Talk to Your Analytics
Your AI agent can now answer any analytics question — from quick counts to multi-step analysis combining experiments, funnels, and retention. No dashboards needed.
If you use Claude Code, Cursor, OpenClaw, Codex, or any AI coding assistant — you already have an AI agent. It writes code, runs commands, creates files. Agent Analytics is what happens when that agent can also read your analytics.
We’re not selling you an agent. We’re the analytics platform your agent already knows how to use. Connect it, and every question you’d normally answer by opening a dashboard, your agent answers in seconds.
Quick questions
“How many signups from Germany this week?”
Your agent calls one endpoint:
47 signups from DE in the last 7 days — up 31% vs previous week.“Where are my users?”
US 4,231 events 1,847 users
DE 1,092 events 534 users
GB 876 events 421 users
FR 654 events 312 users
JP 498 events 267 users“Which pages have ‘pricing’ in the URL?”
/pricing 1,842 views 923 users
/pricing/enterprise 341 views 187 users
/blog/pricing-update 89 views 54 usersThese are single API calls. Group by country, substring match with contains, and get the answer back fast. Any agent can do this.
Where it gets interesting
The real power isn’t a single query. It’s combining them.
Our API is agent-first. Every endpoint returns clean, structured data that an agent can reason about. So when you ask a complex question, your agent pulls from experiments, funnels, retention, breakdowns, and queries, cross-references the results, and gives you an answer.
“Is the new checkout actually better?”
We’ve been running checkout-redesign for 14 days with enough traffic to be confident.
The free shipping badge is the clear winner — 17% more purchases than the original. People get to the payment step at the same rate, but more of them actually complete it. The badge removes the “what’s the total going to be?” anxiety right at the moment they’re deciding.
Removing the phone number field helped too — 8% more completions. Fewer fields, less friction, no surprise there.
The green CTA button did nothing. Literally 0.2% difference.
“Are organic users more valuable than paid?”
You’re spending $2,400/mo on Google Ads. Is it worth it?
Short answer: your organic users are worth about twice as much.
People who find you through search stick around — 18% come back within a week, 9% are still active after a month. They sign up at 12% and about 1 in 25 eventually purchases.
Your paid traffic looks good on the surface (similar visit counts) but the numbers drop off fast. Only 8% return within a week, 3% after a month. They sign up less and purchase at half the rate.
That $2,400/mo is bringing people who click, look around, and leave. Your blog content is doing a better job of attracting people who actually become customers.
“Monday morning brief”
This is where an agent fully replaces a dashboard. You ask for a weekly summary and it pulls everything together:
my-saas.dev — week of Feb 17–23
Good week. 8,234 events, 3,102 unique users — both up double digits. Your best week for signups since launch: 247, up 31%. Most of that came from Monday when your “Why We Switched” blog post hit the front page of Hacker News and drove 340 visits with a 12% bounce rate (your homepage bounces at 45% for comparison).
The funnel improved too — 4.6% of visitors now make it all the way from landing to first activation, up from 3.8% last week. That’s the onboarding changes paying off.
Two experiments running. pricing-test has a winner: showing annual plans first converts 18% better, and we have 1,200 exposures — that’s enough data, you can ship it. onboarding-v3 only has 89 exposures per variant, needs about 5 more days.
One thing to act on: that blog post is your best-performing content by far. Consider promoting it — the people it attracts are actually signing up.
Why this matters
A dashboard answers the questions you thought to ask when you built it. An agent answers the questions you think of right now — and it doesn’t just return a number, it tells you what the number means and what to do about it.
“Is the new checkout better?” isn’t a chart. It’s pulling experiment data, building funnels, comparing where users drop off, and telling you which variant to ship and why.
That’s the difference between analytics you look at and analytics you talk to.
Get started at agentanalytics.sh. API docs at docs.agentanalytics.sh. Open source on GitHub.
