BoomAU
Australian suburb growth predictions updated fortnightly, backtested for accuracy
A fortnightly suburb scoring system that rates every Australian suburb as Strong, Good, Fair or Weak, helping property investors find growth areas within their
About the business
BoomAU monitors 15,000 Australian suburbs fortnightly to identify property investment opportunities. The service scores every suburb using growth, days on market, vacancy, rental yield, and price data, then rates each as Strong, Good, Fair or Weak. Users can filter results to their budget and access a personalized fortnightly report with raw data and a clear verdict per suburb.
The platform combines timing signals (whether a suburb is moving) with affordability headroom (distance from the capital city median) to rank suburbs. BoomAU's backtested model shows Strong Signal suburbs beat the market by 7.5 percentage points with 85.7% accuracy across 12,360 postcode-month historical evaluations.
What you get
- Fortnightly suburb scoring and rating system
- Data from YIP, SQM, Domain, CoreLogic, and ABS
- Signal ratings: Strong, Good, Fair, and Weak
- Budget filtering for suburb selection
- Interactive map with 15,000 suburbs
- Raw data and macro signals per suburb
- Historical backtest validation
Pricing
Pricing model: Free
Neighbours ask
How often is suburb data updated?
BoomAU updates suburb scores fortnightly using data from YIP, SQM, Domain, CoreLogic, and ABS. This ensures users always have current information without needing to manually research multiple sources.
What factors are used to score suburbs?
The system scores suburbs using growth rates, days on market (DOM), vacancy rates, rental yield, and price data. Signals combine timing indicators and affordability headroom relative to the capital city median.
How many suburbs does BoomAU cover?
BoomAU monitors 15,000 Australian suburbs fortnightly, covering every Australian suburb with a Signal rating and detailed data.
How is the backtested accuracy calculated?
BoomAU walked forward across 12,360 historical postcode-months, assigning signals using only data available at the evaluation date, then scoring on market-adjusted 12-month returns. Strong Signal beats Good Signal beats Fair Signal beats Weak Signal in both median excess and beat-market rate.
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