DOCSEARCHbyAlgolia
Submit Docs

Stormly AI-Powered E-Commerce Analytics

website·Indexed 34 days ago

https://www.stormly.com/developer/docs/

AI-powered e-commerce and product analytics platform providing insights into conversion prediction, user retention, and revenue contribution. Features include deep event analysis, predictive root cause detection, and customer lifetime value tracking, with integrations for Shopify, Wix, Adobe Commerce (Magento), React, and Google Tag Manager.

Tokens
117.6K
Snippets
66
Records
863
Agent score
67%

What's inside Stormly

  1. Overview of Stormly for eCommerce Analytics

    Stormly is a commerce-aware analytics platform designed for retail teams. Unlike generic telemetry tools, it natively handles eCommerce-specific data models including SKUs, variants, bundles, returns, and subscriptions. It provides built-in merchandising analytics (attach rate, product mix, cannibalization, and margin opportunities) and AI-driven daily summaries with actionable insights.

  2. Overview of the Cart Abandonment Report

    The Cart Abandonment Report identifies specific points of revenue leakage by tracking items added to carts that were not purchased. Unlike sitewide abandonment rates, this report provides granular visibility at the SKU, brand, and category levels, allowing teams to identify systemic issues (e.g., poor size charts, pricing mismatches, or stockouts) and prioritize fixes based on lost revenue and margin.

  3. Overview of Stormly product analytics for e-commerce

    Stormly is an AI-powered product analytics tool specifically designed for e-commerce webshops of all sizes. Unlike traditional analytics tools, it uses GPT capabilities to act as a virtual data analyst, suggesting crucial product questions and answering them via automated dashboards and detailed explanations. Key capabilities include predictive analytics to forecast user retention and churn, and advanced user filtering to analyze specific e-commerce behaviors (e.g., tracking specific product types added to carts or items favorited during a user's third visit).

  4. Overview of Stormly MCP for Ecommerce Analytics

    Stormly provides an MCP (Model Context Protocol) server that bridges ecommerce analytics data with AI clients. This allows users to ask plain-language questions about revenue, SKUs, carts, orders, funnels, and retention. The system is specifically modeled for ecommerce domains, handling relationships between products, variants, brands, collections, and repeat buyers, and returns answers in Markdown format based on actual project data.

  6. Overview of Stormly no-code analytics

    Stormly is a data analytics platform that uses a no-code approach to generate actionable insights from large datasets. It leverages AI and machine learning algorithms to automatically scan raw data to identify patterns and trends without requiring manual programming, complex syntax, or trial-and-error testing. This allows non-technical users to perform complex analyses, visualize data, and build simple predictive models based on historical trends without relying on IT or data teams.

  7. Analyze event property distributions and percentiles in Stormly

    Stormly allows users to analyze the distribution of event properties, funnel conversion times, and session counts. By using custom calculations, you can derive specific statistics such as averages and percentiles to identify differences in user actions and metrics.

  8. Implement product-level analytics with Stormly

    Stormly provides a "third layer" of analytics that treats the product catalog as the primary dimension rather than a secondary filter. It eliminates the need for custom event definitions or BI requests to answer:

    • Which SKUs are dragging down overall conversion rates?
    • Which first-purchase products predict a returning buyer?
    • Where the checkout funnel breaks specifically by product.

  9. Optimize Stormly dashboard and report performance

    Stormly employs several infrastructure optimizations to maintain fast load times and reduce server strain as data scales:

    1. Smart Update System: To avoid wasting server resources, dashboards or reports that have not been opened in two weeks are automatically paused from auto-refreshing. They update immediately upon the next user access.
    2. Parallel Query Execution: For reports requiring multiple views (e.g., daily, weekly, and monthly views for 'Active Users'), Stormly runs these queries in parallel rather than sequentially.

    These optimizations have resulted in an average load time reduction of over 50% across all report types.

  10. Understand the difference between Product and Marketing Analytics for eCommerce

    In an eCommerce context, marketing analytics focuses on the 'top of the funnel' (acquisition), while product analytics focuses on 'inside the store' (behavior and retention).

    Marketing Analytics answers "Who came and from where?" It measures events that happen before a customer lands on the store, such as channels, campaigns, clicks, and cost per acquisition (CPA). Common tools include GA4, Meta Ads Manager, and Triple Whale.

    Product Analytics answers "What did they buy and whether they came back?" It tracks actions inside the store, such as order sequences, SKU-level conversion rates, cart behavior, and repeat purchase patterns. Common tools include Stormly, Mixpanel, and Amplitude.

  11. Use Stormly for eCommerce intelligence and merchandising

    Stormly serves as a specialized alternative to Power BI for eCommerce teams. While Power BI is a general visualization tool requiring manual data modeling for commerce logic, Stormly provides a native commerce model out of the box. It is specifically designed for merchandising and operations, featuring built-in support for variant funnels, SKU cohorts, returns, bundles, and subscription modeling. It integrates with Shopify, Magento, Adobe Commerce, WooCommerce, and BigCommerce.

  12. Stormly Product Analytics Platform Overview

    Stormly is an AI-powered data analytics platform designed for product managers to uncover patterns and insights from customer behavior. Unlike simple visualization tools, Stormly focuses on data analysis to identify trends, predict future performance, and pinpoint the "aha" moment when users find value in a product. It utilizes AI and GPT capabilities to act as a virtual product expert, posing relevant questions about product performance and providing answers via organized dashboards and comprehensive explanations.