# Executive One-Pager — Content Operations Framework

**Date:** 2026-06-26 | **Market:** Bangkok OTA listings (n=23,233)

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## PROBLEM
**49.41%** of listings (11,480) have substandard content (score < 70). Ops teams lack a data-driven way to prioritize fixes by business impact.

## IMPACT (data-backed)
| Finding | Value |
|---------|-------|
| High vs low content — median reviews | **16 vs 0** (p < 0.001) |
| Regression uplift per +10 score pts | **~77%** more reviews (R² = 0.4515) |
| Est. uplift — top 50 RICE properties | **+8,908** reviews/yr (proxy) |
| Revenue opportunity proxy | **1,429,644,464 THB** at risk |
| Largest content gap | **94.46%** descriptions below 150 words |

## ACTION (prioritized)
1. **Immediate:** Outreach to **2,870** Premium High-Potential listings (highest RICE ROI)
2. **This sprint:** Batch-fix description gap for Mid-Market segment (**6,296** listings)
3. **Pilot:** 47-listing A/B test to validate >= 20% review uplift (see `experiment_proposal.md`)

## ASK
Approve **Mid-Market content upgrade pilot** and allocate **2 ops FTE** for weekly top-20 RICE execution.

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_All figures are proxies from Inside Airbnb Bangkok data. Review volume ≠ bookings; revenue = occupancy gap × price estimate._