Make your books easier to find in Amazon search and AI answers

Kadaxis helps publishers connect books with readers through Amazon keyword research, AI discovery intelligence, and practical AI advice.

Talk to Chris Read the research
A crowded Paris bookstall around 1910, with books stacked, tied and hung on wires, and the bookseller sitting at the right reading one of them.
Eugène Atget, secondhand book dealer, place de la Bastille, 1910 to 1911. Digital image courtesy of Getty's Open Content Program.
  1. Catalogue languageadult fiction / suspense / literary
  2. Reader languageunreliable narrator, slow-burn psychological thriller, book-club twist ending
  3. Retailer fieldspecific query paths, weighted and ordered for discovery
8% Keywords publishers assign
40% Keywords Kadaxis builds
How often a keyword brings its book up on the first two pages of Amazon Books results. The publisher figure comes from 248,046 keywords across 24,367 books; ours is the average across thousands of books. Both are approximate and measure search visibility. Read the study

From reader questions to book discovery

Amazon keywords

Title-specific research and keyword sets for frontlist and backlist books, with supporting search visibility reports.

Explore keyword services

AI discovery (GEO)

Understand how your books appear in AI answers, which sources and competing titles surface, and what to improve.

Explore AI discovery (GEO)

AI consulting

Practical advice for publishing leaders considering AI workflows, internal tools, and vendor decisions.

Explore AI consulting

Publishers we have worked with include

See selected publishers Join Chris at BISG's book discovery webinar on November 19.

Led by Chris Sim

About Chris and Kadaxis
Bookish
Chris was CTO, where he built book search and recommendation systems.
BCG X
Later a venture CTO, where he was recognized as one of the firm's global topic leaders in generative AI.
FutureBook
Kadaxis was named BookTech Company of the Year.
BISG
Kadaxis contributed to BISG's 2018 keywords best-practices standard.

Research

Studies on how readers find books in Amazon search and AI tools. Read the findings, examine the methods, and explore the questions publishers ask.

  1. Source-list appearances in 27,702 answers: retailer (e.g. Barnes & Noble, Kobo) 81.0%; reader community (e.g. Reddit, Goodreads) 77.6%; editorial and review (e.g. Book Riot, Kirkus Reviews) 77.1%; publisher 75.6%; book summary or discovery service 52.9%; reference 39.0%; library 17.0%; institutional 11.5%.

    AI discovery

    Where AI book recommendations come from

  2. Four reader requests, each asked in ChatGPT three times without naming the book or its author. Explaining the main types of dementia plainly, and what each means for family care: The Dementia Caregiver was named in all three answers, first in two. A short starter for the first week after a diagnosis: not named; ChatGPT recommended other introductory guides and parts of broader references. Portable checklists for daily care: not named; it recommended books with checklists and forms, the same two books in all three answers. Questions to take to appointments: not named; it recommended question-focused books and free appointment guides.

    AI discovery

    GEO and AEO for publishers: Matching books to reader needs

  3. Three-panel summary showing search phrases far ahead when searched exactly, across expansion searches, and across the complete keyword record.

    Amazon search

    Should Book Keywords Be Single Words or Search Phrases?

Explore all research

Discuss discovery for your list

Send Chris a message about your publisher, your titles, or the question your team is considering. We will reply directly and arrange a conversation when useful.

Talk to Chris
Two shelves of old books in a brown-toned early photograph with rough paper edges.
William Henry Fox Talbot, A Scene in a Library, 1844. Metropolitan Museum of Art.