Why You Can Trust FairCost
We are asking you to trust pricing data. That is hard. Here is exactly how we earn that trust.
How FairCost makes money
Featured provider listings ($149-249/mo), agent subscriptions ($49-199/mo), API access ($199-999/mo), and enterprise data partnerships. Consumers never pay. We never sell leads or contact information.
Listings never affect data
Featured providers pay for visibility, not for influence. Their pricing submissions are weighted identically to everyone else's. Revenue and data are architecturally separated — different database tables, different code paths, different teams. A featured provider cannot buy a better fair range.
How data is verified
Every submission passes through evidence weighting (self-reported 0.3x → bank-verified 1.0x), scope normalisation, outlier detection, IP analysis, and manual admin review. We reject suspicious submissions. Our confidence scores tell you exactly how much data backs each range.
How we prevent manipulation
Five layers: evidence weighting means unverified claims barely register. Freshness decay means old data loses influence. IP and pattern analysis catches bulk submissions. Contributor reputation means new accounts carry less weight. Manual review catches what automation misses.
How often data updates
Aggregates recalculate within 60 seconds of an admin approving a submission. Pages rebuild automatically via Incremental Static Regeneration. The FairCost Index updates quarterly. We aim for weekly new submissions across all 16 categories.
Provider right of reply
If a provider is flagged as expensive, they can submit a scope explanation. We review context (e.g. 'price included trench excavation and after-hours callout') and adjust the scope normalisation if valid. We are not anti-provider. We are anti-opacity.
What we show vs what we know
We always display confidence levels. Low confidence (under 10 submissions) is clearly labelled. We never present uncertain data as authoritative. If we don't have enough data for a suburb, we say so and fall back to city-level ranges.
What we refuse to do
Sell user contact information. Allow pay-for-rank in pricing data. Suppress negative pricing signals. Present estimates as guarantees. Hide our methodology. Accept sponsored content that looks like editorial.
Questions? Read our full methodology or get in touch.