import os, requests, time
from google.ads.googleads.client import GoogleAdsClient
from collections import defaultdict
MV = os.environ["MAVERA_API_KEY"]
CUSTOMER_ID = os.environ["GOOGLE_ADS_CUSTOMER_ID"]
client = GoogleAdsClient.load_from_env()
ga_service = client.get_service("GoogleAdsService")
query = """
SELECT
auction_insights.display_domain,
metrics.auction_insight_search_impression_share,
metrics.auction_insight_search_overlap_rate,
metrics.auction_insight_search_outranking_share,
metrics.auction_insight_search_position_above_rate,
metrics.auction_insight_search_top_impression_percentage
FROM auction_insights
WHERE segments.date DURING LAST_30_DAYS
"""
response = ga_service.search(customer_id=CUSTOMER_ID, query=query)
competitors = defaultdict(lambda: {
"impression_share": [], "overlap_rate": [], "outranking_share": [],
"position_above_rate": [], "top_impression_pct": [],
})
for row in response:
domain = row.auction_insights.display_domain
m = row.metrics
competitors[domain]["impression_share"].append(m.auction_insight_search_impression_share)
competitors[domain]["overlap_rate"].append(m.auction_insight_search_overlap_rate)
competitors[domain]["outranking_share"].append(m.auction_insight_search_outranking_share)
competitors[domain]["position_above_rate"].append(m.auction_insight_search_position_above_rate)
competitors[domain]["top_impression_pct"].append(m.auction_insight_search_top_impression_percentage)
def avg(lst):
return sum(lst) / len(lst) if lst else 0
comp_summary = []
for domain, metrics in competitors.items():
if domain == "Your domain":
continue
comp_summary.append({
"domain": domain,
"impression_share": avg(metrics["impression_share"]),
"overlap_rate": avg(metrics["overlap_rate"]),
"outranking_share": avg(metrics["outranking_share"]),
"position_above_rate": avg(metrics["position_above_rate"]),
"top_impression_pct": avg(metrics["top_impression_pct"]),
})
comp_summary.sort(key=lambda c: c["overlap_rate"], reverse=True)
top_competitors = comp_summary[:5]
print(f"Top {len(top_competitors)} competitors by auction overlap:\n")
for c in top_competitors:
print(f" {c['domain']}: overlap {c['overlap_rate']:.1%}, "
f"outranking {c['outranking_share']:.1%}, "
f"pos above {c['position_above_rate']:.1%}")
for comp in top_competitors:
prompt = f"""Generate a competitive battle card for {comp['domain']}.
GOOGLE ADS AUCTION DATA (last 30 days):
- Impression share: {comp['impression_share']:.1%}
- Overlap rate with us: {comp['overlap_rate']:.1%} (how often we compete)
- They outrank us: {comp['outranking_share']:.1%} of the time
- They appear above us: {comp['position_above_rate']:.1%} of the time
- Their top impression %: {comp['top_impression_pct']:.1%}
Research this competitor and produce:
1. Company overview (funding, size, positioning)
2. Their strengths (what they do well)
3. Their weaknesses (where we win)
4. Pricing intelligence (if available)
5. Common objections when competing against them
6. Killer discovery questions for reps
7. Landmine questions to watch for
8. Why customers switch from them to us
9. Recommended ad copy adjustments when competing in the same auction"""
card = requests.post(
"https://app.mavera.io/api/v1/mave/chat",
headers={"Authorization": f"Bearer {MV}", "Content-Type": "application/json"},
json={"message": prompt},
).json()
print(f"\n{'='*60}")
print(f"BATTLE CARD: {comp['domain']}")
print(f"Overlap: {comp['overlap_rate']:.1%} | They outrank us: {comp['outranking_share']:.1%}")
print(f"{'='*60}")
print(card.get("content", "")[:1200])
print(f"Sources: {len(card.get('sources', []))}")
time.sleep(1)
