customerFeedback_getBrowseNodeReturnTrends
Month-by-month share of the category's returns that cite each return reason (past 6 months, newest first) for a browse node (US, UK, FR, IT, DE, ES, JP only) — whether a reason is
readAmazon Seller (SP-API)sp.customerFeedback_2024-06-01
growing, and seasonal patterns. The last step, after customerFeedback_getBrowseNodeReturnTopics. Amazon SP-API · getBrowseNodeReturnTrends · GET /customerFeedback/2024-06-01/browseNodes/{browseNodeId}/returns/trends
Call it
In an AI client (MCP)
{
"name": "customerFeedback_getBrowseNodeReturnTrends",
"arguments": {
"store": "myStore-US",
"browseNodeId": "<browseNodeId>"
}
}From code (Tool API)
curl -X POST https://api.sellersheetai.com/api/v1/tools/customerFeedback_getBrowseNodeReturnTrends \
-H "Authorization: Bearer $SELLERSHEET_API_KEY" \
-H "Content-Type: application/json" \
-d '{"store":"myStore-US","browseNodeId":"<browseNodeId>"}'Early access — the Tool API is open on request, contact us.
Arguments
| Name | Type | Description |
|---|---|---|
storerequired | string | the store ref `<store>-<CC>` (name-country, e.g. 'myStore-US') — one of get_user_context's store_refs, verbatim. |
browseNodeIdrequired | string | Browse node ID from customerFeedback_getItemBrowseNode. |
summarize | boolean | true returns the slim shape (~80 % smaller: flat cat_pct lists plus a computed direction and delta) — use it in AI workflows; default false returns Amazon's raw payload.Default: false |
Result
Every tool answers {notification, data, human_action}; data carries:
data.returnTrends— the Amazon payload; the topics sit one level down under a second returnTrends key (data.returnTrends.returnTrends) in both shapes, as one flat list (NOT split positive/negative). Raw: {browseNodeId, displayName, marketplaceId, countryCode, dateRange: {startDate, endDate}, returnTrends: [TrendTopic]}, TrendTopic = {topic, trendMetrics: [Period]}, one Period per month, newest first = {dateRange, browseNodeMetrics: {occurrencePercentage: {allProducts}}}. Slim: [SlimTrend], SlimTrend = {topic, cat_pct: [float] (the reason's monthly share, newest first), direction: RISING | STABLE | FALLING | null (newest-2-month vs oldest-2-month average, ±10 %; null below 3 reported months once Amazon's zero-padded edge months are trimmed), delta: newest − oldest reported month (positive = that reason's share is growing; null below 2 reported months)}.