Most analytics tools are great at recording what happened.
Which channel sent traffic last week? GA4 knows. How long did visitors spend on your pricing page? Hotjar can show you. Did that SEO article drive actual revenue? Good luck.
Connecting traffic to actual paying customers meant running exports, building spreadsheets, and making educated guesses. Every tool talked only to itself.
So I built Zenovay.
Revenue Attribution
Connect Stripe once. See exactly which traffic source, UTM campaign, or landing page converted into paid subscriptions. Not pageviews. Actual revenue per channel.
Heatmaps and Session Replay
See where visitors click, scroll, and drop off. Watch real sessions. Understand your pricing page before guessing your way into a redesign. Replays stored for 60 days on Pro.
Goals and Funnels
We ran our own signup funnel through Zenovay. 24,500 homepage visitors, 11,980 reached pricing, 1,753 signed up. Without funnel tracking those are just two numbers with no story. With it you know exactly where to focus.
AI Insights and Anomaly Detection
This is the "tell me what to do next" part. Instead of staring at dashboards, Zenovay surfaces what changed and why it matters. Unusual traffic spike? Conversion rate drop? You get flagged before your morning review.
Google Search Console Integration
See which organic keywords bring paying customers, not just curious readers.
Uptime Monitoring and Error Tracking
Also included. No extra plan needed.
Everything above lives in one dashboard, one script tag, events processed in under 100ms.
Pricing
Free: 3,000 events/mo, 1 site, real time dashboard, revenue attribution.
Pro: $20/mo, 50K events/mo, 10 sites, session replay, heatmaps, AI insights, retention analytics.
Scale: $90/mo for agencies. Adds SQL query access, white label, B2B company identification.
What it is not
Not open source or self hosted. Not a PostHog replacement if you need feature flags or A/B testing. For those needs, PostHog or Plausible are honest better fits and I will say so.
Zenovay is for solo founders and small SaaS teams who want one clean answer: what is making me money this month?
How many analytics tools are currently in your stack, and what is the one question none of them can answer?
zenovay.com
The revenue attribution piece is what makes this stand out. I've been running a SaaS for AI-generated ad creatives and the biggest gap in our analytics stack is exactly what you described — we can see traffic sources all day, but connecting a specific UTM campaign to actual Stripe revenue requires duct-taping together GA4, Stripe exports, and a spreadsheet that nobody trusts. The fact that you built the Stripe integration as a first-class feature rather than an afterthought tells me you've actually lived this problem.
Honest question about the AI insights — how do you handle the signal-to-noise ratio? My worry with automated anomaly detection is that early-stage products have so much natural variance (a single Reddit post can 10x your traffic for a day) that everything looks like an anomaly. Do you have a way to calibrate the sensitivity based on traffic volume or product stage?
Also really respect the "what it is not" section. That kind of honesty about scope builds way more trust than trying to be everything. Bookmarking this one.