
Tiny Experiments: How to Live Freely in a Goal-Obsessed World
4.5 stars from 1,269 reviews. Top 87% of Nonfiction books we track.
Last checked: Jun 22, 2026
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Price range: $1.99 – $16.99
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Fans of these authors will like this...
- Oliver Burkeman
- Adam Grant
- Nir Eyal
Fans of these books will like this...
- Four Thousand Weeks
- Atomic Habits
- Range
Perfect for you if...
- You feel trapped by the pressure to have your entire life figured out and want permission to explore multiple paths without guilt.
- You're creative or entrepreneurial and tired of productivity systems that demand you know your exact destination before you start moving.
- You're curious about how neuroscience and philosophy can help you make better decisions when the way forward feels genuinely unclear.
Maybe not for you if...
- You thrive with rigid structure and clear metrics, and you view goal-setting as a solved problem that works perfectly for you.
- You want quick hacks and immediate answers rather than a framework that asks you to do real introspection and design your own experiments.
- You're sceptical that uncertainty can be anything other than anxiety, and you prefer straightforward productivity advice over philosophical reframing.
About this book
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Price History
Kindle price over time. Green zones = periods when the book was free.
Currently on sale at $1.99 — 88% off peak. Price has dropped 3 times over the last 23 months. Goes on sale roughly every 149 days.
Sales Rank
Amazon sales rank: lower number = better selling book. #1 is the bestseller.
Currently #1,576 in the Kindle store — a top-10K bestseller.
Rating & Reviews
Purple line = star rating over time. Blue area = total review count growth.
Currently 4.5★ from 1,269 reviews
Gaining approximately 82 new reviews per month. Steady word of mouth growth. Rating has dipped slightly from 5.0 to 4.5.
Sale Prediction
Actual Predicted
This book is currently discounted at $1.99. It typically returns to around $16.99.
Prices shown in USD from Amazon US. We continuously pull new data to improve tracking. If dates look old, it usually means there has been no significant change since the last data point.
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