# Customer Segment Observations — String Normalisation & Category Frequencies

> Customer Segment Observations — 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).

Performs string normalisation and category frequency analysis on customer segment observation records (account_count, revenue_amount) for up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-16-024?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-category-frequencies-cdbb9fb4
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_uGVW7ioRSZiH-Wuj9BO8n

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-category-frequencies-cdbb9fb4 -d '<json body>'
```

Example prompt: Can you run string normalisation and category frequency analysis on my customer segment observations? I have 4 rows: row-1 on 2026-10-01 for group-a with 10 accounts and $1 revenue, row-2 on 2026-10-02 for group-b with 20 accounts and $2 revenue, row-3 on 2026-10-03 for group-a with 15 accounts and $3 revenue, and row-4 on 2026-10-04 for group-b with 30 accounts and $4 revenue.

## When to prefer this

Choose this endpoint when you need both string normalisation and category frequency analysis on customer segment data (account_count, revenue_amount) in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where you want two complementary local analytical reports without requiring external lookups, predictions, or live data connections. Prefer this over general-purpose analytics tools when working specifically with company-group-segmented customer observation records and cost efficiency ($0.01 per call) is a priority.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) causes rejection
- Invalid date format (non-YYYY-MM-DD) triggers a pattern validation error
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array returns an error
- Payment failure (insufficient USDC) prevents execution

## How this service works

Customer segment observations — String normalisation + Category frequencies: String normalisation + Category frequencies 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

Returns two analytical reports: (1) a string normalisation report that standardizes the company_group and other string fields across the supplied rows, and (2) a category frequency report showing the distribution and counts of categorical values (such as company_group) along with summaries of numeric fields (account_count, revenue_amount) for up to 200 input rows.

## 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-category-frequencies-cdbb9fb4/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)