# Brand Mention Inventories — Trailing Mean Series + Two-Measure Correlation

> Brand Mention Inventories — Trailing Mean Series + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).

Computes a trailing moving-average series and a two-measure Pearson/rank correlation between mention_count and source_count for supplied brand mention inventory records (up to 200 rows).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-18-150?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/brand-mention-inventories-trailing-mean-series-two-measure-correlation-130afacf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_56YXgPSu1o_L_wi8klCPp

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 brand-mention-inventories-trailing-mean-series-two-measure-correlation-130afacf -d '<json body>'
```

Example prompt: I have 50 rows of daily brand mention data with mention_count and source_count for two company groups — can you run a trailing mean series (window of 7) on mention_count and also compute the two-measure correlation between mention_count and source_count for all of them?

## When to prefer this

Choose this endpoint when you have brand mention inventory data (with mention_count and source_count fields) and need both a rolling/trailing mean time series AND a correlation analysis between the two measures in a single low-cost call. It is purpose-built for brand monitoring analytics on supplied data with no external lookup, making it ideal for offline or batch statistical reporting on pre-collected brand data.

## Known failure modes

- Fewer than 2 rows supplied — minItems validation failure
- Window size larger than number of rows — insufficient data for trailing mean
- Missing required fields (row_id, date, mention_count, source_count) — schema validation error
- Date strings not matching YYYY-MM-DD pattern — rejected by pattern validator
- More than 200 rows submitted — maxItems exceeded
- Null values in both measure columns — correlation undefined or NaN result

## How this service works

Brand mention inventories — Trailing mean series + Two-measure correlation: Trailing mean series + Two-measure correlation for supplied brand mention inventories records (mention_count, source_count). 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 trailing moving-average time series for the selected primary field (mention_count or source_count) computed with the specified window size, and (2) a two-measure correlation analysis between mention_count and source_count. Results are based entirely on the supplied rows — no external data is fetched.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "company_group",
     "date",
     "mention_count",
     "source_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "mention_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "source_count": 1,
     "company_group": "group-a",
     "mention_count": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_count": 2,
     "company_group": "group-b",
     "mention_count": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_count": 3,
     "company_group": "group-a",
     "mention_count": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_count": 4,
     "company_group": "group-b",
     "mention_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "mention_count",
    "source_count"
   ],
   "type": "string",
   "default": "mention_count"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/brand-mention-inventories-trailing-mean-series-two-measure-correlation-130afacf/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)