Campaign recommendations

Overview

The Search Engine Marketing (SEM) campaign recommendations API enables sellers to optimize campaign performance by providing budget and bidding strategy recommendations derived from campaign performance signals. Recommendations are generated for eligible active campaigns.

Use cases

This API allows you to:

Optimize campaign budgets and bidding strategies
Improve ROAS through data-driven recommendations
Prioritize high-impact campaigns by projected impact metrics

Key data considerations

Recommendations are generated only for eligible active campaigns. Inactive or ineligible campaigns will not return results.
Projected metrics are estimates. Actual performance may vary based on campaign activity, inventory availability, and market conditions.
Recommendations may suggest budget adjustments, bidding strategy changes, or both, depending on campaign eligibility.
Poll this endpoint periodically to surface the most current optimization opportunities.

Endpoint

POST /v3/advertising/sem/campaigns/recommendations/search

Supported filters

Filter field	Description
`campaignIds`	Filter by campaign IDs
`recommendationType`	Filter by `BUDGET` or `BIDDING_STRATEGY`

Supported sorting

Field	Orders
`adspend`	`ASC`, `DESC`

Recommendation types

Recommendation type	Description
`BUDGET`	Budget increase or adjustment recommendations
`BIDDING_STRATEGY`	Bidding strategy optimization recommendations

Request sample

curl --request POST \ --url 'https://marketplace.walmartapis.com/v3/advertising/sem/campaigns/recommendations/search' \ --header 'WM_QOS.CORRELATION_ID: b3261d2d-028a-4ef7-8602-633c23200af6' \ --header 'WM_MARKET: US' \ --header 'WM_SVC.NAME: Walmart Marketplace' \ --header 'WM_SEC.ACCESS_TOKEN: <Your_access_token>' \ --header 'WM_GLOBAL_VERSION: 3.1' \ --header 'Accept: application/json' \ --header 'Content-Type: application/json' \ --data '{ "page": { "offset": 0, "limit": 10 }, "filters": [ { "field": "recommendationType", "values": ["BUDGET"] } ] }'

import requests url = "https://marketplace.walmartapis.com/v3/advertising/sem/campaigns/recommendations/search" headers = { "WM_QOS.CORRELATION_ID": "b3261d2d-028a-4ef7-8602-633c23200af6", "WM_MARKET": "US", "WM_SVC.NAME": "Walmart Marketplace", "WM_SEC.ACCESS_TOKEN": "<Your_access_token>", "WM_GLOBAL_VERSION": "3.1", "Accept": "application/json", "Content-Type": "application/json"
} payload = { "page": { "offset": 0, "limit": 10 }, "filters": [ { "field": "coopRecommendationType", "values": ["BUDGET"] } ]
} response = requests.post(url, headers=headers, json=payload)
print(response.json())

Modify your code

You can customize recommendation queries by:

Filtering by campaign IDs
Retrieving only BUDGET or BIDDING_STRATEGY recommendations
Sorting campaigns by adspend
Adjusting pagination values

Example customization

{ "sort": { "field": "adspend", "order": "DESC" }
}

Response sample

{ "pagination": { "pageNo": 0, "pageSize": 10, "totalCount": 1, "totalPages": 1, "hasNextPage": false, "hasPreviousPage": false }, "data": [ { "campaignId": "2085840575", "name": "Electronics Growth Campaign", "dailyBudget": 1000, "campaignRecommendations": [ { "type": "BUDGET", "subType": "INCREASE_DAILY_BUDGET", "recommendedValue": "2400.0" } ] } ]
}

Results

A successful response returns paginated campaign-level recommendations for active SEM campaigns. Each campaign includes current settings and one or more recommendations with projected performance impact metrics.

Error handling

Status code	Description	Remediation
`400`	Invalid request parameters	Validate filters, sort fields, and paging values
`401`	Unauthorized	Verify access token
`403`	Forbidden	Confirm SEM access permissions
`422`	Unprocessable entity	Validate request body structure
`429`	Rate limit exceeded	Retry later
`500`	Internal server error	Retry request
`503`	Service unavailable	Retry with exponential backoff

Best practices

Review projected metrics before applying any recommendation
Prioritize recommendations with the highest projected click or impression lift
Retrieve recommendations on a regular cadence to catch new optimization opportunities
Implement an approval workflow before enabling any auto-apply logic
Surface recommendation data in campaign dashboards for visibility across your team