New rental pricing tool uses tenant rejection data to help landlords set the right asking rent

Ons siening

This is a UK-market story, but the underlying problem — landlords mispricing rentals and losing out — is deeply familiar to South African property professionals. In South Africa's major rental markets (Johannesburg, Cape Town, Durban, Gqeberha), landlords and agents still largely rely on gut feel, comparable listings, and TPN or PayProp data to set asking rents. The nHabit model is interesting because it captures what tenants silently reject, not just what they enquire about — a blind spot in every South African portal today. For local landlords and buy-to-let investors, the principle is worth noting: overpricing a rental in a soft market doesn't just delay a letting, it can signal desperation once a price drop is visible. Underpricing invites volume enquiries but may attract tenants who don't meet affordability criteria under the Rental Housing Act's screening norms. SA proptech players — including PayProp, Flow, and TPN — could take a cue here. Behavioural rejection data, if built into local platforms, would give landlords and agents a more honest read on market appetite than click-through rates alone. For now, SA landlords should cross-reference at least two data sources (TPN rental index, PayProp benchmarks) before setting an asking price, and resist anchoring to what a previous tenant paid.