# Customer Segment Observations — Exact Row Deduplication + IQR Outlier Flags

> Customer Segment Observations — Exact Row Deduplication + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).

Deduplicates exact rows and flags IQR-based outliers in customer segment observation records containing account_count and revenue_amount fields, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-16-049?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/customer-segment-observations-exact-row-deduplication-iqr-outlier-flags-644798d0
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_QQ3_w2EJ4Z-KxQs4yf9Fl

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 customer-segment-observations-exact-row-deduplication-iqr-outlier-flags-644798d0 -d '<json body>'
```

Example prompt: Can you deduplicate and flag IQR outliers on my customer segment observations? I have rows with company_group, date, account_count, and revenue_amount — analyze the revenue_amount field, up to 200 rows, and give me both reports.

## When to prefer this

Choose this endpoint when you have customer segment observation records with account_count and/or revenue_amount fields and need both duplicate removal and statistical outlier detection in a single low-cost call. Ideal for pre-pipeline data quality checks on datasets up to 200 rows. Prefer this over generic data quality tools when your data is specifically structured around company groups, dates, and segment-level numeric metrics.

## Known failure modes

- Exceeding 200-row limit causes rejection
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) causes validation error
- Invalid date format (not YYYY-MM-DD) causes parsing failure
- Providing fewer than 1 row causes error
- Field value outside allowed numeric range causes rejection
- IQR computation may be unreliable with very small datasets (fewer than 4 rows)

## How this service works

Customer segment observations — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags for supplied customer segment observations records (account_count, revenue_amount). 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) an exact row deduplication report identifying which rows are exact duplicates, and (2) an IQR outlier flagging report marking rows whose selected numeric field (account_count or revenue_amount) falls outside the interquartile range bounds. Both reports are generated locally without external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/customer-segment-observations-exact-row-deduplication-iqr-outlier-flags-644798d0/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)