
Made for Each Other: The Biology of the Human-Animal Bond (Merloyd Lawrence Novels)
4.4 stars from 65 reviews
Last checked: May 15, 2026
While not the biggest discount we've seen for this book, it's still a great deal and we recommend grabbing it before price returns to its normal range.
Price range: $2.99 – $15.62
0 readers are tracking this book's price
Fans of these authors will like this...
- Yuval Noah Harari
- Malcolm Gladwell
- Mary Roach
Fans of these books will like this...
- The Hidden Life of Deer
- Braiding Sweetgrass
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Perfect for you if...
- You're curious about why animals affect you so deeply and want the science to back up what you've always felt.
- You love books that weave together evolutionary biology, history, and practical insights about how our brains work.
- You're concerned about disconnecting from nature and want evidence for why that matters to your health.
Maybe not for you if...
- You're looking for a how-to guide on training or caring for specific pets.
- You prefer narrative-driven stories over scientific explanation and data.
- You're sceptical of the claim that animals fundamentally shape human biology and well-being.
About this book
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We track price drops, sale patterns, and predict when this book will go on offer next.
Price History
Kindle price over time. Green zones = periods when the book was free.
Price has dropped 12 times over the last 6 years. Goes on sale roughly every 130 days.
Sales Rank
Amazon sales rank: lower number = better selling book. #1 is the bestseller.
Currently around #195K in the Kindle store — a niche title. Climbing the charts — 79% improvement recently.
Rating & Reviews
Purple line = star rating over time. Blue area = total review count growth.
Currently 4.4★ from 65 reviews
Review activity has been quiet recently. Rating has remained stable at 4.4 over the tracking period.
Sale Prediction
Actual Predicted
This book goes on sale roughly every 130 days. Next drop estimated in about 16 weeks. Typical discount: 81% off.
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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