Local Business → Focus Group Stimulus

import os, requests, time

YELP = os.environ["YELP_API_KEY"]
MV = os.environ["MAVERA_API_KEY"]
YELP_H = {"Authorization": f"Bearer {YELP}"}
MV_BASE = "https://app.mavera.io/api/v1"
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

# 1. Pull top competitors
CATEGORY = "pizza"
LOCATION = "Brooklyn, NY"

r = requests.get("https://api.yelp.com/v3/businesses/search",
    headers=YELP_H,
    params={"term": CATEGORY, "location": LOCATION, "limit": 10,
            "sort_by": "review_count"})
r.raise_for_status()
competitors = r.json().get("businesses", [])

# 2. Get detailed profiles
profiles = []
for biz in competitors[:6]:
    detail = requests.get(f"https://api.yelp.com/v3/businesses/{biz['id']}",
        headers=YELP_H).json()

    revs = requests.get(f"https://api.yelp.com/v3/businesses/{biz['id']}/reviews",
        headers=YELP_H).json().get("reviews", [])

    profiles.append({
        "name": detail.get("name", ""),
        "rating": detail.get("rating", 0),
        "reviews": detail.get("review_count", 0),
        "price": detail.get("price", "N/A"),
        "categories": ", ".join(c.get("title", "") for c in detail.get("categories", [])),
        "hours": "Open" if not detail.get("is_closed") else "Closed",
        "neighborhood": detail.get("location", {}).get("city", LOCATION),
        "excerpt": revs[0].get("text", "")[:200] if revs else "No reviews",
    })
    time.sleep(0.5)

# 3. Create local consumer personas
CONSUMER_ARCHETYPES = [
    {"name": "Busy Parent", "desc": "Family of 4, ordering takeout 3x/week. Values speed, portion size, kid-friendliness. Budget: $30-50/order."},
    {"name": "Foodie Millennial", "desc": "Late 20s, Instagram-active. Values quality, ambiance, unique menu items. Willing to pay premium."},
    {"name": "Budget College Student", "desc": "NYU student. Eats out daily. Values price, late hours, portion size. Budget: under $15."},
    {"name": "Local Regular", "desc": "Lives in the neighborhood 10+ years. Values consistency, knowing the staff, supporting local. Goes weekly."},
]

persona_ids = []
for arch in CONSUMER_ARCHETYPES:
    p = requests.post(f"{MV_BASE}/personas", headers=MV_H, json={
        "name": f"Yelp Consumer: {arch['name']}",
        "description": f"{arch['desc']} Location: {LOCATION}.",
        "demographic": {"location": LOCATION},
        "psychographic": {"dining_persona": arch["name"]},
    }).json()
    persona_ids.append({"id": p["id"], "name": arch["name"]})
    time.sleep(0.2)

# 4. Build stimulus
competitor_cards = "\n\n".join(
    f"({chr(65+i)}) {p['name']}\n"
    f"   Rating: {p['rating']}/5 ({p['reviews']} reviews) | Price: {p['price']}\n"
    f"   Categories: {p['categories']}\n"
    f"   Neighborhood: {p['neighborhood']}\n"
    f"   Recent review: \"{p['excerpt']}\""
    for i, p in enumerate(profiles)
)

# 5. Focus Group
fg = requests.post(f"{MV_BASE}/focus-groups", headers=MV_H, json={
    "name": f"{CATEGORY.title()} Preference Study — {LOCATION}",
    "persona_ids": [p["id"] for p in persona_ids],
    "questions": [
        {"type": "ranking", "text": f"Rank these {CATEGORY} places from first choice to last:\n\n{competitor_cards}"},
        "Explain why you ranked your #1 choice first. What specific attribute sealed it?",
        "What would make you switch from your current favorite to a new option?",
        "Describe your ideal ordering experience for this category in 2 sentences.",
        "If a new place opened in your neighborhood, what ONE thing would make you try it?",
    ],
    "context": f"Consumer preference study: {CATEGORY} in {LOCATION}.\n\n{competitor_cards}",
    "responses_per_persona": 3,
}).json()

# 6. Poll
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

print(f"=== {CATEGORY.title()} Preference Study — {LOCATION} ===")
for resp in data.get("responses", []):
    persona = next((p["name"] for p in persona_ids if p["id"] == resp.get("persona_id")), "?")
    print(f"\n[{persona}] {resp.get('question','')[:60]}")
    print(f"  → {resp.get('answer','')[:300]}")

const YELP = process.env.YELP_API_KEY;
const MV = process.env.MAVERA_API_KEY;
const YELP_H = { Authorization: `Bearer ${YELP}` };
const MV_BASE = "https://app.mavera.io/api/v1";
const MV_H = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

const CATEGORY = "pizza";
const LOCATION = "Brooklyn, NY";

// 1. Top competitors
const competitors = (await fetch(
  `https://api.yelp.com/v3/businesses/search?term=${CATEGORY}&location=${encodeURIComponent(LOCATION)}&limit=10&sort_by=review_count`,
  { headers: YELP_H }
).then((r) => r.json())).businesses || [];

// 2. Profiles
const profiles = [];
for (const biz of competitors.slice(0, 6)) {
  const detail = await fetch(`https://api.yelp.com/v3/businesses/${biz.id}`, { headers: YELP_H }).then((r) => r.json());
  const revs = await fetch(`https://api.yelp.com/v3/businesses/${biz.id}/reviews`, { headers: YELP_H })
    .then((r) => r.json()).then((d) => d.reviews || []);
  profiles.push({
    name: detail.name, rating: detail.rating, reviews: detail.review_count,
    price: detail.price || "N/A",
    categories: (detail.categories || []).map((c) => c.title).join(", "),
    excerpt: revs[0]?.text?.slice(0, 200) || "No reviews",
  });
  await new Promise((r) => setTimeout(r, 500));
}

// 3. Personas
const archetypes = [
  { name: "Busy Parent", desc: "Family of 4. Values speed, portions, kid-friendly. $30-50." },
  { name: "Foodie Millennial", desc: "Late 20s, Instagram. Quality, ambiance, unique menu." },
  { name: "Budget Student", desc: "Eats out daily. Price, late hours, portions. Under $15." },
  { name: "Local Regular", desc: "10+ years in neighborhood. Consistency, community, weekly." },
];

const personaIds = [];
for (const arch of archetypes) {
  const p = await fetch(`${MV_BASE}/personas`, {
    method: "POST", headers: MV_H,
    body: JSON.stringify({
      name: `Yelp: ${arch.name}`, description: `${arch.desc} Location: ${LOCATION}.`,
      psychographic: { dining_persona: arch.name },
    }),
  }).then((r) => r.json());
  personaIds.push({ id: p.id, name: arch.name });
  await new Promise((r) => setTimeout(r, 200));
}

// 4. Stimulus + Focus Group
const cards = profiles.map((p, i) =>
  `(${String.fromCharCode(65 + i)}) ${p.name}\n   ${p.rating}/5 (${p.reviews}) | ${p.price}\n   "${p.excerpt}"`
).join("\n\n");

const fg = await fetch(`${MV_BASE}/focus-groups`, {
  method: "POST", headers: MV_H,
  body: JSON.stringify({
    name: `${CATEGORY} Preference — ${LOCATION}`,
    persona_ids: personaIds.map((p) => p.id),
    questions: [
      { type: "ranking", text: `Rank these:\n\n${cards}` },
      "Why is your #1 first?",
      "What would make you switch?",
      "Describe your ideal ordering experience.",
      "What ONE thing would make you try a new place?",
    ],
    context: cards,
    responses_per_persona: 3,
  }),
}).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;
}

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