import os, requests, time
MV = os.environ["MAVERA_API_KEY"]
MV_BASE = "https://app.mavera.io/api/v1"
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}
PRE_ROLL_CANDIDATES = [
{"path": "ads/preroll_a_product_demo.mp4", "label": "Product Demo — Fast Cuts"},
{"path": "ads/preroll_b_testimonial.mp4", "label": "Customer Testimonial — Face First"},
{"path": "ads/preroll_c_problem_hook.mp4", "label": "Problem Hook — Text Overlay"},
{"path": "ads/preroll_d_humor.mp4", "label": "Humor — Unexpected Opening"},
]
# 1. Upload and analyze each candidate
analyses = []
for candidate in PRE_ROLL_CANDIDATES:
upload = requests.post(f"{MV_BASE}/assets",
headers={"Authorization": f"Bearer {MV}"},
files={"file": (
candidate["label"] + ".mp4",
open(candidate["path"], "rb"),
"video/mp4",
)},
).json()
analysis = requests.post(f"{MV_BASE}/video-analysis", headers=MV_H, json={
"asset_id": upload["id"],
"analysis_types": [
"hook_score", "visual_complexity", "text_legibility",
"emotional_arc", "cognitive_load", "pacing",
],
"options": {"focus_window": "0-5s"},
"metadata": {"label": candidate["label"], "format": "pre-roll"},
}).json()
analyses.append({"id": analysis["id"], "label": candidate["label"]})
time.sleep(0.5)
# 2. Poll all analyses
results = []
for a in analyses:
for _ in range(30):
time.sleep(3)
status = requests.get(
f"{MV_BASE}/video-analysis/{a['id']}", headers=MV_H
).json()
if status.get("status") == "completed":
break
r = status.get("results", {})
results.append({
"label": a["label"],
"hook_score": r.get("hook_score", {}).get("score", 0),
"hook_assessment": r.get("hook_score", {}).get("assessment", ""),
"visual_complexity": r.get("visual_complexity", {}).get("score", 0),
"text_legibility": r.get("text_legibility", {}).get("score", 0),
"emotional_trigger": r.get("emotional_arc", {}).get("peak_emotion", "none"),
"cognitive_load": r.get("cognitive_load", {}).get("average", 0),
})
# 3. Create Focus Group personas
persona_ids = []
for name, desc in [
("Impatient Scroller", "25-year-old who skips every ad. Watches YouTube on mobile during commute. Only stops for humor or shock value. Hates sales pitches."),
("Intentional Viewer", "35-year-old who watches ads if they're relevant. Desktop viewer, often in research mode. Will watch 15s if the topic matches their search."),
("Background Listener", "28-year-old who plays YouTube in the background while working. Audio matters more than visual. Will skip if the first sound is a jingle."),
]:
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)
# 4. Focus Group — "Would you skip?"
result_block = "\n\n".join(
f"AD {i+1}: \"{r['label']}\"\n"
f" Hook Score: {r['hook_score']}/100 — {r['hook_assessment']}\n"
f" Visual Complexity: {r['visual_complexity']}/10 | Text Legibility: {r['text_legibility']}/10\n"
f" Emotional Trigger: {r['emotional_trigger']} | Cognitive Load: {r['cognitive_load']}/10"
for i, r in enumerate(results)
)
fg = requests.post(f"{MV_BASE}/focus-groups", headers=MV_H, json={
"name": "Pre-Roll Skip Test",
"persona_ids": persona_ids,
"questions": [
f"You're watching a YouTube video and these pre-roll ads play. For each, answer: Would you SKIP or WATCH? Why?\n\n{result_block}",
"Which ad's first 2 seconds grabbed you? What specifically hooked you?",
"Rewrite the opening line of the weakest ad to make you NOT skip.",
"Rate each ad 1-10 on 'Would I click through to the website?'",
],
"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
print("PRE-ROLL AD SKIP TEST")
print("=" * 60)
for r in results:
skip_predict = "WATCH" if r["hook_score"] > 70 else "LIKELY SKIP" if r["hook_score"] > 45 else "SKIP"
print(f" {r['label']:<45} Hook:{r['hook_score']:>3}/100 → {skip_predict}")
print("\nFOCUS GROUP RESPONSES:")
for resp in data.get("responses", []):
print(f"\n[{resp.get('persona_id', '?')[:20]}] {resp.get('question', '')[:60]}...")
print(f" → {resp.get('answer', '')[:300]}")
