Analyze purchase patterns and suggest product bundles to increase average order value.
AI AgentLLM ServerEcommerceBundleUpsell
0.5×← Perlahan · Cepat →
0%Stage 0 / 7 · Idle
💬Tekan Play Demo untuk lihat Product Bundle Suggestion Agent.
Demo Complete — All Stages Generated
01 WhatsApp Command
💼
OpenClaw — AINNA Agent
● Neural Link Active
02 Requirement Analysis
Products
6
Bundles
3
Avg Saving
15%
Potential
+22%
Menunggu Sedang aktif Selesai
03 Python Script Generation
1
📊
Analisis orderAnalyze purchase patterns
2
🔗
Cari pasanganFind frequently bought together
3
💰
Kira diskaunCalculate optimal bundle price
4
📤
Cadang bundleSuggest bundles to platform
from collections import defaultdict
def suggest_bundles(orders, min_support=0.02):
pairs = defaultdict(int)
for order in orders:
items = order['products']
for i in range(len(items)):
for j in range(i+1, len(items)):
pairs[(items[i], items[j])] += 1
bundles = [(a, b, count) for (a, b), count in pairs.items()
if count / len(orders) >= min_support]
return sorted(bundles, key=lambda x: -x[2])
04 Block Diagram
Menunggu Sedang aktif Selesai
05 System Schematic
Menunggu Sedang aktif Selesai
⚠️ Validate bundle pricing to ensure margin protection.
06 Simulasi Bundle Suggestion
Mula Bundle
Bundles
0
Min Saving
0%
Max Saving
0%
AOV Impact
0%
07 Bundle Report
Demo
Bundle
Bundles
0
Products
6
AOV Upside
0%
Status
Standby
Terminal Log
[SISTEM] Product Bundle Suggestion Agent sedia
System Architecture
📱 Command Layer
WhatsApp instruction
🤖 Agent Layer
Order pattern analyzer
Bundle optimizer
Price calculator
🛒 Ecommerce Layer
Order DB
Product catalog
Pricing engine
Safety Notes
Validate bundle pricing to ensure margin protection.