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Today’s episode is inspired by something that many of us in the podcasting or even business world experience at some point: negative reviews. We covered negative client reviews a few weeks ago, but today I’m talking about a negative podcast review.
A few months ago, I received a review from a listener who was disappointed that I had ‘sold out’ because I started running sponsorship ads on the podcast. Now, I get it—change can be hard, and if you’ve been listening since the early days when there weren’t ads, this might feel different. But here’s the thing: sponsorships are what allow me to continue producing this show at a high level.
And today, we’re going to break down exactly why sponsorships exist, the psychology of customer reviews—especially the star rating system—and how we can reframe negative feedback as a sign of engagement and care from the audience.
Let’s dive in.
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About Dr. Jeremy Sharp
I’m a licensed psychologist and Clinical Director at the Colorado Center for Assessment & Counseling, a private practice that I founded in 2009 and have grown to over 20 clinicians. I earned my undergraduate degree in Experimental Psychology from the University of South Carolina before getting my Master’s and PhD in Counseling Psychology from Colorado State University. These days, I specialize in psychological and neuropsychological evaluation with kids and adolescents.
As the host of the Testing Psychologist Podcast, I provide private practice consulting for psychologists and other mental health professionals who want to start or grow psychological testing services in their practices. I live in Fort Collins, Colorado with my wife (also a therapist) and two young kids.
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Comments 2
Such a great discussion! One thing that really stood out to me is how reading and responding to reviews or other feedback you receive — whether for a presentation you did, a class you taught, or podcast episode you poured your heart into, or, if you’re a student, even something like a semester-long practicum—is an ideal use case for AI.
For example, you could try this: Save your reviews in a Word document without reading them, then ask ChatGPT to summarize them by highlighting:
* Your key strengths
* A little food for thought for polishing your product for next time
* 3–5 small action items to enhance your strong points and incorporate useful feedback
Bonus tip: if you get a review that stings emotionally, you can have AI craft a warm, professional response that honors the time the reviewer took, while still giving you space to process. A prompt like this can be useful: “I received this feedback, and it was tough to read. Can you draft a response that is professional, appreciative, and acknowledges the reviewer’s time, while also including one action item or takeaway I can use for growth?”
AI can’t erase the sting of criticism, but it can help us engage with feedback in a way that’s constructive rather than overwhelming. 🙂
Thanks for continuing to provide this invaluable service to all of us, Jeremy, and for leading with vulnerability!
Author
Thank you for the kind words and, as always, the insightful ideas! I love the thought of using AI to navigate reviews (and definitely tried it after reading your comment).