CTA Performance × Focus Group

import os, requests, time

WS = os.environ["WISTIA_API_TOKEN"]
MV = os.environ["MAVERA_API_KEY"]
WS_BASE = "https://api.wistia.com"
MV_BASE = "https://app.mavera.io/api/v1"
WS_H = {"Authorization": f"Bearer {WS}", "Accept": "application/json"}
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

# 1. Fetch medias with their customizations (CTAs)
medias = requests.get(f"{WS_BASE}/v1/medias.json", headers=WS_H, params={
    "per_page": 50, "sort_by": "play_count", "sort_direction": 0,
}).json()

cta_videos = []
for media in medias:
    hashed_id = media.get("hashed_id", "")
    customizations = media.get("embed_options", {})
    cta = customizations.get("call_to_action", {}) or customizations.get("postRollCTA", {})

    if not cta:
        continue

    # 2. Get stats for this media
    stats = requests.get(
        f"{WS_BASE}/v1/stats/medias/{hashed_id}.json", headers=WS_H
    ).json()

    play_count = stats.get("play_count", 0)
    cta_clicks = cta.get("clicks", 0)
    cta_ctr = round(cta_clicks / max(play_count, 1) * 100, 2)

    cta_videos.append({
        "name": media.get("name", "Untitled"),
        "hashed_id": hashed_id,
        "duration": media.get("duration", 0),
        "plays": play_count,
        "cta_text": cta.get("text", ""),
        "cta_url": cta.get("url", ""),
        "cta_type": cta.get("type", "text"),
        "cta_time": cta.get("time", "end"),
        "cta_clicks": cta_clicks,
        "cta_ctr": cta_ctr,
    })
    time.sleep(0.2)

print(f"Found {len(cta_videos)} videos with CTAs")

# 3. Sort by CTR for analysis
cta_videos.sort(key=lambda x: x["cta_ctr"])

# 4. Create Focus Group personas
persona_ids = []
for name, desc in [
    ("Impulse Clicker", "Clicks CTAs that create urgency or curiosity. Responds to 'limited time,' 'see inside,' and action verbs. Ignores generic 'learn more' buttons. Mobile-first viewer who needs the CTA to be thumb-friendly."),
    ("Deliberate Researcher", "Only clicks CTAs after watching the full video. Needs the CTA to match the video's promise exactly. Distrusts 'bait-and-switch' where the CTA leads somewhere unrelated. Values specificity over urgency."),
    ("Skeptical Executive", "Senior decision-maker watching to evaluate vendors. Will only click if the CTA offers something they can't get elsewhere — a demo, a calculator, an exclusive report. Ignores 'contact us' and 'subscribe.'"),
    ("Content Binger", "Watches 5+ videos in a session. CTAs interrupt their flow. Will only click if the CTA offers a natural next step in their learning journey, not a sales redirect."),
]  :
    p = requests.post(f"{MV_BASE}/personas", headers=MV_H, json={
        "name": name, "description": desc,
    }).json()
    persona_ids.append(p["id"])
    time.sleep(0.3)

# 5. Build CTA performance summary
cta_block = "\n\n".join(
    f"VIDEO: \"{v['name']}\"\n"
    f"  CTA Text: \"{v['cta_text']}\"\n"
    f"  CTA URL: {v['cta_url']}\n"
    f"  Placement: {v['cta_type']} at {v['cta_time']} | Plays: {v['plays']:,} | "
    f"Clicks: {v['cta_clicks']} | CTR: {v['cta_ctr']}%"
    for v in cta_videos[:8]
)

# 6. Run Focus Group
fg = requests.post(f"{MV_BASE}/focus-groups", headers=MV_H, json={
    "name": "CTA Performance Optimization",
    "persona_ids": persona_ids,
    "questions": [
        f"Review these video CTAs and their click-through rates. For each, explain why you would or wouldn't click:\n\n{cta_block}",
        "Rewrite the 3 lowest-performing CTA texts to maximize YOUR click probability. Explain what you changed and why.",
        "Where in the video should the CTA appear? At the end (post-roll)? Mid-video? As an overlay? Why does placement matter to you?",
        "What CTA format would make you most likely to click: text button, image banner, or interactive annotation? Why?",
        "If you've already decided you're interested in the product, what CTA text would make you convert immediately?",
    ],
    "responses_per_persona": 2,
}).json()

