Publishing’s Spider-Man Tweaks Author Earnings

It’s now roughly the two-year anniversary of Author Earnings, first launched in February 2014 by indie author Hugh Howey and “Data Guy.” It’s an ongoing effort to bring data-driven analysis and transparency to ebook earnings and sales—using Amazon sales rank as a key indicator.

Data Guy is the pseudonym of the person behind the data analysis of Author Earnings, now out with a February report. It’s over twenty dense pages in PDF form, and its pronouncements—derived from a software spider’s scrapings of Amazon sales pages—are, as usual, optimistic for those who hope for financial success as indie authors.

Our position on the Author Earnings project is that it’s valuable as a complement, however controversial, to standard industry statistics programs such as BookStats and Nielsen BookScan, the latter of which has smartly been provided by Amazon to Author Central participants since 2010.

Author Earnings is, however, driven by an agenda: its goal is to portray self-publishing as a viable financial option to—and even a superior choice over—trade publishing. Its digital data-harvesting mechanism is as arcane as the sales-to-rank formula that estimates what the spider’s scrapings mean. This is why Author Earnings can seem like counting the leaves that fall off a tree in the autumn to estimate how green the branches will be in the spring.

While the new report is interesting for its claims of indie dominance of Amazon bestsellers, its first-time inclusion of print (and audiobooks), and its commentary on Big Five agency pricing, our interest here is on two other points:

  1. A change in methodology ahead of Data Guy’s presentation at Digital Book World in March.
  2. A revelation that the old methodology, quoting Data Guy, “overestimated overall Amazon Kindle sales by roughly 18 percent.”

We asked Data Guy whether authors are actually sharing their royalty statements, as the report indicates. Data Guy wrote back to us: “Obviously sensitive info, so I’ll be deliberately vague, but yes. New approach takes out human element completely—no more informal spreadsheet reporting, no selection bias or possibility for skewed reporting or mistakes. And done at much larger scale now.”

When we asked Data Guy how many authors are in this baseline pool, sharing royalty statements, the answer we received was “More than a dozen now, and growing.” This seems a small sample of author input, even if the group participating comprises major indie bestsellers with many titles on the market.

Bottom line: While Data Guy is one of the most good-natured folks with whom we work—he and Howey have never seemed less than earnest about contributing meaningful data to the industry—the Author Earnings mission and its approach remind us that no statistical system is without flaw. At best, Author Earnings still uses “found data”; Amazon and other major online retailers don’t report ebook sales data. We approach all statistical appraisals of the industry with caution; one should always consider agenda and methodology.