Geographic News → Market-Specific Messaging

import os, requests, time

PG_KEY = os.environ["PERIGON_API_KEY"]
PG_BASE = "https://api.goperigon.com/v1"
MV = os.environ["MAVERA_API_KEY"]
MV_BASE = "https://app.mavera.io/api/v1"
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

PRODUCT = "digital payments platform"
MARKETS = [
    {"country": "GB", "label": "United Kingdom", "currency": "GBP"},
    {"country": "DE", "label": "Germany", "currency": "EUR"},
    {"country": "JP", "label": "Japan", "currency": "JPY"},
]

for market in MARKETS:
    # 1. Fetch local news
    r = requests.get(f"{PG_BASE}/all", params={
        "apiKey": PG_KEY, "q": PRODUCT, "country": market["country"],
        "sortBy": "date", "size": 10,
    })
    if not r.ok:
        print(f"{market['label']}: API error {r.status_code}")
        continue
    articles = r.json().get("articles", [])
    print(f"\n{market['label']}: {len(articles)} articles")

    local_context = "\n".join(
        f"- [{a.get('source',{}).get('name','')}] {a.get('title','')}: {a.get('summary', a.get('description',''))[:200]}"
        for a in articles[:8]
    )

    # 2. Create local personas
    LOCAL_PERSONAS = [
        {"name": f"{market['label']} Early Adopter", "desc": f"Tech-forward consumer in {market['label']}. Uses multiple fintech apps. Price-sensitive but values UX. Local payment habits."},
        {"name": f"{market['label']} Traditional Buyer", "desc": f"Established professional in {market['label']}. Prefers banks. Skeptical of fintech. Values security and regulation compliance."},
        {"name": f"{market['label']} Small Business Owner", "desc": f"SMB owner in {market['label']}. Needs payment processing, invoicing, cross-border. Cost is primary concern."},
    ]
    persona_ids = []
    for lp in LOCAL_PERSONAS:
        p = requests.post(f"{MV_BASE}/personas", headers=MV_H, json={
            "name": lp["name"], "description": lp["desc"],
        }).json()
        persona_ids.append(p["id"])
        time.sleep(0.3)

    # 3. Focus Group with local context
    fg = requests.post(f"{MV_BASE}/focus-groups", headers=MV_H, json={
        "name": f"Market Entry: {market['label']}",
        "persona_ids": persona_ids,
        "questions": [
            f"What matters most when choosing a {PRODUCT} in {market['label']}?",
            f"What local alternatives do you currently use and why?",
            f"What would make you switch to a new {PRODUCT}?",
            f"How important is that the platform operates in {market['currency']}?",
        ],
        "responses_per_persona": 2,
    }).json()

    for _ in range(20):
        time.sleep(5)
        data = requests.get(f"{MV_BASE}/focus-groups/{fg['id']}", headers=MV_H).json()
        if data.get("status") == "completed":
            break

    # 4. Generate localized copy
    fg_summary = "\n".join(
        f"[{r.get('persona_id','')}] {r.get('question','')[:60]} → {r.get('answer','')[:200]}"
        for r in data.get("responses", [])[:12]
    )

    copy = requests.post(f"{MV_BASE}/generations", headers=MV_H, json={
        "prompt": f"Generate localized marketing copy for {PRODUCT} entering {market['label']}.\n\n"
            f"LOCAL NEWS CONTEXT:\n{local_context}\n\n"
            f"FOCUS GROUP INSIGHTS:\n{fg_summary}\n\n"
            "Generate:\n"
            f"1. Hero headline (8 words max) — resonates with {market['label']} values\n"
            "2. Subheadline (20 words) — addresses top local concern\n"
            "3. Three feature bullets — localized benefits, not features\n"
            "4. CTA button text (4 words)\n"
            f"5. Social proof line referencing {market['label']} adoption\n\n"
            f"Currency: {market['currency']}. Tone: trustworthy, local, modern.",
    }).json()

