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Cost of Manual Work — PropTech
See what repetitive manual work is costing PropTech teams each year — where listing data quality is structurally broken — MLS feeds vary by market, photos are mislabeled, square footage is contested, and pricing fields update on different cadences across the 600+ MLSs the platform consumes.
What this means for PropTech
- Listing data quality is structurally broken — MLS feeds vary by market, photos are mislabeled, square footage is contested, and pricing fields update on different cadences across the 600+ MLSs the platform consumes.
- Transaction velocity is throttled by paper-and-PDF closing — title, escrow, lender, and brokerage workflows still pass documents around in email when the consumer-facing product promises a tap-to-buy experience.
- iBuyer/instant-offer pricing models are under post-Zillow-Offers scrutiny — the algorithm needs explainable pricing, defensible market assumptions, and operational discipline that survives the next housing-cycle inflection.
Where it pays to act
- Listing data quality and enrichment — AI on photo classification, room labeling, square-footage validation, and cross-source reconciliation that finally produces a defensible single source of truth per property.
- Automated valuation models (AVMs) with explainable pricing — modern AVMs that beat the legacy comp-based models, with explainability layers that survive regulator and lender scrutiny.
Adjust the inputs to match your PropTech team.
What manual work costs you
Annual cost
₹6.6 L
People-weeks / year
33
Recoverable via automation
₹4.62 L
Payback
7.8 mo
What this means
PropTech teams lose 33 people-weeks a year to this work — about ₹6.6 L. Automating the routine ~70% recovers ₹4.62 L a year.
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Cost of manual work — summary
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