# TradepilotUSA Buyer Persona Generator

> TradepilotUSA Buyer Persona Generator is a paid API for AI agents from www.tradepilotusa.com, paid per call via x402, $0.25/call, status unknown (last checked 2026-10-02).

Generates detailed buyer persona hypotheses from a source text and optional audience/brief context using AI analysis

## Facts

- Endpoint: POST https://www.tradepilotusa.com/api/agent-commerce/v1/services/buyer_persona/execute?utm_source=zero.xyz
- Price: $0.25/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/tradepilotusa-buyer-persona-generator-35ffff56
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_LwlHJ68JkW9TJHTHs0eLK

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 tradepilotusa-buyer-persona-generator-35ffff56 -d '<json body>'
```

Example prompt: Based on this market research brief and source text I have about our residential door installation company's operations, generate buyer persona hypotheses targeting operations managers focused on scheduling efficiency — the brief is 'We need to reduce missed consultations for a two-person installation crew' and the source text is the full interview transcript I'll provide.

## When to prefer this

Choose this endpoint when you need AI-generated, hypothesis-driven buyer persona profiles derived directly from your own source content (e.g., interview notes, briefs, survey data, business descriptions) rather than generic market data lookups. It is especially useful when you want structured persona outputs with explicit assumptions and evidence gaps flagged for human review, supporting marketing strategy, sales enablement, or product positioning workflows within a business operations context.

## Known failure modes

- Source text below 20 characters minimum returns validation error
- Brief below 10 characters minimum returns validation error
- Source text exceeding 32,000 characters limit returns payload too large error
- Audience field exceeding 500 characters returns validation error
- Malformed JSON body returns 400 bad request
- Insufficient USDC balance or failed x402 payment returns 402 payment required
- Service unavailability returns 503 or timeout

## How this service works

Build explicitly labeled persona hypotheses from supplied evidence, avoiding sensitive personal profiling. Uses buyer-supplied information only; no external research or outbound actions. Returns a draft for human review.

## Output

Returns a structured JSON object containing a task label, a brief summary of the personas generated, a detailed artifact with markdown-formatted persona profiles (including role, primary concerns, team structure, and challenges), provenance metadata (source, generation timestamp, whether external research was performed), a request ID, a list of assumptions made during generation, identified evidence gaps that may require further research, and a flag indicating whether human review is recommended.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "brief": {
   "type": "string",
   "maxLength": 12000,
   "minLength": 10
  },
  "audience": {
   "type": "string",
   "maxLength": 500
  },
  "source_text": {
   "type": "string",
   "maxLength": 32000,
   "minLength": 20
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "task": "buyer_persona",
  "summary": "Developed persona hypotheses for an operations manager at a residential door installation company focused on improving consultation scheduling. Personas emphasize interests in scheduling efficiency an",
  "artifact": "Illustrative excerpt from a synthetic provider check:\n## Persona Hypotheses for Residential Entry Door Installation Operations Manager\n\n### Persona 1: Operations Manager Focused on Scheduling Efficiency\n- **Role:** Operations Manager at a residential door installation company\n- **Primary Concern:** Improving consultation scheduling to reduce missed appointments\n- **Team Structure:** Oversees a two-person installation crew\n- **Current Challenge:** Inefficiencies in scheduling leading to missed consultations\n- **Interest:** Open to a scheduling-proce",
  "provenance": {
   "source": "buyer_supplied",
   "generated_at": "2026-09-22T14:40:12.827Z",
   "external_research_performed": false
  },
  "request_id": "example_buyer_persona",
  "assumptions": [
   "The operations manager is the primary stakeholder for scheduling improvements.",
   "The two-person crew size influences scheduling complexity."
  ],
  "evidence_gaps": [
   "Budget allocated for scheduling improvements.",
   "Timeline or urgency for implementing changes."
  ],
  "requires_human_review": true
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tradepilotusa-buyer-persona-generator-35ffff56/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from www.tradepilotusa.com](https://www.zero.xyz/host/www.tradepilotusa.com/llms.txt)