A couple of years ago, I worked on a project that included building a recommendation engine for books. It seemed like a worthy goal until I looked at my bedside table, which was covered with books I hadn’t read yet. And the floor around the table. And my home office desk. And my desk at work.
Discovery didn’t seem like much of an issue — I could easily find far more titles than I’d ever have time to read. I buy and read books in hardback, paperback, Kindle, ePub and occasionally PDF.
Recently though, a new project has forced me to consider exactly how I decide what to read and how to read it.
I’ve usually thought about purchase decisions in terms of the traditional AIDA marketing path:
Awareness > Interest > Desire > Action
Andrew Rhomberg, writing for Digital Book World, goes a bit deeper, breaking down Awareness into contexts:
- Social (word-of-mouth, social media)
- Algorithmic (recommendation engine like Amazon, Pandora, Netflix)
- Distributed (reviews, blogs, at conferences)
- Incentivized (sales, co-op, promotions, freebies)
I like the first three, but I think ‘Distributed’ could be broken down even further. Book reviews, book end-notes, blogger mentions, etc. offer, in my mind, different kinds of recommendations. I like them all.
via Andrew Rhomberg and Digital Book World