# Brand Mention Inventories — String Normalisation + Two-Measure Correlation

> Brand Mention Inventories — String Normalisation + 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 2026-10-16).

Normalises strings and computes two-measure correlation (mention_count vs source_count) for up to 200 rows of brand mention inventory data, producing 2 independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-18-033?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/brand-mention-inventories-string-normalisation-two-measure-correlation-a743758c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_uBCL96wJq1T5xjq_ZJlGm

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-string-normalisation-two-measure-correlation-a743758c -d '<json body>'
```

Example prompt: Can you run string normalisation and a two-measure correlation on this brand mention data — I have up to 50 rows with columns for row_id, company_group, date, mention_count, and source_count — and give me 2 analytical reports?

## When to prefer this

Choose this endpoint when you have brand mention inventory data (mention_count + source_count) for up to 200 rows across one or more company groups and need both string normalisation and a statistical two-measure correlation in a single low-cost call. Prefer it over general-purpose analytics services when you want a lightweight, no-external-lookup, paid-per-call computation with two bundled reports at $0.01 USDC.

## Known failure modes

- Fewer than 1 or more than 200 rows supplied — request rejected
- Missing required fields (row_id, company_group, date, mention_count, source_count) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejection
- All null values for mention_count or source_count — correlation cannot be computed

## How this service works

Brand mention inventories — String normalisation + Two-measure correlation: String normalisation + 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 2 independent analytical reports covering: (1) string-normalised brand mention inventory records, and (2) a two-measure correlation analysis between mention_count and source_count across the supplied rows (up to 200). 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",
     "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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/brand-mention-inventories-string-normalisation-two-measure-correlation-a743758c/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)