Do you also spend hours organizing and analyzing feedback?
There's a better way. Olvy integrates with your Slack, Zendesk, Intercom, Hubspot, and everywhere your users are to bring all your user feedback in one place and analyze it all using AI 🪄
Hey Product Hunt 👋,
We are super excited to showcase Olvy on ProductHunt today!
Multiple brainstorming sessions, hundreds of Figma designs, and thousands of lines of code, all to help you collect, analyze and reply to user feedback in snap 🫰🏻
Olvy is built to help product teams manage the complete feedback loop; here’s everything that you can do:
1️⃣ Collect user feedback: Need a feedback widget? Or do you need a tool to listen to user feedback on your Slack/Discord community? No matter where the feedback is, Olvy is there to collect it.
2️⃣ Reply to user feedback: Are your users finding out their issue was fixed through your tweets or newsletters? Why not reply to them right where the feedback came from, like directly on Slack? It’s impossible to do manually, but what if you can do that directly in one single dashboard? That’s exactly what Olvy can help you with.
3️⃣ Keep your dev team in loop: It’s essential to pass the complete context of user feedback which includes feature requests or bugs to your development team. Olvy lets you pass the complete context on what the users said and also creates issues directly into your issue tracker. Isn’t it cool?
👑 Analyze user feedback with AI: It can be hard analyzing hundreds, if not thousands, of user feedback at once. Olvy ingests all your user feedback, runs it through our AI and lets you know what users are talking about in simple, easy-to-read pointers.
5️⃣ Announce changes: Fixed a bug or shipped a new feature? It's time to notify users, Olvy lets you directly notify the user at the source and also publish your changelog that can be read by everyone. Also, did I mention it can be multilingual, and there’s an in-app notification widget too?
Join us in shaping the future of product management, we’re just getting started!
-Arnob
Congrats on the launch team Olvy! Love the launch video too - it gets you into the groove 😎.
The product looks great. I can tell a lot of work went into this.
It seems Olvy automatically categorises user feedback. But what if the AI gets it wrong? Do users have the ability to override the decisions from the AI in this case?
Last question - What's the next step for Olvy ❓
@ed_forson Hi Eddie, Thankyou.
The AI is only on the frontline to save people time. It rarely gets things wrong, but if it does you can override any AI decision in the product.
We've a lot planned in the coming months, but all of it at the core is about helping people listen to their users better so they can build better products.
This is amazing. And the website is one of the best I've seen in much time! I'm wondering, is there an in-app chat? Or does it automate emails? We don't like using private chats for feedback...
@alvarovillalb_ Hi Alvaro, we don't have an in-app chat but connect with your existing in-app chat tool and help to collect feedback from there without any effort. You can setup automations on email, and you also get a feedback page.
Congratulations on the launch ?makers Love how the team is using AI for feedback summarization and translation. Also feedback to engineering tickets is💡And awesome video as always @iamarnob6543 👑
Congrats on the Launch Arnob! 🚀 Feedback is very important, especially for early stage startups, to find out where and how the product is positioned. This seems to be helpful!
Congrats on launching! 🚀 Super valuable for making user feedback actionable and improving your product! By the way I love the design of the launch page and Olvy AI page 👏
@sentry_co Hi Andre,
Once feedback starts flowing into your Olvy workspace, it's run through sentiment analysis, keyword extraction, and tagged based on its type.
This makes a bunch of qualitative metadata available to you which you can use to get to your own insights. For example, the Olvy AI Copilot can help you answer questions like,
"Which features are getting the most bug reports?"
"What are the top feature requests?"
"What is overview of everything my users are asking for?"
...
and a lot more
The AI Copilot helps you summarize everything, and it also integrates with your CRM so you have a sense of what impact will resolving a feedback have on your revenue.
I'd highly recommend, signing up and uploading any CSV or Excel file you have with some of your user feedback to see the platform in action. Happy to answer any questions.
@nshntarora We only have Google analytics user patterns so far. And some from Crisp chat. But user feedback is usually mostly feature requests etc. I think the goldmine is to analyse observable google analytics data. But I have not found anything that does this yet.
@sentry_co That's sounds like a good idea, would love to get more of your thoughts on this.
What question do you find yourself asking? and maybe what would an ideal solution to that question look like for you?.
@nshntarora The data is there. We just have to interpret it. With observable telemetries you can almost read peoples thoughts. But there are no tools to sort and make sense of the data at scale. Not that I am aware of. now with AI. Someone should be able to do it.
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