My Next Read

The Challenge

How can I quickly discover something new to read that I will enjoy?

Whilst there are many book recommendation services and platforms, most of them are based upon relationships of the form "other people who liked this also liked...". In this project we teamed up with Penguin and our data science team to explore different ways of exploring book relationships. The core algorithm analysed book synopses to discover similar writing styles to find titles that users might not have seen or considered before.

Design Highlights

• We started off by interviewing numerous book readers to understand their thought processes and motivations as they searched for new books. We also spoke with Penguin about their expectations for the project, and how it could integrate with their main e-commerce website.
• The solution needed integrate with the core Penguin website available across multiple platforms, so a responsive web design was decided on.
• The design objective was to create an interface that concealed the underlying complexity of the algorithm and provide a very simple experience for users to find recommendations with minimal intervention.
• Suggestions could be further drilled into, and all suggestion could be bought with a single click from Penguin.

Outcome

Multiple iterations were developed before arriving at a simple web experience that gave users new suggestions very quickly.

Testing with readers demonstrated that the experience was effective

Testing with readers demonstrated that the experience was effective and the concept was valid. Penguin were very satisfied with the result as something that they could easily integrate into their existing services.

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Sketches during the early design stages:

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Final product:

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