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Mystery Comparison - December 2024

1
Best Choice
9.8Exceptional
2
Best Value
9.7Exceptional
3
9.5Excellent
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Model

The Thursday Murder Club: A Novel (A Thursday Murder Club Mystery)
Model
Murdle: Volume 1 (Murdle, 1)
Model
Last Seen Alone

Brand

Random House Books for Young Readers
Brand
Griffin
Brand
Berkley

Reviews

459,471 reviews
Reviews
6,831 reviews
Reviews
6,375 reviews

Tech Specs

item weight

2.31 pounds
item weight
1 pounds
item weight
2.31 pounds

publisher

Penguin Books Reprint edition August 3, 2021
publisher
Griffin June 13, 2023
publisher
Berkley September 28, 2021

isbn 10

1984880985
isbn 10
1250892317
isbn 10
0593197364

language

English
language
English
language
English

isbn 13

978-1984880987
isbn 13
978-1250892317
isbn 13
978-0593197363

dimensions

5.45 x 0.83 x 8.22 inches
dimensions
6.06 x 0.94 x 9.12 inches
dimensions
4.1 x 0.82 x 6.7 inches

Available On

Available On
Available On

Our Top 3 Picks

Here are the top 3 recommended products with more information to help you find the right product for you
  • 9.8
    1
    Random House Books for Young Readers
    50% Off

    The Thursday Murder Club: A Novel (A Thursday Murder Club Mystery)

  • 9.7
    2
    Griffin
    50% Off

    Murdle: Volume 1 (Murdle, 1)

    Why we love it

    Challenging puzzles with varying difficulty levels.
    Humorous and engaging narrative.
    Inclusive representation of LGBTQ+ characters.
  • 9.5
    3
    Last Seen Alone
    Berkley
    40% Off

    Last Seen Alone

    Why we love it

    Engaging storyline with suspense and romance.
    Well-developed characters and realistic plot.
    Quick and easy to read, hard to put down.

Our ranking system

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Features

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Consumer Reviews

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Popularity

Our system also considers the popularity of products, analyzing factors such as market presence, reputation, and user satisfaction. By leveraging AI, we capture a comprehensive picture of a product's standing in the market, which may not always be evident through traditional testing.
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Value for money

AI allows us to compare products based on attributes like price, specifications, and user feedback, helping to determine their value for money. This data-driven approach offers an efficient and reliable way to assess how products stack up against one another in terms of cost-effectiveness.
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