# Customer Segment Observations — String Normalisation + Exact Row Deduplication

> Customer Segment Observations — String Normalisation + Exact Row Deduplication is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).

Normalises strings and deduplicates exact rows in customer segment observation records containing account counts and revenue amounts, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-16-020?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/customer-segment-observations-string-normalisation-exact-row-1b49f19c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Ojx2gpVgbWt5ZLeRmFKnF

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-string-normalisation-exact-row-1b49f19c -d '<json body>'
```

Example prompt: Can you clean up my customer segment data? I have about 150 rows with fields like row_id, company_group, date, account_count, and revenue_amount — please run string normalisation and exact row deduplication on them and give me both reports.

## When to prefer this

Choose this endpoint when you need lightweight, offline data quality operations — specifically string normalisation and exact row deduplication — on customer segment observation data (account_count, revenue_amount per company_group and date) for up to 200 rows. It is ideal when you do not need live lookups, predictions, or external enrichment, and when you want two focused reports at low cost ($0.01 USDC). Prefer alternatives if you need fuzzy deduplication, probabilistic matching, or more than 200 rows processed at once.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) causes row rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- account_count or revenue_amount outside [-1e12, 1e12] range rejected
- Empty rows array returns an error
- Payment failure or insufficient USDC balance prevents processing

## How this service works

Customer segment observations — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication 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: one covering string normalisation results (e.g. standardised company_group values) and one covering exact row deduplication results (identifying and removing duplicate records), applied to the supplied customer segment observation rows (up to 200 rows with account_count and revenue_amount fields).

## 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/customer-segment-observations-string-normalisation-exact-row-1b49f19c/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)