Cycle App

We're excited to organize our first meetup in San Francisco tomorrow! We'll deconstruct PLG (Product-Led Growth) in the AI era with AJ from Census and Jacob from Beacons 🔥 This is an 𝗶𝗻𝘃𝗶𝘁𝗲-𝗼𝗻𝗹𝘆 𝗲𝘃𝗲𝗻𝘁, 𝗹𝗶𝗺𝗶𝘁𝗲𝗱 𝘁𝗼 𝗷𝘂𝘀𝘁 𝟯𝟬 𝗽𝗮𝗿𝘁𝗶𝗰𝗶𝗽𝗮𝗻𝘁𝘀 to keep it highly conversational. If you're a founder or product leader in SF, register now! Pizzas & drinks are on us 🤗 🗓️ Wednesday 31st of July at 5:30pm PST 📍 Census' San Francisco office Book your spot here 👉 https://lu.ma/d2y7m7qe

One of our most used dashboard to monitor Cycle's performance is our GraphQL performance metrics. 📈 During the last weeks, we reworked most of our SQL queries, added cache optimisations and improved our queuing strategy. The results are amazing 🔥 We went from an Apdex score (customer satisfaction) of 86% to 92% 🚀 Having that kind of observability is critical to correctly monitor the progression and identify performance flaws. This is why we built this dashboard a couple time ago, based on the prometheus plugin from envelop: https://lnkd.in/eSAtfgE8 🙏 If you want the same kind of dashboard, I made it available on the Grafana community dashboards (first comment) 👇

We're excited to co-organize an event with Census & Beacons in San Francisco. We'll discuss how to re-think product-led growth strategies with AI, from acquisition to retention. Can't wait to learn from Mehdi Boudoukhane, AJ Jindal & Jacob Choi-Durham's experiences! This is an 𝗶𝗻𝘃𝗶𝘁𝗲-𝗼𝗻𝗹𝘆 𝗲𝘃𝗲𝗻𝘁, 𝗹𝗶𝗺𝗶𝘁𝗲𝗱 𝘁𝗼 𝗷𝘂𝘀𝘁 𝟯𝟬 𝗽𝗮𝗿𝘁𝗶𝗰𝗶𝗽𝗮𝗻𝘁𝘀 to keep it highly conversational. Book your spot now! If you're a founder or product leader in SF, register now! Pizzas & drinks are on us 😋 🗓️ Wednesday 31st of July at 17:30 📍 Census' San Francisco office Apply here 👉 https://lu.ma/d2y7m7qe

Cycle's AI keeps getting better every week. Anytime you'd like to create a new feature, we suggest an AI-generated title.   We'll also match your naming style according to the five latest features you created in your workspace – feature category by feature category. Now Cycle's AI will take this into account and generate titles that make sense based on your style for each category.

Recency bias has bad press in product management literature. But when it comes to product feedback, I believe it’s a good bias to have. New product ideas actually are more valuable than old ones, especially when they emerge from recent customer interactions (as they should). I wrote a blog post about it. Read on if you want to learn why and how recency bias can help fight complacency and increase customer delight👇

Extract product insights from your Gong calls ✨ Automatically fetch sales call transcripts and process them all on autopilot.   You'll extract « voice of sales » insights: -What are the top feature requests, sorted by $ revenue impact? -What are the most common problems highlighted by top customers? -What are the best upsell opportunities? -What deals are blocked due to a missing feature?   Revenue teams love it as it helps them be analytical about their requests to the product teams: now they can put dollar values on feature requests!    Every feedback doc linked to a Gong call will have the embedded video as well as the title, participants & transcript.

I'll be in San Francisco with the Cycle team until Aug 10 – who wants to grab coffee or a beer? We'll be organizing a couple of AI meetups with other builders, stay tuned 👀

$10 billion business idea below. AI is completely changing how companies think about feedback. Organizations are sitting on a goldmine of feedback from various sources but aren't using it effectively. Take Success/Sales call recordings for instance, where you have: - Emerging trends and opportunities - Feature requests that are blocking deals - What customers love about your product - What customers don't understand about your product Yet, this info is nearly never analyzed by product folks because they just never get this data. Product folks thus work on initiatives identified through NPS surveys and other data that they easily get. The data leveraged is very incomplete, out of date, and often biased. A company should build an autonomous application. One that automatically captures ALL feedback sources: Customer calls, internal discussion channels, Sales CRM, Success CRM, emails, files, app reviews, forms, ... and anything else on the web or via API. Aka the big majority of feedback that never makes its way back to product folks. Then leverages AI to make sense of it and aggregate this data. Biggest problems, feature requests, frictions, loved features, etc. - all split by customer segments. Name it something like “Product Intelligence.” Is anyone building this? 👀

Make your release notes shine with Arcade, Loom or Tella embeds! My personal favorite is Arcade for beautiful product demos that aren't boring to watch (👋 Caroline ☺️) Check out the following Cycle App demo to get a feel for what's possible with Arcade 👇 https://lnkd.in/dAMXPYnf

New product updates in our latest changelog: ✨ Improved AI feature recommendations We’ve refined the logic for linking features to insights in autopilot mode. The matches are 🔥! 🛡️ SOC 2 Type 1-certified Type 2 is already underway 👀 ⚡️ Performance Improvements 🔗 Changelog - Embed your links Embed Arcade, Loom, Tella & YouTube links in your releases & changelog to make them shine. 🔧 API Tips 1) Trigger automations based on any property change in Cycle. 2) Leverage our script to import your Canny data to Cycle. 👉 Learn more and see other updates in our changelog: https://lnkd.in/e9RiQFJt