S10-M. Luxury Brand SOV + Counter Occupancy (Mitsukoshi-specific)
Published 2026-05-14Updated 2026-06-302 min read
Mitsukoshi differentiation point ⭐ — Analyze counter occupancy and SOV (Share of Voice) of 700+ tenant brands by 19 stores, floors, and seasons.
1. URL · Personas
/brand-sov· P5 (MD & Store Operations)
2. User Stories
P5 — Compare counter GMV and turnover for LV vs Hermes on the 1F of Xinyi store + analyze 4-week impact after SS-season new releases hit the display.
3. Data Mix
| Data | Source |
|---|---|
| Boutique × Brand × Store | Neptune (~3K Boutique) |
| POSTransaction | Neptune (~200K) |
| Counter area / lease | Boutique attributes |
| Season (Anniversary Sale / SS / FW) | Campaign nodes |
| Competitor SOV | CompetitorSignal (social + mention frequency) |
4. Processing Pipeline
1. Aggregate GMV / turnover by (store, floor, brand)
2. Compute GMV efficiency per counter area
3. Compare seasons (4-week impact after SS new releases)
4. Join with competitor SOV (Xiaohongshu and Instagram mentions)
5. Counter re-layout recommendation (Sonnet 4.6)
5. Output UI
- Left: 19 stores × floor matrix (heatmap)
- Center: brand SOV bar chart (first-party vs competitors)
- Right: counter efficiency scatter plot (area vs GMV)
- Bottom: recommended counter re-layout card (Sonnet)
6. Guardrails
- Protect tenant brand business information (no external exposure)
- Counter lease prices kept private
7. Demo Scenarios
- Xinyi store 1F LV vs Hermes → GMV comparison + turnover
- 4 weeks after SS new release → first-party LV +12%, competitor SOV +18%
- Counter re-layout recommendation → "Moving B1 food → 1F new-release cabinet expected to lift +8%"