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

# 7. Output
print("\nCTA PERFORMANCE × FOCUS GROUP")
print("=" * 60)
print(f"{'Video':<35} {'CTA Text':<25} {'Plays':>7} {'CTR':>7}")
print("-" * 60)
for v in cta_videos[:8]:
    print(f"  {v['name'][:33]:<35} {v['cta_text'][:23]:<25} {v['plays']:>7,} {v['cta_ctr']:>6.2f}%")

print("\nFOCUS GROUP RESPONSES:")
for resp in fg_data.get("responses", []):
    print(f"\n[{resp.get('persona_name', '?')}] {resp.get('question', '')[:55]}...")
    print(f"  → {resp.get('answer', '')[:400]}")

const WS = process.env.WISTIA_API_TOKEN;
const MV = process.env.MAVERA_API_KEY;
const WS_BASE = "https://api.wistia.com";
const MV_BASE = "https://app.mavera.io/api/v1";
const WS_H = { Authorization: `Bearer ${WS}`, Accept: "application/json" };
const MV_H = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

// 1. Fetch medias with customizations
const medias = await fetch(
  `${WS_BASE}/v1/medias.json?per_page=50&sort_by=play_count&sort_direction=0`, { headers: WS_H }
).then(r => r.json());

const ctaVideos = [];
for (const media of medias) {
  const hashedId = media.hashed_id || "";
  const cta = media.embed_options?.call_to_action || media.embed_options?.postRollCTA;
  if (!cta) continue;

  // 2. Stats
  const stats = await fetch(
    `${WS_BASE}/v1/stats/medias/${hashedId}.json`, { headers: WS_H }
  ).then(r => r.json());

  const playCount = stats.play_count || 0;
  const ctaClicks = cta.clicks || 0;
  ctaVideos.push({
    name: media.name || "Untitled", hashedId,
    duration: media.duration || 0, plays: playCount,
    ctaText: cta.text || "", ctaUrl: cta.url || "",
    ctaType: cta.type || "text", ctaTime: cta.time || "end",
    ctaClicks, ctaCtr: playCount > 0 ? Math.round(ctaClicks / playCount * 10000) / 100 : 0,
  });
  await new Promise(r => setTimeout(r, 200));
}

console.log(`Found ${ctaVideos.length} videos with CTAs`);
ctaVideos.sort((a, b) => a.ctaCtr - b.ctaCtr);

// 3. Personas
const personaIds = [];
for (const [name, desc] of [
  ["Impulse Clicker", "Clicks urgency/curiosity CTAs. Ignores 'learn more.' Mobile-first."],
  ["Deliberate Researcher", "Clicks only after full watch. CTA must match video promise. Values specificity."],
  ["Skeptical Executive", "Senior buyer. Only clicks for demos, calculators, exclusives. Ignores 'contact us.'"],
  ["Content Binger", "Watches 5+ videos. CTAs interrupt flow. Only clicks natural next-step CTAs."],
]) {
  const p = await fetch(`${MV_BASE}/personas`, {
    method: "POST", headers: MV_H,
    body: JSON.stringify({ name, description: desc }),
  }).then(r => r.json());
  personaIds.push(p.id);
  await new Promise(r => setTimeout(r, 300));
}

// 4. CTA summary
const ctaBlock = ctaVideos.slice(0, 8).map(v =>
  `VIDEO: "${v.name}"\n  CTA: "${v.ctaText}" | ${v.ctaType} at ${v.ctaTime} | ` +
  `Plays: ${v.plays.toLocaleString()} | Clicks: ${v.ctaClicks} | CTR: ${v.ctaCtr}%`
).join("\n\n");

// 5. Focus Group
const fg = await fetch(`${MV_BASE}/focus-groups`, {
  method: "POST", headers: MV_H,
  body: JSON.stringify({
    name: "CTA Performance Optimization", persona_ids: personaIds,
    questions: [
      `Review CTAs and CTRs. Would you click each? Why/why not?\n\n${ctaBlock}`,
      "Rewrite the 3 worst CTAs to maximize YOUR clicks. Explain changes.",
      "Best CTA placement: end, mid-video, overlay? Why does it matter to you?",
      "Best format: text button, image banner, or interactive annotation?",
      "If already interested, what CTA text converts you immediately?",
    ],
    responses_per_persona: 2,
  }),
}).then(r => r.json());

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

// 6. Output
console.log("\nCTA PERFORMANCE × FOCUS GROUP");
console.log("=".repeat(60));
ctaVideos.slice(0, 8).forEach(v =>
  console.log(`  ${v.name.slice(0, 33).padEnd(35)} ${v.ctaText.slice(0, 23).padEnd(25)} ` +
    `${String(v.plays.toLocaleString()).padStart(7)} ${(v.ctaCtr + "%").padStart(7)}`)
);

console.log("\nFOCUS GROUP:");
for (const resp of fgData.responses || []) {
  console.log(`\n[${resp.persona_name || "?"}] ${(resp.question || "").slice(0, 55)}...`);
  console.log(`  → ${(resp.answer || "").slice(0, 400)}`);
}