import os, requests
from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
RunReportRequest, Dimension, Metric, DateRange, OrderBy, FilterExpression,
Filter,
)
PROPERTY_ID = os.environ["GA4_PROPERTY_ID"]
MV = os.environ["MAVERA_API_KEY"]
MB = "https://app.mavera.io/api/v1"
MH = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}
client = BetaAnalyticsDataClient()
report = client.run_report(RunReportRequest(
property=f"properties/{PROPERTY_ID}",
dimensions=[Dimension(name="landingPage")],
metrics=[
Metric(name="totalUsers"),
Metric(name="bounceRate"),
Metric(name="engagementRate"),
Metric(name="averageSessionDuration"),
Metric(name="conversions"),
Metric(name="screenPageViews"),
],
date_ranges=[DateRange(start_date="30daysAgo", end_date="today")],
dimension_filter=FilterExpression(filter=Filter(
field_name="landingPage",
string_filter=Filter.StringFilter(
match_type=Filter.StringFilter.MatchType.BEGINS_WITH,
value="/",
),
)),
order_bys=[OrderBy(metric=OrderBy.MetricOrderBy(metric_name="totalUsers"), desc=True)],
limit=50,
))
pages = []
for row in report.rows:
path = row.dimension_values[0].value
users = int(row.metric_values[0].value)
bounce = float(row.metric_values[1].value)
engagement = float(row.metric_values[2].value)
duration = float(row.metric_values[3].value)
conversions = int(row.metric_values[4].value)
views = int(row.metric_values[5].value)
if users < 100:
continue
pages.append({
"path": path, "users": users, "bounce": bounce,
"engagement": engagement, "duration": duration,
"conversions": conversions, "views": views,
"conv_rate": conversions / max(users, 1),
})
needs_refresh = [p for p in pages if p["bounce"] > 0.6 or p["engagement"] < 0.4]
needs_refresh.sort(key=lambda p: p["users"], reverse=True)
BRAND_VOICE_ID = os.environ.get("BRAND_VOICE_ID", "")
AUDIENCE = "B2B marketing directors at mid-market SaaS companies (200–2000 employees)"
print(f"Pages needing refresh: {len(needs_refresh)} of {len(pages)} total\n")
for page in needs_refresh[:5]:
prompt = (
f"Rewrite the landing page copy for this URL path: {page['path']}\n\n"
f"CURRENT PERFORMANCE (last 30 days):\n"
f"- Users: {page['users']}\n"
f"- Bounce rate: {page['bounce']:.0%}\n"
f"- Engagement rate: {page['engagement']:.0%}\n"
f"- Avg session duration: {page['duration']:.0f}s\n"
f"- Conversion rate: {page['conv_rate']:.2%}\n\n"
f"TARGET AUDIENCE: {AUDIENCE}\n\n"
f"Generate:\n"
f"1. New H1 headline (max 10 words)\n"
f"2. Sub-headline (max 20 words)\n"
f"3. 3 benefit bullet points (max 15 words each)\n"
f"4. CTA button text (max 5 words)\n"
f"5. Social proof line (max 15 words)\n\n"
f"The current copy has a {page['bounce']:.0%} bounce rate — the rewrite must hook visitors in 3 seconds."
)
payload = {"prompt": prompt}
if BRAND_VOICE_ID:
payload["brand_voice_id"] = BRAND_VOICE_ID
gen = requests.post(f"{MB}/generations", headers=MH, json=payload).json()
print(f"{'='*50}")
print(f"Page: {page['path']}")
print(f"Users: {page['users']} | Bounce: {page['bounce']:.0%} | Engagement: {page['engagement']:.0%}")
print(f"{'='*50}")
print(gen.get("output", gen.get("content", ""))[:600])
print()
