Clientpulse
Voice of customer insights for PMs
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Alex Lider

Clientpulse - Voice of customer insights for PMs

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LLM-based clustering to organize support tickets into actionable topics. Monitor overall trends and drill down into individual mentions to uncover root causes. Built for PMs to understand customers at scale. Pricing starts at $0.02 per ticket.

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Alex Lider
Maker
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Hey Product Hunt! Super excited to launch the first version of Clientpulse! 🥳 We put lots of thought and intention into making this. We know that building a great product starts with understanding your customers — but this gets really hard at scale. When you have thousands of support tickets, reviews, and surveys, you might feel like you have some evidence of what users are asking for, but there's no quantifiable insight to back it up. I've been there. As a PM, I worked on customer support automation at a 20M MAU app and struggled with the same thing: – User interviews only capture a fraction of the full picture and take lots of time – Generic AI summaries miss critical details – Traditional clustering is outdated and lacks flexibility – Existing services are too expensive to try So we built Clientpulse: an LLM-powered clustering engine that turns unstructured feedback into clear, actionable topics. The first version includes: → Automatic tagging of support tickets. → Quantitative insights on recurring issues, product questions, and feature requests. → Drill-down into real user conversations to find root causes. → Adaptive topic modeling that evolves as customer queries change over time. We're gradually onboarding first users and testing analytics for reviews and other sources with early customers. So if you're working with large volumes of customer feedback, would love to chat and hear your thoughts!
Ilia Smetanin

Oh my this is just Ive been missing, thx for tge product team!

Ilya Farafonov

Looks very cool! Definitely gonna try it out. See u on demo call 🤝

Nik Voice

Support tickets is amazing source of isights! Usually I spend 3-5 hours per month to review tickets. With your tool I believe this process will be more effective! Good luck with the launch

Alex Lider
Maker

@nikolay_golos Great practice! Used to do the same. I think beyond a certain scale, it becomes really difficult to keep up. From talking to different teams, I’ve seen that once you hit about 1k tickets per month, manual review becomes too time-consuming, and quantitative approaches become more useful.

Aleksandr Lavrinenko
Hello Alex! Amazing idea! One of the companies that I worked for, did a simple version of it and it really busted support 🔥 Do you plan to do something like automatic answers based on cluster or you plan to go deeper in the analytics?
Alex Lider
Maker

@aleksanadr_lavrinenko Awesome to hear that even a simple version made a big impact on support! 🙌
Right now, we’re going deeper into analytics across multiple feedback sources, not just support tickets. I see much greater value in aggregating all customer feedback in one place.

That said, we’re also exploring a few interesting use cases like syncing tags back into helpdesk after clustering to help prioritize responses, and automatically generating tasks based on new topics, emerging bugs, or feature requests. 


However, we’re not focusing on chatbot automation, since there are already many solutions in that space.

Hina Siddiqui

This is a major win for PMs. Does it merge similar issues into one topic?

Alex Lider
Maker

@hina_siddiqui Great question!

We define a topic as a unique issue or request, formulated like a task name for development or resolution. If multiple users report the same problem, their feedback will be assigned to the same topic.


At the same time, related topics can be grouped into subcategories—for example, all issues related to notifications can be grouped together to track overall trend. That’s why we built a flexible taxonomy that can be adjusted as needed.

These rules are handled at the prompting level, and as LLMs improve, accuracy gets even better.

Jesus Porter

This could save teams a lot of time. Does your tool work with popular helpdesk platforms like Zendesk or Intercom or is it designed to be a standalone solution?

Alex Lider
Maker

@jesus_porter We primarily focus on integrating with Zendesk and Intercom to import and regularly sync new ones.
At the moment, we don’t send classified tickets back to the helpdesk as tags or custom fields, but it’s on our roadmap!

Harper Young

This is such a smart way to use LLMs. Does the clustering work equally well for short and vague tickets?

Alex Lider
Maker

@harper_young In most cases - yes! We don’t cluster entire tickets—instead, we first extract key highlights and then cluster them. This means that generic or low-context tickets (like spam or vague one-liners) usually won’t be categorized under something like “Issue” since they don’t contain enough signal to be classified meaningfully.

Nikolas Shevchik

Congrats, Alex, on launching Clientpulse! It looks like your tool can really save companies a lot of time, freeing up valuable resources to focus on what matters most. Wishing you continued success!

Daniil Andreev

Congrats with launch!
Excited to try it with my team

Alex Lider
Maker

@daniil_andreev Thanks! We should definitely chat 🤝

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