Status Quo Bias
The preference for the current state of affairs, where any change from the baseline is perceived as a loss.
Status quo bias is the reason most people never switch banks, change insurance providers, or cancel subscriptions they barely use. First formalized by William Samuelson and Richard Zeckhauser (1988), it describes our deep preference for "the way things are."
Why This Matters for Experimentation
Status quo bias has a paradoxical relationship with A/B testing. It's the reason many experiments show flat results — users default to familiar patterns even when the variation is objectively better. It's also the reason default settings are so powerful.
Defaults Are Decisions
The single most impactful application of status quo bias is default optimization. Pre-selected options, default plans, opt-out vs. opt-in — these aren't neutral choices. They're behavioral architecture.
Research consistently shows that default options are chosen 70-90% of the time, regardless of whether they're optimal. This means the choice of what to make the default is often more impactful than the design of the selection interface.
How to Test Against Status Quo Bias
When your A/B test requires users to change their behavior, factor in the "switching cost" — not just monetary, but cognitive and emotional. Tests that work with existing user habits (incremental changes) consistently outperform tests that require behavioral shifts (radical redesigns).
If your test requires users to learn a new interaction pattern, expect a novelty dip before you see the true effect. Run the test longer than you think you need to.