Trying out the Stefan Caray thing
So, I kept bumping into this name, Stefan Caray, mentioned here and there online. Mostly in old forum threads, talking about some way he had for looking at feedback, user comments, that kind of stuff. It wasn’t the usual keyword counting or sentiment analysis junk. Sounded a bit different, more about the ‘why’ behind the comments. Curiosity got the better of me, so I figured, why not try and figure this out myself? See if it actually works or if it’s just talk.
First thing, I tried digging up more about this ‘Caray method’. Man, that was tough. Found almost nothing solid. No manual, no proper guide. Just scattered mentions, vague descriptions. Felt like chasing a ghost. But okay, I had a rough idea – something about looking past the surface words, trying to get the real feeling or intent.
Alright, step one: I pulled together all the user feedback we got over the last, say, six months. Emails, support tickets, forum posts, the lot. Dumped it all into one massive document. It was a big pile, let me tell you.
Then the real work started. I just began reading. Slowly. Didn’t rush it. Instead of just tagging ‘bug’ or ‘feature request’, I tried to use tags based on what I thought Caray was getting at. Stuff like:
- User feels stuck
- Excited but confused
- Annoyed with step X
- Likes it but wants more depth
Yeah, sounds a bit wishy-washy, I know. And it felt like that at first. Just pure guesswork sometimes. I’d read a comment, tag it, then come back later and wonder what I was thinking. Had to refine my tags as I went. Spent a few solid afternoons just reading, tagging, re-reading, re-tagging. Lots of coffee was involved.
Sorting through the mess
Once I had everything tagged with these new ‘feeling’ labels, I tried sorting the feedback using them. At first, it just looked like a different kind of mess. Not sure what I was expecting, maybe some magic insight to jump out. It didn’t.
But I stuck with it. Started grouping comments with similar feeling-tags together. Played around with it. Moved things about. It was more art than science, felt like I was sorting socks or something. But slowly, very slowly, some patterns started to kinda… emerge. Things I hadn’t really noticed when I just looked at keywords or simple positive/negative scores.
For example, I saw a strong link between people tagged as ‘Confused by onboarding’ and those who stopped using the thing after a week. Obvious maybe? But the standard analysis missed the ‘why’ – the confusion part was clearer with this approach.
So, what happened in the end?
Did I find some secret Stefan Caray formula? Nope. Still not entirely sure if it’s a ‘real’ defined method or just someone’s personal habit that got named. But the exercise itself was useful. It forced me to slow down and actually read the feedback, to think about the person writing it.
The main takeaway for me was this: it shifted my perspective. Instead of just tallying complaints or requests, I got a slightly better feel for the user’s journey, their frustrations, their little moments of delight. It didn’t give me a neat report with charts, but it sparked ideas for improving some specific communication points and tweaking a couple of confusing features.
Was it efficient? Hell no. Took way longer than running some analysis script. Would I do it all the time? Probably not on this scale. But as an occasional exercise to get a different angle on user feedback? Yeah, I think it was worth the effort. Sometimes you just gotta roll up your sleeves and wade through the raw stuff yourself to really understand what’s going on. This Caray thing, real or not, gave me a good excuse to do just that.
