In addition to the recommendation algorithms and filters that you use to build recommendation strategies and bundles for Monetate Dynamic Bundles, you can upload your own product recommendations as a Recommendations dataset. See Create a Recommendations Dataset to learn how to accomplish that task.
Dataset Specifications
This table contains the attributes, also called columns or fields, you must include in a Recommendations dataset.
| Attribute | Data Type | Example | Description |
|---|---|---|---|
lookup_key |
String | abc |
Value used to find related recommendations. These values should associate to item_group_id parent identifier values in the linked product catalog. |
id |
String | xyz-123 |
A product's unique identifier. Use the SKU collected in your web integration where possible. These values should associate to the id values in the linked product catalog. |
rank |
Number | 10 |
The ranking of importance or the position in which this record is returned in the list of records from the specified lookup_key. |
Only the attributes in the specifications table can appear in a Recommendations dataset. If you include additional ones when creating the dataset schema, Monetate discards them without alerting you. If you include them when updating a Recommendations dataset, the update then fails, with the File Upload Error modal noting the presence of the unknown field(s).
Submit a support ticket using the Monetate Technical Support portal (support.monetate.com) if you need additional assistance customizing recommendations.
Use Cases
Here are three examples of how you can use a Recommendations dataset.
Display Customized Recommendations
Purpose: To create your own product recommendations for any products
Implementation: Input an item_group_id (product ID) in the lookup_key column, and list in the id column a product that you want to recommend for the corresponding item_group_id.
Examples
- Leverage the expertise of merchandisers to offer curated recommendations for specific products.
- Leverage the output of a new algorithm internally developed by a data science team.
Sample file: RecDataset.csv
Recommend a Specific List of Products
Purpose: To display a manually curated list of products
Implementation: Ensure the lookup_key column is populated with a value of none for all line items.
Examples
- Display a curated list of products on a homepage or landing page.
- Display products that you want to highlight as "New Arrivals."
Sample file: RecDataset_none_lookupkey.csv
Recommend Products to Specific Customers
Purpose: To display internally developed recommendations for individual users
Implementation: Ensure that the lookup_key column is populated with customer IDs and that the id column is populated with the products that you want to recommend for the corresponding customer IDs.
Example
Leverage the output from a data science team to present individually curated recommendations to high-value shoppers on a landing page.
Sample file: RecDataset_custid_lookupkey.csv