# Customer Segment Observations — Record Quality Audit, String Normalisation & Category Frequencies

> Customer Segment Observations — Record Quality Audit, String Normalisation & Category Frequencies 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).

Runs three analytical reports (record quality audit, string normalisation, and category frequencies) on up to 200 rows of customer segment observation data containing account counts and revenue amounts.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-16-195?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-record-quality-audit-string-434cf16b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_RwEWGwOVSl1OGe6jQKZWH

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-record-quality-audit-string-434cf16b -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and category frequency report on my customer segment data? I have rows with fields: row_id, company_group (like 'group-a', 'group-b'), date (e.g. 2026-10-01), account_count, and revenue_amount — up to 200 rows total.

## When to prefer this

Choose this endpoint when you need lightweight, offline data quality and profiling reports on small-to-medium customer segment datasets (up to 200 rows) without sending data to external live services. It is ideal for pre-processing pipelines where you want record quality auditing, string normalisation, and category frequency summaries bundled into a single low-cost call ($0.01 USDC for all three reports).

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) causes row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern trigger pattern validation errors
- Numeric values outside ±1,000,000,000,000 bounds are rejected
- Empty rows array returns an error
- Payment failure via x402 protocol prevents execution

## How this service works

Customer segment observations — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied customer segment observations records (account_count, revenue_amount). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Three independent analytical reports: (1) a record quality audit flagging missing values, type mismatches, or out-of-range entries; (2) normalised string representations of text fields like company_group; and (3) category frequency counts showing how often each distinct category value appears across the supplied rows. All computed 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/customer-segment-observations-record-quality-audit-string-434cf16b/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)