Product Requirements → Focus Group

import os, requests, time

NOTION = os.environ["NOTION_API_KEY"]
MV = os.environ["MAVERA_API_KEY"]
NB = "https://api.notion.com/v1"
MB = "https://app.mavera.io/api/v1"
NH = {
    "Authorization": f"Bearer {NOTION}",
    "Notion-Version": "2022-06-28",
    "Content-Type": "application/json",
}
MH = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

PRD_DB_ID = "your-prd-database-id"

# 1. Query PRD pages in "Review" status
prds = requests.post(f"{NB}/databases/{PRD_DB_ID}/query", headers=NH, json={
    "filter": {"property": "Status", "select": {"equals": "In Review"}},
    "page_size": 5,
}).json().get("results", [])

print(f"Found {len(prds)} PRDs in review")

# 2. Extract PRD content
def get_page_text(page_id):
    texts = []
    cursor = None
    while True:
        params = {"page_size": 100}
        if cursor:
            params["start_cursor"] = cursor
        r = requests.get(f"{NB}/blocks/{page_id}/children", headers=NH, params=params)
        if r.status_code == 429:
            time.sleep(1); continue
        data = r.json()
        for block in data.get("results", []):
            btype = block.get("type", "")
            rt = block.get(btype, {}).get("rich_text", [])
            text = "".join(t.get("plain_text", "") for t in rt)
            if text.strip():
                texts.append(text)
        cursor = data.get("next_cursor")
        if not cursor:
            break
        time.sleep(0.4)
    return "\n".join(texts)

# 3. Create user personas for validation
USER_SEGMENTS = [
    {"name": "Enterprise IT Director", "desc": "Manages 50+ person tech team. Evaluates tools for security, scalability, and ROI. Risk-averse. Needs exec-level justification."},
    {"name": "Startup Founder", "desc": "Wears many hats. Needs fast time-to-value. Price-sensitive but willing to pay for 10x improvements. Values simplicity."},
    {"name": "Marketing Manager (Mid-Market)", "desc": "Runs campaigns for a 200-person company. Juggles 5+ tools. Wants consolidation and better reporting. Reports to VP Marketing."},
    {"name": "Developer (IC)", "desc": "Individual contributor building integrations. Cares about API quality, documentation, and developer experience. Skeptical of 'AI magic' claims."},
    {"name": "Product Analyst", "desc": "Data-driven decision maker. Wants quantitative insights, A/B testing support, and export capabilities. Lives in dashboards."},
]

persona_ids = []
for seg in USER_SEGMENTS:
    p = requests.post(f"{MB}/personas", headers=MH, json={
        "name": f"PRD Review: {seg['name']}",
        "description": seg["desc"],
    }).json()
    persona_ids.append({"id": p["id"], "name": seg["name"]})
    time.sleep(0.3)

print(f"Created {len(persona_ids)} personas")

# 4. Run focus group for each PRD
for prd in prds:
    props = prd.get("properties", {})
    title_parts = props.get("Name", props.get("Title", {})).get("title", [])
    title = "".join(t.get("plain_text", "") for t in title_parts)
    prd_text = get_page_text(prd["id"])

    fg = requests.post(f"{MB}/focus-groups", headers=MH, json={
        "name": f"PRD Review: {title}",
        "persona_ids": [p["id"] for p in persona_ids],
        "questions": [
            f"Here is a product requirements document:\n\n{prd_text[:3000]}\n\nOn a scale of 1-10, how interested would you be in this feature? Explain your rating.",
            "What is the single biggest concern or objection you have about this feature?",
            "What would need to be true for you to adopt this on day one?",
            "How would you describe this feature to a colleague in one sentence?",
            "What existing alternative (if any) do you currently use to solve this problem?",
        ],
        "responses_per_persona": 2,
    }).json()

