Grouped Revenue Contribution
Kontribusi revenue per kategori & drill-down per produk
Per Kategori
Per Produk
Evaluation Menu
Product Sales by Qty, Product Sales by Value (Rp), and Best Seller Product
Product Sales Ranking (Qty)
memilih range
tanggal/week/yearly
Product Sales Ranking (Rp)
memilih range
tanggal/week/yearly
10 Top Sales
Zero Sales Product
Target vs Aktual
Revenue aktual vs target per outlet — Data Olsera POS + Laporan Penjualan 2026
Target vs Aktual Revenue per Outlet
Revenue Bulanan — Target vs Aktual (Semua Outlet)
Distribusi Revenue: Online vs Offline
Online Channel Breakdown
Daily Performance
Performa harian per shift (Pagi / Siang / Malam / Late Night) — transaksi, avg basket, revenue, efektivitas late night
| Promo | Qty Sold | Revenue Contribution |
|---|
Analisis Shift per Outlet & Bulan
Detail Harian per Shift (Ketercapaian) / Average Basket per Outlet
Trend Revenue Harian
Promotion Sales — Efektivitas Promo & Voucher
Solid Product Proportion
Proporsi produk terhadap total penjualan — untuk keputusan R&D dan optimasi menu
Proporsi per Kategori (Revenue Share)
Detail Produk
Cost Control & Margin
Analisis HPP, margin, dan profitabilitas per produk
Margin % per Produk
Revenue vs HPP Breakdown
Detail Margin per Produk
HPP = Harga Pokok PenjualanBCG Matrix — Menu Engineering
Product Lifecycle
Cross-Outlet Heatmap
Menu Survival Curve
Survival Rate per Cohort Launch
Grafik Survival
Year-over-Year Comparison
Perbandingan revenue 3 tahun terakhir (2023 – 2025)
Revenue Bulanan: 2023 vs 2024 vs 2025
Detail Perbandingan per Bulan
SOP & Kecepatan Pelayanan
Monitoring waktu pelayanan per outlet & shift — Target < 5 menit
Rata-rata Waktu Pelayanan per Outlet
Distribusi Kecepatan
Detail per Outlet & Shift
Pareto 80/20 — Produk
Berapa banyak produk yang menghasilkan 80% revenue? Ch.1 EDA — Practical Statistics for Data Scientists
Kontribusi Revenue per Produk (Cumulative)
Top 100 Produk — Revenue Share
| # | Produk | Revenue | Share % | Kumulatif % | Status |
|---|
Margin Quadrant — Winning vs Traffic Builder
Volume × Margin. Ch.1 Correlation — Practical Statistics for Data Scientists
Scatter: Volume vs Margin %
Winning — Volume Tinggi + Margin Bagus
| Produk | Qty | Revenue | Margin % |
|---|
Traffic Builder — Volume Tinggi + Margin Tipis
| Produk | Qty | Revenue | Margin % |
|---|
Top Produk per Outlet
Ranking produk terlaris di setiap cabang — bandingkan apa yang laku di masing-masing lokasi
RFM Segmentasi Customer
K-Means clustering 4 segmen pada skor RFM (Recency × Frequency × Monetary). Ch.7 — Practical Statistics for Data Scientists
Distribusi Segmen (K-Means, k=4)
Avg Monetary per Segmen
Detail Customer
| Customer | Recency (hari) | Frequency | Monetary | R | F | M | Segmen | Jam Aktif |
|---|
Cashier KPI
Performa kasir per outlet — trx/hari, avg basket. ANOVA F-test avg basket antar outlet. Ch.3 — Practical Statistics for Data Scientists
Trx per Hari per Kasir
Avg Basket per Kasir
Tabel KPI Lengkap
| Outlet | Kasir | Total Trx | Trx/Hari | Hari Kerja | Total Revenue | Avg Basket |
|---|