Display/YouTube Placement Analysis

import os, requests
from google.ads.googleads.client import GoogleAdsClient

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
        group_placement_view.display_name,
        group_placement_view.target_url,
        group_placement_view.placement_type,
        metrics.impressions,
        metrics.clicks,
        metrics.conversions,
        metrics.cost_micros,
        metrics.ctr
    FROM group_placement_view
    WHERE segments.date DURING LAST_30_DAYS
        AND metrics.impressions > 100
    ORDER BY metrics.conversions DESC
    LIMIT 50
"""

response = ga_service.search(customer_id=CUSTOMER_ID, query=query)

placements = []
for row in response:
    gpv = row.group_placement_view
    m = row.metrics
    placements.append({
        "name": gpv.display_name,
        "url": gpv.target_url,
        "type": gpv.placement_type.name,
        "impressions": m.impressions,
        "clicks": m.clicks,
        "conversions": m.conversions,
        "cost": m.cost_micros / 1_000_000,
        "ctr": m.ctr,
    })

top_converting = [p for p in placements if p["conversions"] > 0]
bottom_spend = sorted(
    [p for p in placements if p["conversions"] == 0],
    key=lambda p: -p["cost"]
)[:10]

placement_block = "\n".join(
    f"- [{p['type']}] {p['name']} ({p['url']}) — conv: {p['conversions']:.0f}, CTR: {p['ctr']:.2%}, cost: ${p['cost']:.2f}"
    for p in top_converting[:25]
)

waste_block = "\n".join(
    f"- [{p['type']}] {p['name']} — $0 conversions, spent ${p['cost']:.2f}, {p['impressions']} impressions"
    for p in bottom_spend
)

mave = requests.post(
    "https://app.mavera.io/api/v1/mave/chat",
    headers={"Authorization": f"Bearer {MV}", "Content-Type": "application/json"},
    json={"message": f"""Analyze these Google Display/YouTube placements and provide strategic recommendations.

TOP CONVERTING PLACEMENTS ({len(top_converting)}):
{placement_block}

TOP WASTED SPEND (0 conversions):
{waste_block}

Produce:
1. Content themes that drive conversions (group placements by topic/category)
2. Which YouTube channels or site categories perform best and why
3. Recommended placement exclusions (categories burning budget)
4. Content partnership opportunities (sites worth direct deals)
5. Audience insight: what do converting placements tell us about our buyer?"""},
).json()

print("--- Placement Analysis ---")
print(mave.get("content", "")[:2500])

const DEV_TOKEN = process.env.GOOGLE_ADS_DEVELOPER_TOKEN;
const ACCESS_TOKEN = process.env.GOOGLE_ADS_ACCESS_TOKEN;
const CUSTOMER_ID = process.env.GOOGLE_ADS_CUSTOMER_ID;
const MV = process.env.MAVERA_API_KEY;

const gaql = `
  SELECT group_placement_view.display_name, group_placement_view.target_url,
    group_placement_view.placement_type, metrics.impressions, metrics.clicks,
    metrics.conversions, metrics.cost_micros, metrics.ctr
  FROM group_placement_view
  WHERE segments.date DURING LAST_30_DAYS AND metrics.impressions > 100
  ORDER BY metrics.conversions DESC LIMIT 50`;

const gaRes = await fetch(
  `https://googleads.googleapis.com/v23/customers/${CUSTOMER_ID}/googleAds:searchStream`,
  {
    method: "POST",
    headers: { Authorization: `Bearer ${ACCESS_TOKEN}`, "developer-token": DEV_TOKEN, "Content-Type": "application/json" },
    body: JSON.stringify({ query: gaql }),
  }
).then((r) => r.json());

const placements = (gaRes[0]?.results || []).map((row) => ({
  name: row.groupPlacementView.displayName,
  url: row.groupPlacementView.targetUrl,
  type: row.groupPlacementView.placementType,
  impressions: parseInt(row.metrics.impressions),
  clicks: parseInt(row.metrics.clicks),
  conversions: parseFloat(row.metrics.conversions),
  cost: parseInt(row.metrics.costMicros) / 1_000_000,
  ctr: parseFloat(row.metrics.ctr),
}));

const topConverting = placements.filter((p) => p.conversions > 0);
const wastedSpend = placements.filter((p) => p.conversions === 0).sort((a, b) => b.cost - a.cost).slice(0, 10);

const placementBlock = topConverting.slice(0, 25)
  .map((p) => `- [${p.type}] ${p.name} (${p.url}) — conv: ${p.conversions.toFixed(0)}, CTR: ${(p.ctr * 100).toFixed(1)}%, cost: $${p.cost.toFixed(2)}`)
  .join("\n");
const wasteBlock = wastedSpend
  .map((p) => `- [${p.type}] ${p.name} — $0 conv, spent $${p.cost.toFixed(2)}`)
  .join("\n");

const mave = await fetch("https://app.mavera.io/api/v1/mave/chat", {
  method: "POST",
  headers: { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" },
  body: JSON.stringify({
    message: `Analyze these Display/YouTube placements.\n\nTOP CONVERTING:\n${placementBlock}\n\nWASTED SPEND:\n${wasteBlock}\n\nProduce: 1) Content themes 2) Best categories 3) Exclusions 4) Partnership opps 5) Buyer insight`,
  }),
}).then((r) => r.json());

console.log("--- Placement Analysis ---");
console.log((mave.content || "").slice(0, 2500));