BookSeeking
How it worksFor Publishers
About
Sign inExplore the demo →
The research

A recommendation is a small act of teaching.

Most engines optimise for what you'll consume next. BookSeeking optimises for what would help you grow — and that distinction comes straight from the research on how curiosity and learning actually work.

Loewenstein · 1994
The Information Gap

Curiosity is the feeling of a gap between what you know and what you want to know — and it sharpens as you near the edge of your own knowledge.

How BookSeeking applies it

Every concept BookSeeking extracts is sized to be a recognisable gap: specific enough to notice when you've filled it, general enough to recur across books. Recommendations aim at the gaps nearest your sky.

Krashen · 1985
Comprehensible Input (i + 1)

We learn most from material that's mostly comprehensible with a little that's new — your current level, plus one.

How BookSeeking applies it

We rank books by how much of their content you already hold. The sweet spot is roughly 50–80% familiar: enough footing to follow, enough new to grow.

Csikszentmihalyi · 1990
Flow

Absorption happens when challenge meets skill — and as skill grows, the challenge has to rise to match it.

How BookSeeking applies it

As your library grows, BookSeeking quietly tightens its band: a new reader gets variety, a seasoned one gets depth. The challenge tracks your skill.

Iyengar & Lepper · 2000
Choice, Not Overload

More options can mean fewer decisions. In the famous jam study, a smaller display drove far more choices than a larger one.

How BookSeeking applies it

We show eight recommendations by default, not eighty — enough variety to find a match, few enough to actually decide.

Saricks · Readers' advisory
Appeal Factors

What readers love isn't only a book's subject but how it reads — its pacing, characterisation, story line, frame and style.

How BookSeeking applies it

BookSeeking profiles the texture you enjoy and weights matches toward it, so a contemplative reader isn't handed a brisk explainer of the very same idea.

The throughline

Engines tuned purely for engagement narrow what you read. Tuned for development, they widen it. We chose the second on purpose — and every number in the ranking serves it.