log to see feedback messages received from your system.
Learn more about assortment export logs and receiving feedback on item & PO exports.
Data format & frequency
Format: OpenAPI 3; Download our external API documentation.
Frequency: Typically ad hoc as Item or PO ingestion files are processed.
FTP import / export process
To transmit your inbound CSV files and outbound JSON files, we can either provide the sFTP server hosted by NuORDER and share the credentials with you, or we can connect to yours.
Inbound process
All data files will typically be placed in one directory, using unique file names to distinguish between each different data table we are ingesting for you.
How incoming files will be transferred into NuORDER:
- Your developer will set up an automated schedule (cron job) to drop each data file in the FTP directory, or you can manually place files there ad hoc.
- Our system checks on set intervals (coordinated with your Product Manager) to process any new files.
- Once a file has been processed, it will be deleted from the FTP folder automatically.
- You will receive an email notification confirming either success or errors.
- If there are errors, nothing from that file will be saved. You will need to review the data that was loaded, correct the issue, and reload a new file. (Typically errors are caused by an incorrect field header, invalid data type, or blanks in a required field.)
Outbound process
Assortment JSON files will be placed in your FTP folder when initiated by a user export action within the UI. From that point on, the process is up to you and your developer to ingest and delete the files.
Appendix: Sample formats for retailer reference data
Expand each section for more details.
Internal hierarchy
Department / Class / Subclass
Department
File type | File name |
---|---|
CSV | dept_<date>.csv |
Data fields
Column name | Column type | Example data | |
---|---|---|---|
1 | DEPT_ID | INT64 | 100 |
2 | DEPT_NAME | STRING | WOMENS |
Class
File type | File name |
---|---|
CSV | dept-class_<date>.csv |
Data fields
Column name | Column type | Example data | |
---|---|---|---|
1 | DEPT_ID | INT64 | 100 |
2 | CLASS_ID | INT64 | 5 |
3 | CLASS_NAME | STRING | TOPS |
Subclass
File type | File name |
---|---|
CSV | dept-subclass_<date>.csv |
Data fields
Column name | Column type | Example data | |
---|---|---|---|
1 | DEPT_ID | INT64 | 100 |
2 | CLASS_ID | INT64 | 5 |
3 | SUBCLASS_ID | INT64 | 80 |
4 | SUBCLASS_NAME | STRING | TEES |
Department / GMM / DMM / Buyer hierarchy
File type | File name |
---|---|
CSV | dept-hierarchy_<date>.csv |
Data fields
Column name | Column type | Example data | |
---|---|---|---|
1 | DEPT_ID | INT64 | 100 |
2 | BUYER_ID | INT64 | 123 |
3 | BUYER_NAME | STRING | FIRST LAST NAME |
4 | GMM_ID | INT64 | 123 |
5 | GMM_NAME | STRING | FIRST LAST NAME |
6 | MGM_ID | INT64 | 123 |
7 | MGM_NAME | STRING | NAME |
8 | DMM_ID | INT64 | 123 |
9 | DMM_NAME | STRING | NAME |
10 | DIV_ID | INT64 | 123 |
11 | DIV_NAME | STRING | NAME |
12 | PDIV_ID | INT64 | 123 |
13 | PDIV_NAME | STRING | NAME |
Size curves
File type | File name |
---|---|
CSV | size-curves_<date>.csv |
Data fields
Please note, the specific columns correlating to your internal hierarchy (Dept, Class, Subclass in this example) will be customized for your schema and size curve requirements.
Column name | Column type | Example data | |
---|---|---|---|
1 | DEPT_ID | INT64 | 100 |
2 | CLASS_ID | INT64 | 123 |
3 | SUBCLASS_ID | INT64 | 99 |
4 | CURVE_NAME | STRING | WMNS APPAREL TEES |
5 | STORE_NAME | STRING | 1 |
6 | SIZE_NAME | STRING | XS |
7 | SIZE_RANGE | STRING | XXS-XXXL |
8 | SIZE_ORDER | STRING | 2 |
9 | DISTRIBUTION_RATIO | STRING | .05 |