similar sites

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Sites similar to ed-bar.com

Ed Bar – Multi-Genre Author · ranked by shared content topics & relevance

jtorresauthor.com

J. Torres – Author

2 shared topicsfiction

Julia Satu – Author

2 shared topicsfiction

ashleyschaller.com

Ashley Schaller – Author

2 shared topicsbooks-and-literature

J.R. Hebden – Author

2 shared topicsfiction

J.T. Grobler – Author

2 shared topicsfiction

jralexanderauthor.com

JR Alexander – Author

2 shared topicsfiction

aubreybetzauthor.com

Aubrey Betz – Author

2 shared topicsbooks-and-literature

rebeccaphelpsauthor.com

Rebecca Phelps – Author

2 shared topicsfiction

E. C. Rammel – Author

2 shared topicsfiction

mperegrineburrows.com

Michael Burrows – Author

2 shared topicsbooks-and-literature

alanhollingsworth.com

Author of multiple genres — see below

2 shared topicsbooks-and-literature

HOLLY HODDER EGER – Author

2 shared topicsbooks-and-literature

juliemeanskane.com

Julie Means Kane – Author

2 shared topicsfiction

brucefraserauthor.com

Bruce Fraser – Author

2 shared topicsbooks-and-literature

lonnieschaefer.com

Lonnie Schaefer – Children's Book Author

2 shared topicsbooks-and-literature

luannestewartauthor.com

Lu Anne Stewart – Author

2 shared topicsbooks-and-literature

terrigreeningauthor.com

Terri Greening – Author

2 shared topicsfiction

anlynhansell.com

Anlyn Hansell, Author – anlynhansell.com

2 shared topicsbooks-and-literature

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.