Review Text → Brand Voice

Build a Mavera Brand Voice profile from positive Trustpilot review language

Scenario

Your best customers describe your product in their own words on Trustpilot — and those words are often better than anything your marketing team writes. You pull 4-5 star reviews, extract the language patterns, and feed them into Mavera’s Brand Voice engine. The result is a voice profile that mirrors how satisfied customers actually talk about you.

Flow: Trustpilot GET /business-units/{id}/reviews (stars 4-5) → Extract review text → Mavera POST /brand-voices → Customer-grounded voice profile

Architecture

Code

Python

import os, requests, time
from openai import OpenAI

TP_KEY = os.environ["TRUSTPILOT_API_KEY"]
MV = os.environ["MAVERA_API_KEY"]
BU_ID = os.environ["TRUSTPILOT_BU_ID"]
TP_BASE = "https://api.trustpilot.com/v1"
MV_BASE = "https://app.mavera.io/api/v1"
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

# 1. Pull 4-5 star reviews
reviews = []
for stars in [5, 4]:
    page = 1
    while len(reviews) < 100:
        r = requests.get(f"{TP_BASE}/business-units/{BU_ID}/reviews",
            params={"apikey": TP_KEY, "stars": stars, "perPage": 50, "page": page,
                     "orderBy": "createdat.desc"})
        if r.status_code == 429:
            time.sleep(2)
            continue
        r.raise_for_status()
        data = r.json()
        batch = data.get("reviews", [])
        if not batch:
            break
        reviews.extend(batch)
        page += 1
        time.sleep(0.2)

# 2. Extract review text
samples = []
for rev in reviews:
    title = rev.get("title", "")
    text = rev.get("text", "")
    stars = rev.get("stars", 0)
    if text and len(text) > 50:
        samples.append(f"[{stars}★] {title}\n{text}")

# 3. Create Brand Voice
combined = "\n\n---\n\n".join(samples[:20])

bv = requests.post(f"{MV_BASE}/brand-voices", headers=MV_H, json={
    "name": "Trustpilot Customer Voice",
    "samples": [combined],
}).json()
print(f"Brand Voice: {bv['id']}")

# 4. Wait for processing
time.sleep(3)
detail = requests.get(f"{MV_BASE}/brand-voices/{bv['id']}", headers=MV_H).json()
print(f"Status: {detail.get('status', 'unknown')}")

# 5. Test generation
mavera = OpenAI(api_key=MV, base_url=MV_BASE)
test = mavera.responses.create(model="mavera-1",
    input=[{"role": "user", "content": "Write a 100-word homepage hero paragraph."}],
    extra_body={"brand_voice_id": bv["id"]})
print(f"\n{test.output[0].content[0].text}")

const OpenAI = require("openai").default;
const TP_KEY = process.env.TRUSTPILOT_API_KEY;
const MV = process.env.MAVERA_API_KEY;
const BU_ID = process.env.TRUSTPILOT_BU_ID;
const TP_BASE = "https://api.trustpilot.com/v1";
const MV_BASE = "https://app.mavera.io/api/v1";
const MV_H = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

// 1. Pull 4-5 star reviews
const reviews = [];
for (const stars of [5, 4]) {
  let page = 1;
  while (reviews.length < 100) {
    const res = await fetch(
      `${TP_BASE}/business-units/${BU_ID}/reviews?apikey=${TP_KEY}&stars=${stars}&perPage=50&page=${page}&orderBy=createdat.desc`
    );
    if (res.status === 429) { await new Promise((r) => setTimeout(r, 2000)); continue; }
    if (!res.ok) throw new Error(`Trustpilot ${res.status}`);
    const batch = (await res.json()).reviews || [];
    if (!batch.length) break;
    reviews.push(...batch);
    page++;
    await new Promise((r) => setTimeout(r, 200));
  }
}

// 2. Extract text
const samples = reviews
  .filter((r) => r.text && r.text.length > 50)
  .map((r) => `[${r.stars}★] ${r.title || ""}\n${r.text}`)
  .slice(0, 20);

// 3. Brand Voice
const bv = await fetch(`${MV_BASE}/brand-voices`, {
  method: "POST", headers: MV_H,
  body: JSON.stringify({ name: "Trustpilot Customer Voice", samples: [samples.join("\n\n---\n\n")] }),
}).then((r) => r.json());
console.log(`Brand Voice: ${bv.id}`);

// 4. Test
await new Promise((r) => setTimeout(r, 3000));
const mavera = new OpenAI({ apiKey: MV, baseURL: MV_BASE });
const test = await mavera.responses.create({
  model: "mavera-1",
  input: [{ role: "user", content: "Write a 100-word homepage hero paragraph." }],
  extra_body: { brand_voice_id: bv.id },
});
console.log(test.output[0].content[0].text);

Example Output

Brand Voice: bv_tp_cust_4k7m (status: ready)

We built this because we were tired of guessing. Tired of launching campaigns
and hoping the message landed. Our customers — from two-person startups to
Fortune 500 marketing teams — tell us the same thing: "It just works."
Set up takes minutes. Your first insight comes before lunch. And every piece
of content you create from here carries the voice your audience already trusts.

Error Handling

API key vs OAuth

Public review endpoints use ?apikey={key}. Business/private endpoints (reply, flag) require OAuth 2.0. Use OAuth for Job 5 (review responses).

Star filter

Pass stars as a query param. For multiple stars, make separate requests (Trustpilot doesn’t support stars=4,5 in a single call).

Short reviews add noise

One-line reviews like “Great service!” don’t contribute meaningful voice data. Filter reviews under 50 characters.