The Limits of Using an Algorithm to Predict Book Sales

machine learning, publishers, data, metadata, bestseller listThere’s been much recent conjecture on whether book sales can be predicted by text analysis alone. My company, Kadaxis, has dedicated the past few years to machine learning research and product development for the publishing industry. In our early days, we set out to build an algorithm to predict bestsellers, and tested it in the wild. In this post, I’ll share my perspectives on why the text alone isn’t enough.

If You Publish It, Will They Come?

To predict book sales, you need to account for the factors that influence book sales. The text of a book is core to the product, but many other factors, such as sales and marketing, influence whether a customer will discover and buy it. An algorithm predicting book sales using only the text as input will only work in a book market meritocracy, where the best-written books always sell the most copies.

Author platform (brand awareness) is one such non-text factor that influences sales, as in the following examples.

Much more.


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