1. Why data quality matters in Japan
Japan’s real‑estate ecosystem is fragmented across multiple listing portals, brokers and aggregators. Without a disciplined data pipeline, comparisons across stations or wards produce noisy, misleading results. Tokyo Insights was built to solve this problem for serious investors.
2. Source ecosystem
Our datasets aggregate information from major portals such as Suumo, Lifull Homes and Rakumachi, complemented by REINS‑based transaction data. Each source uses different conventions, fields and station labels, which is why harmonisation is not optional — it is the foundation of the entire analytical stack.
3. Harmonisation pipeline
The harmonisation layer reconciles inconsistent columns, normalises station names, converts age formats, standardises layout labels and aligns price and rent units. This allows us to compare listings from different sources on an apples‑to‑apples basis at the station level.
4. Station-level matching
Raw listings often contain station names with aliases, prefixes or minor spelling variations. Tokyo Insights maintains a unified master dictionary of stations and lines so that every listing is mapped to the correct micro‑market. This is crucial for accurate GRM corridors and rent benchmarks.
5. Cleaning, outlier control and validation
The cleaning stage removes duplicates, impossible values, mis‑labelled layouts and extreme outliers. We prefer to discard questionable data rather than dilute the signal. Each dataset is then validated against historical ranges to ensure that new data behaves consistently with known market structure.
6. Output datasets and investor tools
Harmonised, validated datasets feed directly into tools such as Deal Finder, GRM dashboards and station‑level benchmarks. For investors, this means every chart and shortlist is backed by the same rigorous pipeline rather than ad‑hoc scraping.