- Overview
- Platform setup and administration
- Platform setup and administration
- Platform architecture
- Data Bridge onboarding overview
- Connecting a Peak-managed data lake
- Connecting a customer-managed data lake
- Creating an AWS IAM role for Data Bridge
- Connecting a Snowflake data warehouse
- Connecting a Redshift data warehouse (public connectivity)
- Connecting a Redshift data warehouse (private connectivity)
- Reauthorizing a Snowflake OAuth connection
- Using Snowflake with Peak
- SQL Explorer overview
- Roles and permissions
- User management
- Inventory management solution
- Commercial pricing solution
- Merchandising solution
Competitor prices dataset containing observed competitor pricing per product-region combination over time, used by the Commercial Pricing solution for market context.
The Competitor prices dataset contains observed competitor pricing per product and region over time. It gives the commercial pricing solution market context — letting it factor in how competitors are pricing the same products when generating pricing recommendations.
This dataset is required for application deployment and pricing insights analysis.
→ For the canonical technical schema (data types, validation rules, request/response examples), see Competitor Price in the API Guide.
Purpose
The commercial pricing solution uses the Competitor prices dataset to:
- Benchmark recommended prices against observed competitor pricing
- Account for competitive positioning in pricing recommendations
- Identify markets where our pricing is meaningfully out of line with competitors
- Support analysis of how competitor pricing changes over time
Without competitor pricing data, recommendations are made in isolation from the broader market context.
Required fields
About the Nullable column: every field below must appear in your data. Nullable: Yes means the field can be sent as null (or left blank in your source) when no value is available; Nullable: No means a non-null value is required for every row.
| Field | Description | Type | Nullable |
|---|---|---|---|
product_id | Unique identifier for each product. Used to join product metadata to the table. | string | No |
region_id | Unique identifier of the region. Used as a model feature, since competitive pricing varies by region. | string | No |
updated_at | Timestamp when the record was last updated. Successive observations of the same product/region combination are stored as new rows. | timestamp_tz | Yes |
competitor_price | Observed competitor price for this product in this region at the recorded time. | float | Yes |
Custom fields
The fields listed previously are the standard schema for this dataset. A field that your business requires but the standard schema does not include can be added as a custom attribute after the schema is rolled out. Custom attributes are additive, so they extend the dataset without affecting existing fields, and they are validated in the same way as standard fields.
The following request adds a CAPTURE_METHOD column to this dataset:
curl -X POST \
'https://ingestion.peak.ai/api/v2/schema/QP_COMPETITOR_PRICE_OOTB/add-attribute' \
-H 'Authorization: YOUR_API_KEY' \
-H 'Content-Type: application/json' \
-d '{
"solutionName": "QP_OOTB",
"columnName": "CAPTURE_METHOD",
"dataType": "string",
"validations": [
{ "type": "optional" }
]
}'
curl -X POST \
'https://ingestion.peak.ai/api/v2/schema/QP_COMPETITOR_PRICE_OOTB/add-attribute' \
-H 'Authorization: YOUR_API_KEY' \
-H 'Content-Type: application/json' \
-d '{
"solutionName": "QP_OOTB",
"columnName": "CAPTURE_METHOD",
"dataType": "string",
"validations": [
{ "type": "optional" }
]
}'
The table name in the request URL is this dataset's fully qualified warehouse name, which includes the prefix and suffix configured when your solution was rolled out — QP_COMPETITOR_PRICE_OOTB in this example. Retrieve the name for your own solution with Describe a solution's schema.
On standard tables the API prefixes the new column name in the warehouse with C_ (Snowflake) or c_ (Redshift), so CAPTURE_METHOD becomes C_CAPTURE_METHOD and warehouse queries must use the prefixed name.
Custom attributes are additive only — they never become part of the primary key. This dataset is keyed on product_id, region_id, and updated_at, so rows that match on all three overwrite one another regardless of any custom column you add. If you need to record prices from several competitors for the same product, region, and timestamp, that requires a change to the standard schema, not a custom attribute - raise it with your UiPath contact.
→ For the full parameter reference, supported data types, and validation rules, see Customizations in the API Guide.
Usage notes
- All referenced identifiers (
product_id,region_id) must exist in their corresponding datasets. - Submit observed market prices, not estimates — the model treats this as ground truth on competitive positioning.
- Successive observations of the same product and region are appended with new
updated_atvalues, preserving the full history of competitive movement over time. - Historical depth improves the solution's ability to detect pricing trends and react to competitor moves.
- Frequency of updates depends on how often you can observe competitor prices reliably; more frequent updates keep the model's competitive context current.
Why this dataset matters
The Competitor prices dataset is what connects the commercial pricing solution to the broader market. Without it, pricing recommendations only reflect internal cost and demand signals — missing the competitive pressure that often drives whether a quote is won or lost.