    # 5. Poll for results
    for _ in range(30):
        time.sleep(5)
        data = requests.get(f"{MB}/focus-groups/{fg['id']}", headers=MH).json()
        if data.get("status") == "completed":
            break

    print(f"\n{'='*60}\nPRD: {title}\n{'='*60}")
    for resp in data.get("responses", []):
        persona_name = next((p["name"] for p in persona_ids if p["id"] == resp.get("persona_id")), "Unknown")
        print(f"\n[{persona_name}] Q: {resp.get('question','')[:80]}...")
        print(f"  A: {resp.get('answer','')[:300]}")

const NOTION = process.env.NOTION_API_KEY;
const MV = process.env.MAVERA_API_KEY;
const NB = "https://api.notion.com/v1";
const MB = "https://app.mavera.io/api/v1";
const NH = {
  Authorization: `Bearer ${NOTION}`,
  "Notion-Version": "2022-06-28",
  "Content-Type": "application/json",
};
const MH = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

const PRD_DB_ID = "your-prd-database-id";

// 1. Query PRDs
const prds = await fetch(`${NB}/databases/${PRD_DB_ID}/query`, {
  method: "POST", headers: NH,
  body: JSON.stringify({
    filter: { property: "Status", select: { equals: "In Review" } },
    page_size: 5,
  }),
}).then(r => r.json()).then(d => d.results || []);

console.log(`Found ${prds.length} PRDs in review`);

// 2. Extract page text
async function getPageText(pageId) {
  const texts = [];
  let cursor = null;
  do {
    const params = new URLSearchParams({ page_size: "100" });
    if (cursor) params.set("start_cursor", cursor);
    const res = await fetch(`${NB}/blocks/${pageId}/children?${params}`, { headers: NH });
    if (res.status === 429) { await new Promise(r => setTimeout(r, 1000)); continue; }
    const data = await res.json();
    for (const block of data.results || []) {
      const rt = block[block.type]?.rich_text || [];
      const text = rt.map(t => t.plain_text).join("");
      if (text.trim()) texts.push(text);
    }
    cursor = data.next_cursor;
    await new Promise(r => setTimeout(r, 400));
  } while (cursor);
  return texts.join("\n");
}

// 3. Create personas
const USER_SEGMENTS = [
  { name: "Enterprise IT Director", desc: "50+ person team. Security, scalability, ROI." },
  { name: "Startup Founder", desc: "Fast time-to-value. Price-sensitive. Simplicity." },
  { name: "Marketing Manager", desc: "Mid-market. Juggles 5+ tools. Wants consolidation." },
  { name: "Developer (IC)", desc: "API quality, docs, DX. Skeptical of AI hype." },
  { name: "Product Analyst", desc: "Data-driven. A/B testing. Dashboards." },
];

const personaIds = [];
for (const seg of USER_SEGMENTS) {
  const p = await fetch(`${MB}/personas`, { method: "POST", headers: MH,
    body: JSON.stringify({ name: `PRD Review: ${seg.name}`, description: seg.desc }),
  }).then(r => r.json());
  personaIds.push({ id: p.id, name: seg.name });
  await new Promise(r => setTimeout(r, 300));
}

// 4. Focus group per PRD
for (const prd of prds) {
  const props = prd.properties || {};
  const titleProp = props.Name || props.Title || {};
  const title = (titleProp.title || []).map(t => t.plain_text).join("") || "Untitled";
  const prdText = await getPageText(prd.id);

  const fg = await fetch(`${MB}/focus-groups`, { method: "POST", headers: MH,
    body: JSON.stringify({
      name: `PRD Review: ${title}`,
      persona_ids: personaIds.map(p => p.id),
      questions: [
        `PRD:\n\n${prdText.slice(0, 3000)}\n\n1-10 interest rating with explanation.`,
        "Biggest concern or objection?",
        "What must be true for day-one adoption?",
        "Describe this feature in one sentence to a colleague.",
        "Current alternative for this problem?",
      ],
      responses_per_persona: 2,
    }),
  }).then(r => r.json());

  // 5. Poll
  let data;
  for (let i = 0; i < 30; i++) {
    await new Promise(r => setTimeout(r, 5000));
    data = await fetch(`${MB}/focus-groups/${fg.id}`, { headers: MH }).then(r => r.json());
    if (data.status === "completed") break;
  }

  console.log(`\n${"=".repeat(60)}\nPRD: ${title}`);
  for (const resp of data.responses || []) {
    const name = personaIds.find(p => p.id === resp.persona_id)?.name || "Unknown";
    console.log(`\n[${name}] Q: ${(resp.question || "").slice(0, 80)}...`);
    console.log(`  A: ${(resp.answer || "").slice(0, 300)}`);
  }
}