# Customer Segment Observations — Numeric Interval Filter + Secondary-Measure Weighted Mean

> Customer Segment Observations — Numeric Interval Filter + Secondary-Measure Weighted Mean 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).

Filters customer segment observation rows by a numeric interval on a chosen field and computes a secondary-measure weighted mean across up to 200 supplied rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-16-132?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-numeric-interval-filter-secondary-9506ddc8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_iFkzh9_y3Cq5QZfU_hMWu

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-numeric-interval-filter-secondary-9506ddc8 -d '<json body>'
```

Example prompt: I have customer segment data with account_count and revenue_amount for several company groups — can you filter the rows where account_count is between 10 and 50, then compute a weighted mean on revenue_amount? Here are my rows: row-1 group-a 2026-10-01 account_count=10 revenue_amount=1, row-2 group-b 2026-10-02 account_count=20 revenue_amount=2, row-3 group-a 2026-10-03 account_count=15 revenue_amount=3.

## When to prefer this

Choose this endpoint when you have up to 200 customer segment observation rows (with account_count and revenue_amount fields) and need both a numeric interval filter and a secondary-measure weighted mean in a single paid call for $0.01 USDC. It is a local analytical engine with no external lookups, making it fast, deterministic, and private. Prefer it over generic analytics tools when you want two bundled reports cheaply and your data fits within the 200-row limit.

## Known failure modes

- Rows array is empty or missing — validation error returned
- More than 200 rows supplied — request rejected
- Field value not one of 'account_count' or 'revenue_amount' — enum validation failure
- Minimum greater than maximum — may return empty filter result or error
- Null values in the weight or measure fields may cause weighted mean to be undefined or skipped
- Row missing required fields (row_id, company_group, date) — schema validation error
- Date field not matching YYYY-MM-DD pattern — validation error

## How this service works

Customer segment observations — Numeric interval filter + Secondary-measure weighted mean: Numeric interval filter + Secondary-measure weighted mean 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 independent analytical reports using local analytical engines: (1) a numeric interval filter report showing which of the supplied rows fall within the specified minimum/maximum range on the chosen field, and (2) a secondary-measure weighted mean report computing the weighted average of the secondary measure across the filtered subset. No external data is fetched; all computation is performed on the user-supplied rows (up to 200).

## 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/customer-segment-observations-numeric-interval-filter-secondary-9506ddc8/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)