In 2017, I wrote a discovery piece for a decentralized publishing ecosystem built on the Ethereum blockchain (Doug from Phin, Fran from Firebrand and I were working on a solution to decentralize the publishing industry to put more value and control back in the hands of authors, publishers and readers). […]
Posting this for posterity, built around 2012-2013. The startup that was Bookish (joint venture between Simon & Schuster, Penguin and Hachette) is no longer around, but we built out some reasonable book data processing infrastructure, along with a search and recommendation engine. I ran engineering and architected the overall solution. […]
BISG Annual Meeting 2017 at The Harvard Club, NYC. This post originally appeared on the Kadaxis blog. I participated in a panel on “Rights, Metadata and Marketing” at the recent BISG 2017 Annual Meeting. Here are my responses to the questions I was asked: WHAT IS CURRENTLY WORKING FOR KADAXIS? Our approach […]
There’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, […]
This article originally appeared on the Kadaxis blog. Crafting effective keywords to add to a book’s metadata, could be one of the highest return marketing activities to increase online sales potential. This post examines why keywords are so important, and how they affect discovery on Amazon. Let’s break the logic down:• […]
