# Marketing Contribution Return – Benchmark Correlation Calculator

> Marketing Contribution Return – Benchmark Correlation Calculator is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Calculates the Pearson correlation between marketing contribution return figures and a set of user-supplied benchmark values, returning a JSON report with formula, units, and stated limitations.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-finance-marketing-return-correlation?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/marketing-contribution-return-benchmark-correlation-calculator-1b4ff5e6
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_sIw-2uB-gBoAjnHfQt1EI

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 marketing-contribution-return-benchmark-correlation-calculator-1b4ff5e6 -d '<json body>'
```

Example prompt: I have 4 periods of marketing data — spends of $5,000, $5,500, $5,000, $5,500 with attributed contributions of $8,000, $8,800, $8,000, $8,800 — and benchmark values of 10, 20, 30, 40. Can you calculate the Pearson correlation between my marketing contribution return and those benchmarks and give me the formula and limitations?

## When to prefer this

Choose this endpoint when you need a bounded, formula-disclosed Pearson correlation between marketing contribution return figures and a user-supplied benchmark series, and you explicitly do not need causal inference, predictive modeling, or live data feeds. It is ideal for audit-ready statistical reports where transparency about formula and limitations is required, and where the analysis is confined strictly to the supplied data.

## Known failure modes

- Fewer than 2 rows supplied — minimum is 2 data points
- Benchmark array length does not match row count — arrays must be aligned
- marketing_spend values of zero or below — exclusiveMinimum of 0 applies
- attributed_contribution or benchmark values outside allowed numeric range
- More than 200 rows or benchmarks supplied — maxItems limit exceeded
- Malformed JSON body returns 400-level error
- Payment not included or insufficient — 0.01 USDC required per call

## How this service works

Marketing contribution return - Benchmark correlation: Calculate Pearson correlation against aligned supplied benchmarks; no causal or predictive claim. Metric: Marketing contribution return. Supplied figures only; returns JSON with formula, units and limitations. One of 50 calculators with 20 analysis modes. No live feed, financial advice or trade execution. 0.01 USDC includes one bounded benchmark correlation report.

## Output

A JSON object containing the Pearson correlation coefficient between the marketing contribution return series and the supplied benchmark values, along with the formula used, units, and explicit limitations (no causal or predictive claims are made). The report is bounded to the supplied figures only.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "attributed_contribution",
     "marketing_spend"
    ],
    "properties": {
     "marketing_spend": {
      "type": "number",
      "default": 5000,
      "maximum": 1000000000000,
      "minimum": 0,
      "description": "Amount in a consistent supplied currency and reporting period",
      "exclusiveMinimum": 0
     },
     "attributed_contribution": {
      "type": "number",
      "default": 8000,
      "maximum": 1000000000000,
      "minimum": -1000000000000,
      "description": "Amount in a consistent supplied currency and reporting period"
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "marketing_spend": 5000,
     "attributed_contribution": 8000
    },
    {
     "marketing_spend": 5500,
     "attributed_contribution": 8800
    },
    {
     "marketing_spend": 5000,
     "attributed_contribution": 8000
    },
    {
     "marketing_spend": 5500,
     "attributed_contribution": 8800
    }
   ],
   "maxItems": 200,
   "minItems": 2
  },
  "benchmarks": {
   "type": "array",
   "items": {
    "type": "number",
    "default": 1,
    "maximum": 1000000000000000000,
    "minimum": -1000000000000000000
   },
   "default": [
    10,
    20,
    30,
    40
   ],
   "maxItems": 200,
   "minItems": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/marketing-contribution-return-benchmark-correlation-calculator-1b4ff5e6/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)