Welcome to the weekly The Smart Set, where I curate new smart reads about the publishing and media industry. I also point to issues and questions raised, and welcome you to respond or ask your own questions in the comments.
“To seek: to embrace the questions, be wary of answers.”
—Terry Tempest Williams
Must a Writer Go Hybrid for Higher Income? by Elizabeth Spann Craig
Established author—and longtime blogger in the writing community—Elizabeth S. Craig writes that, as of 2013, her self-published books are earning more money than her books with Penguin. She then lists the benefits of having a traditional publisher, and says those benefits for her are “winding down.”
- Like many hybrid authors, Craig established her readership in part by having a traditional publisher, and now she can reach that readership directly on her own. How many authors have the temperament of Craig and will decide that once their readership is established, their publishers don’t offer enough value? (I should note here that a strong commercial fiction factor is in play; genre fiction enjoy the best e-book sales because their reader numbers and consumption are high. Literary fiction authors really aren’t going to be asking these questions, not for a long time.)
- What is the likelihood that publishers will raise e-book royalty rates in light of the above? What other ways could they remain attractive?
- What if Amazon decides to drop their royalty rate from 70% to 35%? Will publishers become more attractive?
Newspapers Are Dead: Long Live Journalism by Ben Thompson
This is the third part in an excellent series at Stratechery discussing the future of news, journalism, and newspapers. While many would like to believe that “quality” will win the day, Thompson provocatively points out that quality journalism is largely irrelevant to the financial well-being of news organizations. It’s not all doomsday, however; Thompson points out the silver lining, primarily that there’s still a (large) audience for journalism, and every writer out there has the potential to reach that audience with free distribution and sharing tools. He offers up potential business models for the future, which are ripe for debate.
- How much journalism in the future will happen through big organizations/corporations versus individuals or small endeavors?
- How quickly and how successfully will journalism transition to subscription- and reader-based revenue models rather than advertising models? How quickly will advertising plummet for legacy news orgs—and is native advertising a stop-gap measure rather than a long-term solution?
- How will business models differ between the general-interest news gathering operations versus niche/specialized areas? It seems quite easy to predict the success of subscription-based models around special-interest areas, or topics with high value to the reader (financial and business news, for example). Perhaps general-interest news gathering or news brands will dwindle down to a handful of big, influential brands, e.g., The New York Times and The New Yorker?
US Consumers’ Biggest Purchase Influencers by Marketing Charts
I discovered this through Peter McCarthy’s Twitter feed (@petermccarthy)—a great follow for any author who’s interested in digital marketing.
The graph you’ll find at the link confirms some of what we already know: word of mouth is the No. 1 influencer of purchases. What’s more interesting and maybe surprising is how the rest of the list stacks up:
- “An online review by someone you do not know in real life” ranks several influence points higher than a magazine ad.
- Ads delivered by social media platforms are near the bottom of the influence list, only beating out video game advertising and a text-message ad (the worst purchase influencer).
- An e-mail from a company or brand ranked below newspaper ad, but above radio and in-theater advertising.
- I would love to see how this chart may have changed over time. Has social media advertising gone up or down in these rankings? Have traditional media ads declined over time? I couldn’t find any comparison data.
What questions (or answers) do you have? Share in the comments.