    print(f"\n{'='*60}\nLOCALIZED COPY: {market['label']}\n{'='*60}")
    print(copy.get("output", copy.get("content", ""))[:600])

const PG_KEY = process.env.PERIGON_API_KEY;
const PG_BASE = "https://api.goperigon.com/v1";
const MV = process.env.MAVERA_API_KEY;
const MV_BASE = "https://app.mavera.io/api/v1";
const MV_H = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

const PRODUCT = "digital payments platform";
const MARKETS = [
  { country: "GB", label: "United Kingdom", currency: "GBP" },
  { country: "DE", label: "Germany", currency: "EUR" },
  { country: "JP", label: "Japan", currency: "JPY" },
];

for (const market of MARKETS) {
  // 1. Local news
  const r = await fetch(
    `${PG_BASE}/all?apiKey=${PG_KEY}&q=${encodeURIComponent(PRODUCT)}&country=${market.country}&sortBy=date&size=10`);
  if (!r.ok) { console.log(`${market.label}: error ${r.status}`); continue; }
  const articles = (await r.json()).articles || [];
  console.log(`\n${market.label}: ${articles.length} articles`);

  const localContext = articles.slice(0, 8).map(a =>
    `- [${a.source?.name||""}] ${a.title||""}: ${(a.summary||a.description||"").slice(0,200)}`).join("\n");

  // 2. Local personas
  const personaIds = [];
  for (const lp of [
    { name: `${market.label} Early Adopter`, desc: `Tech-forward in ${market.label}. Multiple fintech apps. Price-sensitive.` },
    { name: `${market.label} Traditional Buyer`, desc: `Established in ${market.label}. Prefers banks. Values security.` },
    { name: `${market.label} SMB Owner`, desc: `SMB in ${market.label}. Payment processing, invoicing, cross-border.` },
  ]) {
    const p = await fetch(`${MV_BASE}/personas`, { method: "POST", headers: MV_H,
      body: JSON.stringify({ name: lp.name, description: lp.desc }),
    }).then(r => r.json());
    personaIds.push(p.id);
    await new Promise(r => setTimeout(r, 300));
  }

  // 3. Focus Group
  const fg = await fetch(`${MV_BASE}/focus-groups`, { method: "POST", headers: MV_H,
    body: JSON.stringify({ name: `Market Entry: ${market.label}`, persona_ids: personaIds,
      questions: [`What matters most for ${PRODUCT} in ${market.label}?`, `Local alternatives?`,
        `What makes you switch?`, `How important is ${market.currency} support?`],
      responses_per_persona: 2 }),
  }).then(r => r.json());

  let data;
  for (let i = 0; i < 20; i++) {
    await new Promise(r => setTimeout(r, 5000));
    data = await fetch(`${MV_BASE}/focus-groups/${fg.id}`, { headers: MV_H }).then(r => r.json());
    if (data.status === "completed") break;
  }

  const fgSummary = (data.responses || []).slice(0, 12)
    .map(r => `${(r.question||"").slice(0,60)} → ${(r.answer||"").slice(0,200)}`).join("\n");

  // 4. Localized copy
  const copy = await fetch(`${MV_BASE}/generations`, { method: "POST", headers: MV_H,
    body: JSON.stringify({ prompt: `Localized copy for ${PRODUCT} in ${market.label}.\n\nNEWS:\n${localContext}\n\nFOCUS GROUP:\n${fgSummary}\n\n1. Hero headline (8 words)\n2. Subheadline (20 words)\n3. Three feature bullets\n4. CTA (4 words)\n5. Social proof for ${market.label}\n\nCurrency: ${market.currency}. Tone: trustworthy, local.` }),
  }).then(r => r.json());

  console.log(`\n${"=".repeat(60)}\nLOCALIZED COPY: ${market.label}\n${"=".repeat(60)}`);
  console.log((copy.output || copy.content || "").slice(0, 600));
}