Open Rate Prediction

import os, requests, time

MC_KEY = os.environ["MAILCHIMP_API_KEY"]
MC_DC = os.environ["MAILCHIMP_DC"]
MV = os.environ["MAVERA_API_KEY"]
MB = "https://app.mavera.io/api/v1"
MH = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}
MC_BASE = f"https://{MC_DC}.api.mailchimp.com/3.0"
mc_auth = ("anystring", MC_KEY)

r = requests.get(
    f"{MC_BASE}/campaigns",
    auth=mc_auth,
    params={"count": 30, "sort_field": "send_time", "sort_dir": "DESC", "status": "sent"},
)
r.raise_for_status()
campaigns = r.json().get("campaigns", [])

historical = []
for c in campaigns:
    report = c.get("report_summary", {})
    subject = c.get("settings", {}).get("subject_line", "")
    open_rate = report.get("open_rate", 0)
    if subject and open_rate > 0:
        historical.append({"subject": subject, "open_rate": open_rate})

historical.sort(key=lambda x: x["open_rate"], reverse=True)
avg_open = sum(h["open_rate"] for h in historical) / max(len(historical), 1)

history_block = "\n".join(
    f"  {h['open_rate']:.0%} — {h['subject']}"
    for h in historical[:15]
)

NEW_SUBJECTS = os.environ.get("TEST_SUBJECTS", (
    "Your March metrics report is ready|"
    "3 trends your competitors are using right now|"
    "We made a mistake (and fixed it)|"
    "[Name], your account has a new recommendation|"
    "Stop doing this one thing in your campaigns|"
    "The data is in: what worked in Q1|"
    "🔥 New feature drop: AI subject line tester|"
    "Quick question about your workflow|"
    "You're leaving money on the table (proof inside)|"
    "Our CEO's unpopular opinion about email marketing"
)).split("|")

subject_list = "\n".join(f"  {i+1}. {s}" for i, s in enumerate(NEW_SUBJECTS))

PERSONA_IDS = os.environ.get("PREDICT_PERSONA_IDS", "").split(",")
if not PERSONA_IDS[0]:
    for name, desc in [
        ("Mobile Scanner", "Checks email on iPhone during commute. Reads 3-word subjects only. Opens 10% of marketing emails."),
        ("Desktop Power Reader", "Processes email in dedicated blocks. Reads everything. Opens 40% of marketing emails."),
        ("Selective Opener", "Gets 100+ emails/day. Opens only personalized or urgently relevant. 15% marketing open rate."),
        ("Curious Subscriber", "Relatively new subscriber. Opens most emails to evaluate. 60% open rate but declining."),
    ]:
        p = requests.post(f"{MB}/personas", headers=MH, json={"name": name, "description": desc}).json()
        PERSONA_IDS.append(p["id"])
        time.sleep(0.3)

fg = requests.post(f"{MB}/focus-groups", headers=MH, json={
    "name": "Mailchimp: Subject Line Open Rate Prediction",
    "persona_ids": [pid for pid in PERSONA_IDS if pid],
    "questions": [
        f"Rate each subject line on a 1-10 scale for how likely you are to open it (1 = ignore, 10 = open immediately). For each, give the score and a 1-sentence reason:\n{subject_list}",
        "Which 3 subject lines would you DEFINITELY open? Why those three specifically?",
        "Which subject lines would you DEFINITELY ignore or mark as spam? Why?",
        "If you could only open ONE email today and these were all in your inbox, which one wins? What's the deciding factor?",
    ],
    "context": f"""This is a subject line prediction study. Here's the brand's historical performance for context:

Average open rate: {avg_open:.0%}
Recent subject lines (ranked by open rate):
{history_block}

NEW SUBJECT LINES TO TEST:
{subject_list}

Rate honestly based on your email habits. Don't try to be nice — tell us what you'd actually do.""",
    "responses_per_persona": 1,
}).json()

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"Focus Group: {data.get('id')} — {data.get('status')}\n")
for resp in data.get("responses", []):
    print(f"[{resp.get('persona_id','?')}] {resp.get('question','')[:70]}")
    print(f"  → {resp.get('answer','')[:500]}\n")

const MC_KEY = process.env.MAILCHIMP_API_KEY;
const MC_DC = process.env.MAILCHIMP_DC;
const MV = process.env.MAVERA_API_KEY;
const MB = "https://app.mavera.io/api/v1";
const MH = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };
const MC_BASE = `https://${MC_DC}.api.mailchimp.com/3.0`;
const mcAuth = "Basic " + Buffer.from(`anystring:${MC_KEY}`).toString("base64");

const campRes = await fetch(
  `${MC_BASE}/campaigns?count=30&sort_field=send_time&sort_dir=DESC&status=sent`,
  { headers: { Authorization: mcAuth } }
).then((r) => r.json());

const historical = (campRes.campaigns || [])
  .filter((c) => c.settings?.subject_line && (c.report_summary?.open_rate || 0) > 0)
  .map((c) => ({ subject: c.settings.subject_line, openRate: c.report_summary.open_rate }))
  .sort((a, b) => b.openRate - a.openRate);

const avgOpen = historical.reduce((s, h) => s + h.openRate, 0) / (historical.length || 1);
const historyBlock = historical.slice(0, 15).map((h) => `  ${(h.openRate * 100).toFixed(0)}% — ${h.subject}`).join("\n");

const NEW_SUBJECTS = (process.env.TEST_SUBJECTS || "Your March metrics report is ready|3 trends your competitors are using right now|We made a mistake (and fixed it)|[Name], your account has a new recommendation|Stop doing this one thing in your campaigns|The data is in: what worked in Q1|🔥 New feature drop: AI subject line tester|Quick question about your workflow|You're leaving money on the table (proof inside)|Our CEO's unpopular opinion about email marketing").split("|");

const subjectList = NEW_SUBJECTS.map((s, i) => `  ${i + 1}. ${s}`).join("\n");

const personaIds = [];
for (const [name, desc] of [
  ["Mobile Scanner", "iPhone commuter. 3-word subjects only. 10% marketing open rate."],
  ["Desktop Power Reader", "Dedicated email blocks. Reads everything. 40% open rate."],
  ["Selective Opener", "100+ emails/day. Opens only personalized/urgent. 15% open."],
  ["Curious Subscriber", "New subscriber. Opens most emails to evaluate. 60% open."],
]) {
  const p = await fetch(`${MB}/personas`, { method: "POST", headers: MH,
    body: JSON.stringify({ name, description: desc }) }).then((r) => r.json());
  personaIds.push(p.id);
  await new Promise((r) => setTimeout(r, 300));
}

const fg = await fetch(`${MB}/focus-groups`, { method: "POST", headers: MH,
  body: JSON.stringify({
    name: "Subject Line Prediction",
    persona_ids: personaIds,
    questions: [
      `Rate 1-10 likelihood to open each:\n${subjectList}\nScore + 1-sentence reason for each.`,
      "Which 3 would you DEFINITELY open? Why?",
      "Which would you IGNORE or mark spam? Why?",
      "If you could open only ONE today, which wins?",
    ],
    context: `Historical avg open: ${(avgOpen * 100).toFixed(0)}%\nRecent subjects:\n${historyBlock}\n\nNew subjects to test:\n${subjectList}\n\nRate honestly.`,
    responses_per_persona: 1,
  }),
}).then((r) => r.json());

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(`Focus Group: ${data.id} — ${data.status}\n`);
for (const resp of data.responses || []) {
  console.log(`[${resp.persona_id}] ${(resp.question || "").slice(0, 70)}`);
  console.log(`  → ${(resp.answer || "").slice(0, 500)}\n`);
}