When it comes to giving constructive feedback to an author about their book, not all criticism is created equal. Many items on an edit list are easy. “Clean up the copy here” or “flesh out your descriptions there” are impersonal and straightforwardly addressed. But sometimes, bringing up an issue with a book or an author can feel messy and intensely personal.
Sometimes a plot point or a character just doesn’t work. They feel wooden and unnatural, yet the author is convinced that they’re perfect. This is their artistic vision, after all. They’ve poured their heart and soul into their prose, and when it’s just the editor’s opinion against that of the author, who is to say who is right?
When advised to “kill their darlings,” many authors echo the words of “The Big Lebowski’s” The Dude: “That’s just like, your opinion, man.”
That’s where target reader feedback comes in.
When it comes time to give difficult feedback about a writer’s work, data-infused audience insights can act as a buffer between an editor or agent and the author.
In one recent Target Reader Manuscript Analysis (TRMA) report for a non-fiction project, around one-third of readers described how they perceived the author as arrogant and “braggy”—a major turnoff that made them dislike an otherwise very enjoyable and useful book. The passages cited were stories in which the author was describing his truly remarkable accomplishments in the business world, athletic arena, and life—the very same accomplishments that made other readers admire the author and trust his advice.
In short, it wasn’t the stories themselves that were the problem, it was how the author told these stories and described himself in them that rubbed readers the wrong way.
Telling an author, “Look, your book makes you sound like a jerk” is never fun or easy, particularly if the writer in question is already successful or a household name. Yet in examples like this one, patterns revealed in reader response data can help an editor or agent make their case for change (and make a book better) without seeming like the bad guy. Armed with target reader feedback, they can tell the author: “Look, this isn’t just me saying this—33% of readers think XYZ.”
Or, put differently: “That’s just like, the data, man.”