Daniel and Chris groove with Jeff Smith, Founder and CEO at CHRP.ai. Jeff describes how CHRP anonymously analyzes emotional wellness data, derived from employees’ music preferences, giving HR leaders actionable insights to improve productivity, retention, and overall morale. By monitoring key trends and identifying shifts in emotional health across teams, CHRP.ai enables proactive decisions to ensure employees feel supported and engaged.
Jeff Smith: So let me do two things. I’ll take you through the use case. And so I’m now cherry-picking certain data points, and addressing it… But, I mean, the short answer on your question is it depends on your baseline, repeated listening, tilt your mood in a direction, based on certain behaviors you’re doing. So I would say short answer is it depends. And I can kind of walk you through how it works, and then it’ll be fun to get your response on it. And then of course - I mean, that can go into the AI, and what… Let’s start high level.
Music, like AI, artificial intelligence, it’s limited inputs, exponential outputs. If you look at music, there are 12 notes. You’ve got seven letters, you’ve got major/minors, but in the end, you’ve got 12 notes, and that gives you everything from Mozart to Megadeth.
Then you look at music behavior. People on average, like I said, listen to so much music. But then how they’re doing it, when they’re listening to it, their playlist, the repeat, and everything else. And so all that data is there, and we’ve built the engine to capture that, and then AI to analyze, interpret, decode for wellbeing.
And if you look at – I guess on the AI side, you’ve got the traditional to discern the mood of the user from the acoustic features (a lot of what I described from the songs) and then generative to customize messaging, and so what that output is. But if you look at an experience inside of a company, a use case - so you’re an employee at a company, you get an email from HR “Hey, we’ve partner with these rock and rollers of corporate wellness. We care about your personal wellness journey. Opt in with your Spotify, Apple, YouTube, get free perks along the way. Learn more about yourself. All data’s anonymized. We’re looking for trends on how to better serve you, your job and your wellness.”
And so like I said before, we wanted to tap into their current music listening, not create another app they had to download, but it’s just say “Hey, this is the behavior. This is how you’re listening to -” I think say Gregorian chants, and what’s going on in the background.
And so what happens is when that user opts in, there are two paths. One’s for the organization end. The data is anonymized, clustered… They’re looking for trends. This way, an executive/leadership team can look at dashboards, report outs, company-level, department, division, down to team. You don’t want to get to the individual to avoid any liability of selection. “Hey, Johnny [unintelligible 00:26:48.13] was listening to Kid Rock and he got fired.” You want to avoid the one-to-one. But they want a better solution for insights that are one to many. And then you have bespoke recommendations for how to actually intervene or serve those teams.
On the individual side, they’re offering more intel about their emotional buoyancy. After a few weeks, they get a weekly email, encouraging them to check out their E-score. So think of a WHOOP band for mental health. Your sleep score. What does that data point on you? What does it say about you? Because your interaction with music is unique. And they love that, because it’s a data point in their life and wellbeing.
And then we throw in that little added perk, because we do want them to feel seen and heard. “Hey, it looks like you’re feeling a little melancholic this week. Here’s [unintelligible 00:27:31.27] your favorite coffee spot.” How do you actually take that data, not only to be self-aware, but given tools for self-regulation, and everything.
And so when you look at that model, it’s very personal, yet anonymized on the organization side. And so we’ve always had that tension to make sure we have a strong firewall. But then as we work with them and as they listen more and more, it just get smarter, smarter, smarter. It’s fascinating.
[27:59] So to answer your question, I personally don’t know, if you were listening to Taylor Swift this afternoon and then the Wiggles in the morning, how you’re feeling. But I can tell you by running through Chrp for a few weeks, you will see a mirror of your emotion, which is fascinating.