Documentation - Grooving Tics

📚 Documentation & Guides

Selamat datang di pusat dokumentasi lengkap untuk Grooving Tics Dashboard. Di sini Anda akan menemukan penjelasan mendalam tentang setiap fitur, rumus yang digunakan, cara membaca analisis, dan strategi implementasi.

🚀 Quick Navigation

📊 Dashboard Overview

Key Metrics Explained:

Total Revenue: Total pendapatan dari semua transaksi
Total Orders: Jumlah pesanan yang berhasil diproses
Total Customers: Jumlah customer unik yang melakukan pembelian
Average Order Value (AOV): Rata-rata nilai per pesanan
Total GMV: Gross Merchandise Value - total nilai barang yang terjual
Conversion Rate: Persentase visitor yang berhasil melakukan pembelian

Formulas:

AOV = Total Revenue ÷ Total Orders

Conversion Rate = (Orders ÷ Visitors) × 100%

GMV = Σ(Product Price × Quantity)

🎯 RFM Analysis

What is RFM?

RFM (Recency, Frequency, Monetary) adalah metode analisis customer segmentation yang mengelompokkan customer berdasarkan tiga dimensi:

Recency (R): Seberapa baru customer melakukan transaksi terakhir
Frequency (F): Seberapa sering customer bertransaksi
Monetary (M): Berapa total nilai yang dihabiskan customer

RFM Scoring Method:

Recency Score (1-5):

5: ≤ 30 hari
4: 31-60 hari
3: 61-90 hari
2: 91-180 hari
1: > 180 hari

Frequency Score (1-5):

5: ≥ 20 transaksi
4: 10-19 transaksi
3: 5-9 transaksi
2: 2-4 transaksi
1: 1 transaksi

Monetary Score (1-5):

5: Top 20% nilai
4: 21-40% nilai
3: 41-60% nilai
2: 61-80% nilai
1: Bottom 20% nilai

Customer Segments:

Champions (555)

Customer terbaik - sering belanja, nilai tinggi, baru saja belanja

Action: VIP treatment, early access, exclusive offers

Loyal Customers (454)

Customer setia dengan nilai tinggi, belanja reguler

Action: Upsell premium products, loyalty rewards

Potential Loyalists (345)

Customer baru dengan potensi tinggi

Action: Engagement campaigns, product education

At Risk (244)

Customer dengan nilai tinggi tapi jarang belanja

Action: Win-back campaigns, special discounts

Cannot Lose Them (155)

Customer VIP yang jarang belanja

Action: Personal outreach, exclusive incentives

Hibernating (144)

Customer tidak aktif dalam waktu lama

Action: Reactivation campaigns, survey feedback

👥 Customer Segmentation (K-Means)

K-Means Clustering Algorithm:

K-Means adalah algoritma unsupervised learning yang mengelompokkan customer berdasarkan kesamaan pola pembelian mereka.

Features Used for Clustering:

Total Spending: Total nilai yang dihabiskan
Order Frequency: Rata-rata frekuensi pesanan per bulan
Average Order Value: Rata-rata nilai per pesanan
Days Since Last Purchase: Hari sejak pembelian terakhir
Product Category Diversity: Keragaman kategori produk yang dibeli

How to Interpret Clusters:

High-Value Cluster:

• Tinggi: Spending, AOV, Frequency
• Rendah: Days since last purchase
• Strategy: VIP treatment, exclusive offers

At-Risk Cluster:

• Tinggi: Days since last purchase
• Rendah: Recent frequency
• Strategy: Re-engagement campaigns

💎 Customer Lifetime Value (CLV)

CLV Calculation Methods:

Historical CLV: Total Revenue ÷ Total Customers

Predictive CLV: (Average Order Value × Purchase Frequency × Customer Lifespan)

CLV to CAC Ratio: CLV ÷ Customer Acquisition Cost

CLV Interpretation:

CLV > 3x CAC: Healthy customer acquisition
CLV = 1-3x CAC: Break-even, needs optimization
CLV < CAC: Unsustainable, urgent action needed

CLV Optimization Strategies:

Increase Frequency

• Loyalty programs
• Subscription models
• Regular promotions

Increase AOV

• Cross-selling
• Upselling
• Bundle offers

Extend Lifespan

• Customer retention
• Win-back campaigns
• Product diversification

🎯 Marketing Funnel Analysis

Funnel Stages:

TOFU - Top of Funnel (Awareness)

Membangun brand awareness dan menarik perhatian customer potensial

Key Metrics: Impressions, Reach, Brand Awareness

MOFU - Middle of Funnel (Consideration)

Mendorong customer untuk mempertimbangkan produk/layanan

Key Metrics: Engagement, Website Traffic, Lead Generation

BOFU - Bottom of Funnel (Conversion)

Mengkonversi customer menjadi pembeli

Key Metrics: Conversion Rate, Sales, Revenue

Post-Purchase (Retention)

Mempertahankan customer dan mendorong repeat purchase

Key Metrics: Customer Satisfaction, Repeat Purchase Rate, NPS

Conversion Rate Optimization:

TOFU (Top of Funnel):

• Content marketing
• SEO optimization
• Social media presence
• Brand awareness campaigns

MOFU (Middle of Funnel):

• Email nurturing
• Retargeting ads
• Product comparisons
• Customer testimonials

BOFU (Bottom of Funnel):

• Limited-time offers
• Free shipping
• Customer support
• Easy checkout process

Post-Purchase:

• Order confirmation
• Delivery tracking
• Review requests
• Upsell recommendations

📉 Churn Analysis

Churn Rate Calculation:

Churn Rate = (Customers Lost ÷ Total Customers at Start) × 100%

Customer Retention Rate = 100% - Churn Rate

Churn Prediction Indicators:

Decreasing Purchase Frequency: Customer membeli lebih jarang
Declining Order Value: Rata-rata nilai pesanan menurun
Long Periods of Inactivity: Tidak ada aktivitas dalam waktu lama
Support Ticket Increase: Banyak keluhan atau masalah

Retention Strategies:

Preventive Actions

• Regular check-ins
• Personalized offers
• Loyalty rewards
• Quality improvements

Win-back Campaigns

• Special discounts
• New product announcements
• Feedback requests
• Limited-time offers

📁 Data Import Guide

Supported CSV Formats:

Transaction Data:

• transaction_id
• customer_id
• date
• total
• marketplace
• product_name
• quantity

Ads Data:

• campaign_name
• platform
• impressions
• clicks
• spend
• conversions
• date

Data Storage:

Local Storage: Data disimpan di browser untuk akses cepat
Auto-save: Data otomatis tersimpan saat import
Data Persistence: Data tetap ada setelah refresh browser
Sample Data: Gunakan sample data untuk testing fitur

⭐ Best Practices

Data Quality:

• Pastikan data transaksi lengkap dan akurat
• Gunakan format tanggal yang konsisten (YYYY-MM-DD)
• Validasi data sebelum import
• Regular data backup dan update

Analytics Strategy:

• Monitor KPI secara berkala (weekly/monthly)
• Bandingkan performa antar periode
• Segmentasi customer untuk targeted marketing
• Optimasi funnel berdasarkan data conversion

Action Items:

• Set up automated reports
• Create customer journey maps
• Implement A/B testing
• Track ROI dari setiap campaign

🆘 Need Help?

Jika Anda membutuhkan bantuan lebih lanjut atau memiliki pertanyaan tentang fitur analytics, jangan ragu untuk menghubungi tim support.

👋 Selamat Datang di Grooving Tics!