Congrats on the launch, @adi_patel! Love the loom demo. Would love to hear a concrete example of how a (hypothetical) team operates at the moment and where Lancey gives that team a big advantage. Also, what's the sweetspot teamsize where Lancey is really helpful?
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@mikekerzhner thanks Mike!
A product team at a Series B company that gets over 100+ feedback items from their customer channels (Gong calls, support tickets, emails, slack) won't spend more than 10 mins a week manually going through these items.
They end up prioritizing what the loudest voice wants due to lack of time to process all of this information.
Lancey comes in and automatically processes all of this, 24/7. When something important is picked up across all of these sources, we flag the insight to the right PM so they can figure out if its worth prioritizing along with what the impact of it can be.
And then post launch of a new feature, you can use our AI assistant (Merlin) to figure out if the users who complained about a feature or provided feedback actually ended up using the feature. Close the end to end loop!
Due to the nature of the product, Lancey customers typically end up being post-PMF companies (B2B/B2C are both fair game).
Hello PH community!
I'm the co-founder of Lancey. Excited to officially launch today!
Teams are spending more and more time on operationally heavy tasks. Things that don’t make an impact but need to be done. Work for the sake of it. One of the biggest unlock of using AI effectively is the ability to help improve productivity and get teams moving faster with less.
Product teams are guilty of this. We've built Lancey to help product teams make great product decisions while skipping the busy work.
We're starting with helping teams turn customer feedback into building blocks of what you can prioritize and defend. We'll be adding more surface area to the product so we can embed ourselves deeper into the product teams workflow.
Here’s what you can do with Lancey - example use cases:
🔁 Automatically set up AI agents to process, categorize and extract insights from customer feedback
🎫 Generate tickets and issues based on high impact areas
📈 Measure the impact of new feature launches
If you want to reimagine how the best product team work and have feature suggestions, drop a comment. We'll ship you Lancey merch if we end up building what you request.
@msnkarthik hey Karthik, don't have enough details on Zeda but very familar with Productboard. We've heard from customers and product teams that they end up spending a lot of time dealing with the firehose of feedback manually and when you have 1000+ items coming in weekly, things get missed easily.
We've eliminated the need to manually pull out the important bits from the feedback and automatically use your product context to figure out what's important and what product area it relates to. It means teams spend 30 hours less per work on operationally boring work while still seeing the same quality of insights!
Amazing! I find myself looking for automations to do what Lancey promises to do. I keep a giant database of all of our customer requests, complaints, bugs etc. and want someone to periodically categorize and summarize them. Would Lancey also help with querying customer conversations? For example, I find myself wanting to ask "which of our customers have complained about x?" But haven't found a great tool to do this.
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@luigi_la_corte1 you nailed it Luigi! Connect your sources of customer requests/complaints/bugs and Lancey will parse through it all, figure out the important insights and give you an easy way to build what your users want - in true YC style!
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We had this problem in a previous series B/C company. This is especially true when you have SMBs, because you have so many customers and all voice for something, but we didn't have time to go through ProductBoard to tag everything. It is possible, but then when we categorize based on tags, it's already diluted down.
Congrats on the launch @adi_patel and team!
A few questions:
1. I assume the reason this is special (and not like a copy all user feedback and paste them into ChatGPT, or RAG + LLM) is the app would abstract all of that away AND allow you to connect more variety of data like analytics (quant)?
2. How do you dogfood this product internall right now?
3. Love the fun name and logo - what's the story behind those?
Hey Lancey team, great job on the product. Lancey is my fav product of the week so far. Our team Jupitrr AI has been creating a similar database on notion from scratch so I totally feel the pain point your team is solving. Love the variables you made to quantify the potential impact of features (e.g users impacted) which we haven't yet.
I've connected you guys on LinkedIn, happy to get in touch and provide user feedback and support one another.
Congrats on the launch, this is a brilliant product solving a very important problem using LLMs to save product teams a significant amount of time. Keep up the great work @adi_patel and team!
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