Email Stats by Device/Geography → Persona Refinement

import os, requests, time
from collections import defaultdict
from datetime import datetime, timedelta

SG = os.environ["SENDGRID_API_KEY"]
MV = os.environ["MAVERA_API_KEY"]
SG_BASE = "https://api.sendgrid.com/v3"
MB = "https://app.mavera.io/api/v1"
SG_H = {"Authorization": f"Bearer {SG}"}
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

# 1. List recent single sends
sends = requests.get(f"{SG_BASE}/marketing/singlesends",
    headers=SG_H, params={"page_size": 25}).json().get("result", [])

completed = [s for s in sends if s.get("status") == "triggered"]

# 2. Pull stats with breakdowns
device_geo = defaultdict(lambda: {"opens": 0, "clicks": 0, "sends": 0})

for send in completed[:15]:
    sid = send["id"]
    stats = requests.get(f"{SG_BASE}/marketing/stats/singlesends/{sid}",
        headers=SG_H, params={
            "aggregated_by": "total",
            "start_date": (datetime.now() - timedelta(days=90)).strftime("%Y-%m-%d"),
            "end_date": datetime.now().strftime("%Y-%m-%d"),
        })
    if stats.status_code == 429:
        time.sleep(2)
        stats = requests.get(f"{SG_BASE}/marketing/stats/singlesends/{sid}",
            headers=SG_H, params={
                "aggregated_by": "total",
                "start_date": (datetime.now() - timedelta(days=90)).strftime("%Y-%m-%d"),
                "end_date": datetime.now().strftime("%Y-%m-%d"),
            })
    stats.raise_for_status()
    data = stats.json().get("results", [{}])

    for entry in data:
        metrics = entry.get("stats", {})
        device_geo["all"]["opens"] += metrics.get("opens", 0)
        device_geo["all"]["clicks"] += metrics.get("clicks", 0)
        device_geo["all"]["sends"] += metrics.get("delivered", 0)

    time.sleep(0.15)

# 3. Pull global stats with device/geo breakdowns
global_stats = requests.get(f"{SG_BASE}/stats",
    headers=SG_H, params={
        "start_date": (datetime.now() - timedelta(days=30)).strftime("%Y-%m-%d"),
        "end_date": datetime.now().strftime("%Y-%m-%d"),
        "aggregated_by": "month",
    }).json()

browsers = requests.get(f"{SG_BASE}/browsers/stats",
    headers=SG_H, params={
        "start_date": (datetime.now() - timedelta(days=30)).strftime("%Y-%m-%d"),
        "end_date": datetime.now().strftime("%Y-%m-%d"),
        "aggregated_by": "month",
    })
browser_data = browsers.json() if browsers.ok else []

# 4. Analyze patterns with Mave
stats_summary = f"""Email Performance (last 30 days):
Total sends: {device_geo['all']['sends']}
Total opens: {device_geo['all']['opens']}
Total clicks: {device_geo['all']['clicks']}
Open rate: {device_geo['all']['opens'] / max(device_geo['all']['sends'], 1):.1%}
CTR: {device_geo['all']['clicks'] / max(device_geo['all']['sends'], 1):.1%}

Browser breakdown: {browser_data[:3] if browser_data else 'N/A'}
Single sends analyzed: {len(completed[:15])}"""

analysis = requests.post(f"{MB}/mave/chat", headers=MV_H, json={
    "message": f"""Analyze this SendGrid email performance data and produce persona
behavioral profiles.

{stats_summary}

For each inferred segment, describe:
1) Likely device preference (mobile vs desktop)
2) Content format preference (scannable vs detailed)
3) Optimal send time window
4) Subject line style that works
5) CTA format preference

Group into 3 behavioral personas: Mobile-First, Desktop-Focused, Hybrid."""
}).json()

print("=== Behavioral Analysis ===")
print(analysis.get("content", "")[:1500])

# 5. Create behavioral personas
BEHAVIOR_PROFILES = [
    {"name": "SG: Mobile-First Reader",
     "desc": "Opens on mobile (60%+). Prefers scannable content, single CTA, short subject lines.",
     "psych": {"device": "mobile", "format": "scannable", "cta": "single_button"}},
    {"name": "SG: Desktop Focused Reader",
     "desc": "Opens on desktop during business hours. Prefers detailed content, multiple links, professional tone.",
     "psych": {"device": "desktop", "format": "detailed", "cta": "text_links"}},
    {"name": "SG: Hybrid Multi-Device",
     "desc": "Mixed device usage. Opens on mobile, clicks through on desktop. Needs responsive design.",
     "psych": {"device": "hybrid", "format": "responsive", "cta": "progressive"}},
]

