# Returns Handling Analytics — String Normalisation & Daily Sum Series

> Returns Handling Analytics — String Normalisation & Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).

Runs two local analytical reports on retail returns data: string normalisation of store/group labels and a daily sum time series for returned_units or processing_minutes (up to 200 rows).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-retail-04-027?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/returns-handling-analytics-string-normalisation-daily-sum-series-050b3562
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_BtOzftOp5jmmwjZ6l3hTa

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability returns-handling-analytics-string-normalisation-daily-sum-series-050b3562 -d '<json body>'
```

Example prompt: I have up to 200 rows of returns handling records with row IDs, store groups, dates, returned_units, and processing_minutes — can you normalize the store group strings and give me a daily sum series for returned_units across all those rows?

## When to prefer this

Choose this endpoint when you need both string normalization of retail store/group label fields AND a daily sum time series for returns metrics in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where you want offline, deterministic computation with no external data dependencies. It is not suitable for real-time lookups, predictive analytics, or datasets exceeding 200 rows.

## Known failure modes

- Fewer than 1 row submitted returns a validation error
- More than 200 rows submitted exceeds the row limit and is rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null values in the selected numeric field may affect sum accuracy
- Unrecognized field enum value causes rejection
- Missing required fields (row_id, date, store_group) cause per-row errors

## How this service works

Returns handling — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied returns handling records (returned_units, processing_minutes). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Two analytical reports: (1) a string-normalized version of the store_group labels from the submitted rows, and (2) a daily sum time series for the selected numeric field (returned_units or processing_minutes), aggregating values by date across all submitted rows. Both reports are computed locally with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "store_group",
     "date",
     "returned_units",
     "processing_minutes"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "store_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "returned_units": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "processing_minutes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "store_group": "group-a",
     "returned_units": 10,
     "processing_minutes": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "store_group": "group-b",
     "returned_units": 20,
     "processing_minutes": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "store_group": "group-a",
     "returned_units": 15,
     "processing_minutes": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "store_group": "group-b",
     "returned_units": 30,
     "processing_minutes": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "returned_units",
    "processing_minutes"
   ],
   "type": "string",
   "default": "returned_units"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/returns-handling-analytics-string-normalisation-daily-sum-series-050b3562/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)