Statsig toggles your features.
Hyperstone evolves your game economy.
- Economy vs Engineering. Technical flags don't grow LTV.
- Multiple algorithms. Thompson Sampling, Epsilon-greedy, custom models.
- LTV focus. Built to maximise revenue per player, not deployment velocity.
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Hyperstone vs. Statsig
Stop toggling features. Start optimising economies.
Statsig
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Feature flags for controlled rollouts
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Engineering-focused A/B testing
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Warehouse-native data connectivity
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Product observability and analytics
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Manual interpretation, Frequentist significance
Hyperstone
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Bayesian optimisation for game parameters
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Thompson Sampling, Epsilon-greedy, and more
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Pre-built game economy logic out of the box
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Direct IAP and LTV optimisation per segment
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No-code parameter control for LiveOps teams
Comparison FAQ
Statsig is built for feature management and engineering rollouts. It's great at answering 'should we ship this button to 50% of users?'. Hyperstone is built for game teams optimising parameters. Prices, difficulty curves, reward rates. Statsig tells you if a flag should be on. Hyperstone tells you what your sword should cost.
All the time. Use Statsig for technical rollouts, kill switches, and product analytics. Let Hyperstone handle monetisation and economy optimisation. Statsig manages your flags. Hyperstone manages your money.
SaaS by default, zero infra on your end. For enterprise teams with compliance requirements, we support on-prem deployments too.
Statsig needs statistical significance and manual interpretation. Hyperstone uses Thompson Sampling, which converges on winning values fast. Days, not weeks. In our Jump Odyssey case study, we saw ARPU double within two weeks. Ad impressions per user went from 0.3 to 2.3. Engagement time more than doubled.
Hyperstone has its own segmentation tuned for game events. Nothing stops you from syncing user IDs between both systems for consistent cohorts.
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