# Customer Segment Observations — Category Frequencies + Date by Category Pivot

> Customer Segment Observations — Category Frequencies + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).

Runs two local analytical reports on customer segment observation data: category frequency counts and a date-by-category pivot, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-16-110?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/customer-segment-observations-category-frequencies-date-by-category-0f0ba49a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_gON2H6RB04gGPbPu2jAC1

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-category-frequencies-date-by-category-0f0ba49a -d '<json body>'
```

Example prompt: I have a list of up to 200 customer segment observations with company groups, dates, account counts, and revenue amounts — can you run both a category frequency breakdown and a date-by-category pivot on this data using account_count as the metric?

## When to prefer this

Choose this endpoint when you have up to 200 customer segment observation rows with company group and date fields and need two fast, local analytical summaries — category frequency counts and a date-by-category pivot — without any external lookup, prediction, or live data fetch. It is ideal when privacy or data residency matters, since no data leaves the local analytical engine, and when you need both reports in a single low-cost call ($0.01 USDC).

## Known failure modes

- Input rows array is empty or missing — minimum 1 row required
- More than 200 rows supplied — maxItems limit exceeded
- Invalid date format — must match YYYY-MM-DD pattern
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) on any row
- Field enum value not recognized — must be 'account_count' or 'revenue_amount'
- Payment of 0.01 USDC not completed — x402 payment required before response is returned

## How this service works

Customer segment observations — Category frequencies + Date by category pivot: Category frequencies + Date by category pivot 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 derived from the supplied rows: (1) a category frequency table showing how often each company_group value appears, and (2) a date-by-category pivot table aggregating the chosen metric (account_count or revenue_amount) across dates and company groups. No external data is fetched; all computation is local.

## 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-category-frequencies-date-by-category-0f0ba49a/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)