Launching today
LikePulse
See exactly where YouTube audiences react — instantly
52 followers
See exactly where YouTube audiences react — instantly
52 followers
LikePulse analyzes YouTube comments in real time to show you the exact moments where audiences peaked. Open any video and get: • Engagement heatmap — comment spikes overlaid with Most Replayed data • Key moments — the exact timestamps with the highest audience reaction • AI analysis — Claude Haiku explains why each moment resonated • Product detection — AI finds Amazon products mentioned in the video Free. No account. No tracking. Works on any YouTube video instantly.
@adriancubas Congrats on the launch Adrian. I could see this being big with creator/brand partnerships.
@zolani_matebese Thanks so much! Really appreciate the support — it means a lot on launch day. Absolutely — that’s one of the directions I’m most excited about. Creators and brands both want clearer insight into what actually resonates, and LikePulse can surface those moments instantly.
the product detection feature is the one that feels slightly out of place with the rest. heatmaps and key moments are clearly for creators and researchers. amazon product detection feels like a different user entirely, affiliate marketers or brand analysts. are those actually the same person in your head or did that feature come from a different use case you're testing. curious because it changes who you're building for pretty significantly
@ansari_adin That’s a great point — and here’s why I still think product detection can add value for creators and researchers. A lot of high‑engagement moments on YouTube revolve around specific products: tech reviews, unboxings, tutorials, “Amazon favorites,” beauty routines, etc. When a spike in reactions is tied to a product, identifying it helps explain why that moment resonated.
For creators, it highlights what their audience is reacting to. For researchers, it adds context to emotional peaks. So while the feature came from a different experiment, it actually complements the core insight workflow more than it seems at first glance.
knowing WHERE in the video people react is way more useful than just total view count. this is basically a free focus group for every video you publish
@tina_chhabra Exactly — that’s the whole point. Total view count tells you if people showed up, but knowing where they react tells you why the video works. When you can see those reaction spikes in context, it becomes a free focus group baked into every upload. That’s the kind of feedback loop creators rarely get, and it’s what I’m trying to make effortless with LikePulse.
Really like the framing of overlaying comment spikes with Most Replayed — the two signals say different things and the gap between them is where the interesting stuff lives. I run the Mod3Loop YouTube channel on financial modeling, and the moments people comment on are almost never the ones I'd predict from watch retention alone. Tools that surface that mismatch quickly would change how I edit. Following.
@samir_asadov Love this — and you articulated the core idea perfectly. Comment spikes and Most Replayed really are two different signals, and the gap between them is where the real editorial insight lives.
What you described about your channel is exactly the pattern I kept seeing: the moments people talk about are often not the moments they rewatch. Surfacing that mismatch instantly is what I built LikePulse for, because it changes how creators think about pacing, clarity, and emotional beats.
Really appreciate you following along — would love to hear what you discover if you try it on one of your videos.