Swiss real-estate data • English

7 Common Data Quality Issues in SwissRETS & OpenImmo Feeds — and Why They Create Hidden Costs for CRMs

Swiss real-estate data feeds look standardised on paper. In reality, every CRM, agency and portal uses slightly different conventions — which results in inconsistencies, missing fields, and complex edge-cases.

These seven issues are among the most common patterns seen in SwissRETS and OpenImmo feeds:

1. Missing or incomplete price information
   “Auf Anfrage” often results in empty <price> fields, yet the actual price appears in the description text. This leads to misclassification, incorrect filtering, and distorted analytics.
2. Room count inconsistencies
   A listing may show 5 Zimmer in one field, but the description reveals 4.5 Zimmer, or the categorisation varies depending on internal CRM practices.
3. Feature fields are inconsistent or missing
   Boolean fields such as balcony, parking, lift or pets allowed often arrive as:
   • true/false
   • yes/no
   • 1/0
   • or simply missing
   A 3-state logic (true / false / unknown) is essential.
4. Duplicates from multiple sources
   Common causes include:
   • the same property being listed by multiple offices,
   • parallel feeds from CRM and portal accounts,
   • or IDs that don’t change when a property is re-exported.
   This impacts search relevance and creates internal clean-up overhead.
5. Address structure differences
   Street, house number and additional address lines appear in different formats depending on the CRM. For many systems, this requires custom mapping logic.
6. Inconsistent dimension fields
   Living area, usable area, plot area — these fields often differ by naming conventions (livingArea, fläche, area_m2) or are partially filled, resulting in unreliable statistics.
7. Unit price confusion (CHF/m²/year)
   Commercial listings may provide price per square metre per year, but the feed imports it as a simple price value. This causes significant filtering and analytics issues.

Why this matters for CRM systems and portals

These inconsistencies lead to:

• hidden development and maintenance costs,
• incorrect search results,
• unreliable price-per-square-metre calculations,
• broken deduplication logic,
• and ultimately: time lost on troubleshooting.

What Immotor does

Immotor standardises and cleans Swiss real-estate feeds, producing a consistent, search-ready JSON output with:

• normalised fields,
• deduplication,
• feature inference,
• and quality flags.

If you work with SwissRETS or OpenImmo feeds and deal with these issues, I’d be happy to talk — no sales pitch, just a technical exchange.