Multi-Channel Performance → Content Strategy

import os, requests, time
from collections import defaultdict

STORE = os.environ["BIGCOMMERCE_STORE_HASH"]
BC_TOKEN = os.environ["BIGCOMMERCE_ACCESS_TOKEN"]
MV = os.environ["MAVERA_API_KEY"]
BC = f"https://api.bigcommerce.com/stores/{STORE}/v3"
BC_HEADERS = {"X-Auth-Token": BC_TOKEN, "Content-Type": "application/json", "Accept": "application/json"}

CHANNELS = {1: "Storefront", 2: "Amazon", 3: "Facebook Shop", 4: "eBay"}
channel_data = defaultdict(lambda: {"revenue": 0, "orders": 0, "categories": defaultdict(lambda: {"revenue": 0, "units": 0})})

for ch_id, ch_name in CHANNELS.items():
    page = 1
    while True:
        r = requests.get(f"{BC}/orders",
            headers=BC_HEADERS,
            params={"channel_id": ch_id, "page": page, "limit": 50, "sort": "date_created:desc"})
        if r.status_code == 429:
            time.sleep(2); continue
        if r.status_code == 204: break
        r.raise_for_status()
        orders = r.json().get("data", [])
        if not orders: break

        for order in orders:
            total = float(order.get("total_inc_tax", 0))
            channel_data[ch_name]["revenue"] += total
            channel_data[ch_name]["orders"] += 1

            prods = requests.get(f"{BC}/orders/{order['id']}/products",
                headers=BC_HEADERS).json().get("data", [])
            for p in prods:
                cat = p.get("product_options", [{}])[0].get("display_name", "General")
                channel_data[ch_name]["categories"][cat]["revenue"] += float(p.get("total_inc_tax", 0))
                channel_data[ch_name]["categories"][cat]["units"] += int(p.get("quantity", 0))
            time.sleep(0.15)

        if len(orders) < 50: break
        page += 1
        time.sleep(0.2)

summary_lines = []
for ch, data in channel_data.items():
    aov = data["revenue"] / max(data["orders"], 1)
    top_cats = sorted(data["categories"].items(), key=lambda x: -x[1]["revenue"])[:3]
    cats_str = ", ".join(f"{c}(${d['revenue']:.0f})" for c, d in top_cats)
    summary_lines.append(f"{ch}: ${data['revenue']:.0f} revenue, {data['orders']} orders, AOV ${aov:.0f}. Top: {cats_str}")

summary = "\n".join(summary_lines)

strategy = requests.post("https://app.mavera.io/api/v1/mave/chat",
    headers={"Authorization": f"Bearer {MV}", "Content-Type": "application/json"},
    json={"message": f"""Analyze this multi-channel e-commerce performance data and generate
channel-specific content strategies.

For each channel: what content formats work best, recommended messaging angles,
budget allocation suggestion, and one specific campaign idea.

{summary}"""}).json()

print("--- Multi-Channel Content Strategy ---")
print(strategy.get("content", "")[:2000])

const STORE = process.env.BIGCOMMERCE_STORE_HASH;
const BC_TOKEN = process.env.BIGCOMMERCE_ACCESS_TOKEN;
const MV = process.env.MAVERA_API_KEY;
const BC = `https://api.bigcommerce.com/stores/${STORE}/v3`;
const bcHeaders = { "X-Auth-Token": BC_TOKEN, "Content-Type": "application/json", Accept: "application/json" };

const CHANNELS = { 1: "Storefront", 2: "Amazon", 3: "Facebook Shop", 4: "eBay" };
const channelData = {};
for (const name of Object.values(CHANNELS)) {
  channelData[name] = { revenue: 0, orders: 0, categories: {} };
}

for (const [chId, chName] of Object.entries(CHANNELS)) {
  let page = 1;
  while (true) {
    const res = await fetch(`${BC}/orders?channel_id=${chId}&page=${page}&limit=50&sort=date_created:desc`,
      { headers: bcHeaders });
    if (res.status === 429) { await new Promise(r => setTimeout(r, 2000)); continue; }
    if (res.status === 204) break;
    const orders = (await res.json()).data || [];
    if (!orders.length) break;

    for (const order of orders) {
      channelData[chName].revenue += parseFloat(order.total_inc_tax || 0);
      channelData[chName].orders += 1;

      const prods = await fetch(`${BC}/orders/${order.id}/products`,
        { headers: bcHeaders }).then(r => r.json()).then(d => d.data || []);
      for (const p of prods) {
        const cat = p.product_options?.[0]?.display_name || "General";
        channelData[chName].categories[cat] ||= { revenue: 0, units: 0 };
        channelData[chName].categories[cat].revenue += parseFloat(p.total_inc_tax || 0);
        channelData[chName].categories[cat].units += parseInt(p.quantity || 0);
      }
      await new Promise(r => setTimeout(r, 150));
    }
    if (orders.length < 50) break;
    page++;
    await new Promise(r => setTimeout(r, 200));
  }
}

const summaryLines = Object.entries(channelData).map(([ch, data]) => {
  const aov = data.revenue / Math.max(data.orders, 1);
  const topCats = Object.entries(data.categories)
    .sort(([,a],[,b]) => b.revenue - a.revenue).slice(0, 3)
    .map(([c, d]) => `${c}($${d.revenue.toFixed(0)})`).join(", ");
  return `${ch}: $${data.revenue.toFixed(0)} revenue, ${data.orders} orders, AOV $${aov.toFixed(0)}. Top: ${topCats}`;
});

const strategy = await fetch("https://app.mavera.io/api/v1/mave/chat", {
  method: "POST",
  headers: { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" },
  body: JSON.stringify({
    message: `Analyze this multi-channel e-commerce performance and generate channel-specific content strategies.\n\nFor each channel: content formats, messaging angles, budget allocation, one campaign idea.\n\n${summaryLines.join("\n")}`,
  }),
}).then(r => r.json());

console.log("--- Multi-Channel Content Strategy ---");
console.log((strategy.content || "").slice(0, 2000));