Clootrack

Are your customers switching brands? If so, do you know who they’re moving to, and why? Brands ask these questions every day. Investors ask them too, before backing any brand. In today’s fast-changing market, understanding customer movement is more important than ever. Here’s a faster, smarter way to track brand switching: by analyzing thousands of customer reviews with AI. It tells you not just which competitors are winning, but the exact reasons behind customer choices, from performance to reliability. Uncover why customers switch—and use those insights to win them back faster.

Setting up AI analyses can feel overwhelming, so many workflows, so little time. That’s where Clootrack Flow Store comes in. Hundreds of pre-built, battle-tested AI workflows are ready to plug into your data, whether it’s analyzing customer service agent behavior or discovering new product ideas. Transparent, editable templates mean less guesswork, fewer hours spent, and faster insights you can actually act on. See how quickly data can start working for you.

Clootrack customers just crossed 100 BILLION OpenAI tokens. A year ago, we migrated our unsupervised thematic analysis engine to OpenAI. And in February, we launched our Agentic Workflow Builder for voice of the customer analytics on OpenAI. Our customers started running VoC analytics on STEROIDS - using it to: Cut ecommerce returns by double digits Lift NPS within a quarter 3X product development speed Identify high-intent leads that drive topline growth Reduce call center agent churn by 10–20% Cut AHT by 10–15% Shorten investment diligence cycles by 23+ days Understand why customers churn and what jobs they’re getting done from each SKU All made possible by 98%+ accuracy, actionable granularity and repeatable results. But getting here wasn’t easy. It took 12+ months of iteration - We had to rethink our algorithm, our product definition, our dev process, even our team structure. We hit walls almost every day. What got us through was persistence - and a team that refused to ship anything less than enterprise-grade precision. Massive kudos to Clootrack team and customers who believed in the journey. If you’re exploring best practices to make your AI application truly production-ready - drop a comment below. Happy to share our internal notes on what worked (and what didn’t). Subbakrishna Rao Kirat Anand Gaurav Modi Sahej Sahni Jickson P Akhil Haridasan Bhavini V Aubin Mundol Hrithik Shukla Ashok Periya Swamy Kevin Dass Luke Presberg Marc Manara

Are your customers quietly moving to competitors? The real question isn’t just who they’re choosing, but why. By analyzing thousands of reviews with AI, you can uncover the reasons behind every switch, whether it’s performance, reliability, or something unexpected. Suddenly, what felt like guesswork becomes clear, actionable insight. See every switch coming—and act before your competitors do.

AI analyses shouldn’t take weeks. With Clootrack Flow Store, hundreds of pre-built workflows are ready to connect to your data, whether it’s spotting new product ideas or analyzing agent behavior. Less setup. More insights. Faster results. Turn your data into results, fast and simple.

First time at Groceryshop. AI was everywhere. So was AI readiness. Many were talking about unifying data silos. I was wondering - haven’t we had “data lakes” for a decade? Most don’t feel like lakes. They feel like swamps. While teams rush to Agentic AI, AI agents fail without clean, contextual data. What’s happening now: 1. Focus is shifting to building real data lakes. 2. Most are still fixing structured data. 3. Unstructured data (reviews, tickets, calls, chats) is waiting in the pipeline yet to be picked up. Usable AI agents may have to wait! At Clootrack, we realized this need early on. That is why we have these which no voice of the customer solutions have: 1. A configurable VoC AI data pipeline built for speed. 2. Turn messy, unstructured feedback into clean, labeled data with business context So MCPs and AI agents work as expected - and you can really reach your AI goals. Usable AI agents need usable data. As always, made some fantastic friends. Thanks, Matt Lee and Kirat Anand, for the photo.