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Stormly

Product analytics built for e-commerce teams

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Stormly is an AI-native analytics platform built for the complexity of eCommerce data. It unifies customer behavior, product, marketing, and business data from multiple sources into a single platform that not only reports what happened, but explains why it happened. Stormly's AI proactively identifies opportunities, detects anomalies, uncovers root causes, and recommends actions, while enabling teams to ask analytical questions in natural language through integrations with ChatGPT, Claude, Copilot, and other MCP-compatible AI assistants.

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Features

AI-powered root cause analysis for sales, conversion, and revenue changes

Natural language analytics through ChatGPT, Claude, Copilot, and MCP

Unified customer, product, marketing, and business data

Automated AI insights, anomaly detection, and proactive alerts

Product, merchandising, and inventory performance analytics

Marketing attribution and campaign performance analysis

Funnel, conversion, and customer journey reporting

Executive dashboards and customizable reports

Scheduled AI summaries delivered daily or weekly

Multi-source integrations including Shopify, Segment, RudderStack, GA4, custom APIs, and data warehouses

Enterprise-scale analytics capable of processing billions of events

Privacy-first architecture with no AI access to personally identifiable information

Use Cases

Understand why sales increased or decreased

Discover the root causes of conversion drops

Identify best- and worst-performing products and categories

Optimize marketing campaigns and advertising spend

Monitor merchandising performance and new product launches

Detect checkout and funnel bottlenecks

Receive proactive alerts before business issues become critical

Reduce preventable product returns through AI-driven analysis

Enable business users to query data without SQL or BI expertise

Provide executives with automated daily business summaries

Power AI assistants with real-time analytics via MCP integrations

Make faster, data-driven decisions across product, marketing, and eCommerce teams

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Comments

Hi everyone! 👋 We're excited to finally share Stormly. We built Stormly because we were frustrated that traditional analytics platforms tell you what happened, but leave you figuring out why. For eCommerce teams, that's often the hardest and most time-consuming part. Instead of adding AI as a chatbot on top of an existing product, we built Stormly AI-first from day one. Every part of the platform is designed to help you understand your business faster—from automatically finding the root causes behind revenue changes to proactively surfacing opportunities and recommending what to do next. Stormly also understands the complexity of eCommerce. It combines customer behavior, products, inventory, merchandising, marketing, and business data into one place, so you get answers in natural language instead of spending hours building dashboards or SQL queries. We'd love to hear your feedback, feature requests, and toughest analytics questions. Thanks for checking us out! 🚀

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Comments

Hi everyone! 👋 We're excited to finally share Stormly. We built Stormly because we were frustrated that traditional analytics platforms tell you what happened, but leave you figuring out why. For eCommerce teams, that's often the hardest and most time-consuming part. Instead of adding AI as a chatbot on top of an existing product, we built Stormly AI-first from day one. Every part of the platform is designed to help you understand your business faster—from automatically finding the root causes behind revenue changes to proactively surfacing opportunities and recommending what to do next. Stormly also understands the complexity of eCommerce. It combines customer behavior, products, inventory, merchandising, marketing, and business data into one place, so you get answers in natural language instead of spending hours building dashboards or SQL queries. We'd love to hear your feedback, feature requests, and toughest analytics questions. Thanks for checking us out! 🚀

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