for profile in BEHAVIOR_PROFILES:
    r = requests.post(f"{MB}/personas", headers=MV_H, json={
        "name": profile["name"],
        "description": f"{profile['desc']} Based on {device_geo['all']['sends']} sends analyzed. {analysis.get('content', '')[:200]}",
        "psychographic": profile["psych"],
    })
    r.raise_for_status()
    print(f"Created: {profile['name']} → {r.json()['id']}")
    time.sleep(0.3)

const SG = process.env.SENDGRID_API_KEY;
const MV = process.env.MAVERA_API_KEY;
const SG_BASE = "https://api.sendgrid.com/v3";
const MB = "https://app.mavera.io/api/v1";
const sgH = { Authorization: `Bearer ${SG}` };
const mvH = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

// 1. List recent single sends
const { result: sends } = await fetch(`${SG_BASE}/marketing/singlesends?page_size=25`,
  { headers: sgH }).then(r => r.json());

const completed = (sends || []).filter(s => s.status === "triggered");
const totals = { opens: 0, clicks: 0, sends: 0 };

// 2. Pull stats
const now = new Date();
const ago90 = new Date(now - 90 * 86400000).toISOString().slice(0, 10);
const today = now.toISOString().slice(0, 10);

for (const send of completed.slice(0, 15)) {
  let res = await fetch(
    `${SG_BASE}/marketing/stats/singlesends/${send.id}?aggregated_by=total&start_date=${ago90}&end_date=${today}`,
    { headers: sgH });
  if (res.status === 429) {
    await new Promise(r => setTimeout(r, 2000));
    res = await fetch(
      `${SG_BASE}/marketing/stats/singlesends/${send.id}?aggregated_by=total&start_date=${ago90}&end_date=${today}`,
      { headers: sgH });
  }
  const data = await res.json();
  for (const entry of data.results || []) {
    const s = entry.stats || {};
    totals.opens += s.opens || 0;
    totals.clicks += s.clicks || 0;
    totals.sends += s.delivered || 0;
  }
  await new Promise(r => setTimeout(r, 150));
}

// 3. Browser stats
const ago30 = new Date(now - 30 * 86400000).toISOString().slice(0, 10);
const browserRes = await fetch(
  `${SG_BASE}/browsers/stats?start_date=${ago30}&end_date=${today}&aggregated_by=month`,
  { headers: sgH });
const browserData = browserRes.ok ? await browserRes.json() : [];

// 4. Mave analysis
const analysis = await fetch(`${MB}/mave/chat`, {
  method: "POST", headers: mvH,
  body: JSON.stringify({
    message: `Analyze SendGrid email data and produce persona behavioral profiles.
Total sends: ${totals.sends}, Opens: ${totals.opens}, Clicks: ${totals.clicks}
Open rate: ${(totals.opens / Math.max(totals.sends, 1) * 100).toFixed(1)}%
CTR: ${(totals.clicks / Math.max(totals.sends, 1) * 100).toFixed(1)}%
Single sends: ${completed.slice(0, 15).length}

Group into 3 behavioral personas: Mobile-First, Desktop-Focused, Hybrid.
For each: device preference, content format, send time, subject line style, CTA format.`,
  }),
}).then(r => r.json());

console.log("=== Behavioral Analysis ===");
console.log((analysis.content || "").slice(0, 1500));

// 5. Create behavioral personas
const profiles = [
  { name: "SG: Mobile-First Reader",
    desc: "Opens on mobile (60%+). Scannable content, single CTA, short subjects.",
    psych: { device: "mobile", format: "scannable", cta: "single_button" } },
  { name: "SG: Desktop Focused Reader",
    desc: "Desktop during business hours. Detailed content, multiple links, professional tone.",
    psych: { device: "desktop", format: "detailed", cta: "text_links" } },
  { name: "SG: Hybrid Multi-Device",
    desc: "Mixed devices. Opens mobile, clicks desktop. Needs responsive design.",
    psych: { device: "hybrid", format: "responsive", cta: "progressive" } },
];

for (const profile of profiles) {
  const res = await fetch(`${MB}/personas`, {
    method: "POST", headers: mvH,
    body: JSON.stringify({
      name: profile.name,
      description: `${profile.desc} Based on ${totals.sends} sends. ${(analysis.content || "").slice(0, 200)}`,
      psychographic: profile.psych,
    }),
  });
  const persona = await res.json();
  console.log(`Created: ${profile.name} → ${persona.id}`);
  await new Promise(r => setTimeout(r, 300));
}