Open Analytics 0.7.0

Product Introduction

1. Definition: Open Analytics 0.7.0 is a privacy-first, AI-native web analytics platform. Technically, it is a server-side analytics solution built on ClickHouse, designed to process and query high-volume event data in real-time without relying on client-side cookies.
2. Core Value Proposition: It exists to provide businesses with actionable, revenue-attributed insights into their website traffic while eliminating the legal and technical complexity of traditional analytics. Its primary value is delivering Google Analytics-level functionality—including funnels, user journeys, and revenue tracking—through a lightweight, cookieless script that is inherently GDPR-compliant and requires no consent banner.

Main Features

1. Cookieless, Privacy-First Tracking: The platform uses a daily-rotating anonymous hash to identify unique visitors, collecting only pageviews, referrers, device data, and custom events. It honors privacy signals like Global Privacy Control (GPC) and Do Not Track (DNT), discarding those visits entirely. This technical approach ensures compliance with GDPR, ePrivacy, and other global privacy regulations by design, not as an add-on.
2. AI-Powered Analytics & MCP Server: Beyond dashboards, Open Analytics integrates an AI chat assistant directly into its interface. Users can ask questions in plain English (e.g., "Which page brings the most signups?") and receive direct answers. Furthermore, it provides a Model Context Protocol (MCP) server, allowing users to connect their analytics data directly to AI assistants like ChatGPT or Claude for advanced, conversational querying.
3. Revenue Attribution from Stripe & Polar: This feature directly connects to payment processors via read-only API credentials. It automatically attributes Stripe payments and Polar orders to the specific website visit, page, and marketing campaign that generated the revenue. This works by matching the anonymous visitor ID from the website session with the customer ID captured during the checkout process on the connected platform.
4. Real-Time Dashboard & Live Globe: The dashboard updates visitor counts, sources, and key metrics in real-time without manual refresh. The Live Globe visualization plots active visitor sessions geographically on a 3D globe in real-time, providing an immediate, intuitive view of global traffic flow.
5. Visitor Journey & Funnel Analysis: Every anonymous visitor's path through the site is recorded as a chronological session replay, showing page sequence, referrer, and device. Users can define custom funnels (e.g., "Saw pricing > Started trial > Paid") to visualize drop-off rates at each conversion step, identifying precise friction points in the user experience.
6. Core Web Vitals Monitoring: Measures real-user metrics (RUM) including Largest Contentful Paint (LCP), Interaction to Next Paint (INP), Cumulative Layout Shift (CLS), and Time to First Byte (TTFB). Data is segmented by device type (desktop/mobile/tablet), preventing performance issues on mobile devices from being masked by faster desktop averages.
7. Open Source & Self-Hostable: The entire codebase is licensed under AGPLv3 and available on GitHub. Users can deploy Open Analytics on their own infrastructure (e.g., private VPS, Kubernetes cluster) for full data sovereignty, or use the managed cloud service hosted in Helsinki, Finland. Both options offer identical feature sets.

Problems Solved

1. Pain Point: The legal and UX burden of cookie consent banners. Many analytics tools require cookies for user identification, triggering mandatory consent mechanisms under GDPR. Open Analytics' cookieless architecture removes this requirement, allowing site owners to maintain a clean user interface and avoid potential compliance fines.
2. Pain Point: Data silos between marketing analytics and revenue data. Traditional tools show traffic sources but fail to connect them directly to actual payments. Open Analytics solves this by directly attributing Stripe and Polar revenue to marketing campaigns, pages, and referrers, answering the critical question of ROI.
3. Target Audience: SaaS founders and product managers who need to understand user behavior and conversion funnels to optimize growth; marketing teams requiring clear attribution for paid ads (Google, Meta) and organic campaigns; developers and privacy-conscious companies in the EU seeking a compliant, self-hostable analytics alternative to Google Analytics.
4. Use Cases: A bootstrapped SaaS company needs to see which blog post or Product Hunt launch is actually driving paid subscriptions. A marketing agency needs to prove the ROI of a client's ad spend by linking Facebook campaign traffic directly to Stripe revenue. An EU-based enterprise must deploy analytics on its intranet or customer portal without violating strict data residency and privacy policies.

Unique Advantages

1. Differentiation: Unlike Google Analytics 4, it is cookieless by default and offers built-in revenue attribution. Compared to privacy-focused rivals like Plausible and Fathom, it includes advanced features like AI chat, full visitor journey analysis, and Core Web Vitals out-of-the-box, without requiring business-tier plans. Its open-source model contrasts with closed-source competitors like DataFast.
2. Key Innovation: The integration of an MCP (Model Context Protocol) server for AI assistants is a significant technical innovation in the web analytics space. This transforms the platform from a passive reporting tool into an interactive analytics copilot, allowing users to query complex datasets through natural language within their existing AI workflows.

Frequently Asked Questions (FAQ)

1. Is Open Analytics really GDPR compliant without a cookie banner? Yes. Because it uses a daily-rotating anonymous hash and stores no personal data or persistent cookies, it does not require user consent under GDPR. It also honors GPC and DNT signals, deleting those requests entirely.
2. How does the revenue attribution work technically? You connect your Stripe or Polar account via a read-only API key. When a payment is recorded, Open Analytics matches the customer's browser session ID (collected during their site visit) with the customer ID in the payment platform, attributing the revenue to the specific page, campaign, and referrer of that visit.
3. Can I import my historical data from Google Analytics or Umami? Yes. Open Analytics supports importing historical data via export files from Plausible, Fathom, and Umami. You upload a ZIP file, review the mapped data, and confirm the import. This allows for a seamless transition without losing trend history.
4. What is the performance impact of the Open Analytics script? The tracking script is approximately 2 KB when gzipped. It loads asynchronously, meaning it does not block page rendering. It records the first pageview before its own configuration fetch completes, minimizing any impact on site speed and Core Web Vitals.
5. What happens if I exceed my monthly event limit? Based on the provided pricing, plans have hard limits (50K, 500K, 5M events). The platform would likely stop recording new events until the next billing cycle or require an upgrade to a higher plan. For precise overage policies, consulting the official documentation is recommended.