Funnel analysis is how you find where users drop off. If 1,000 people sign up but only 50 convert, something is breaking between step 1 and the end. The answer is in your database. The problem is getting to it without a SQL developer or an expensive analytics platform.
This guide shows you how to run funnel analysis directly from your database — PostgreSQL, MySQL, Supabase, whatever you're running — without writing a single SQL query.
What Funnel Analysis Actually Requires
Every funnel has the same basic structure: users enter at step 1 (signup, first action, page view), some reach step 2, fewer reach step 3, and a fraction convert at the end. Your job is to measure the drop-off at each step.
To answer that from a database, you need event counts, user sequences, and time-bounded aggregations. In SQL, that's JOINs, CTEs, and window functions — not beginner territory. For most product managers, CS leads, and founders, that means waiting on an engineer who has five other things queued up.
Your Options (And Their Real Costs)
Option 1: Hire a data analyst. Weeks to onboard, $80k+ per year, and you still have to explain what you want.
Option 2: Mixpanel, Amplitude, or PostHog. These work well if you instrumented events from day one using their SDKs. If your data is already in your own database — which it is for most SaaS products — these tools can't touch it.
Option 3: Query your database directly in plain English. That's what this guide covers, using AI for Database.
How to Run Funnel Analysis With AI for Database
AI for Database connects to your existing database — PostgreSQL, MySQL, Supabase, BigQuery, and more — and lets you ask questions in plain English. No SQL required, no schema knowledge needed.
Here's how a typical funnel analysis session looks:
1. Connect your database in one click. 2. Type your question exactly as you'd ask a colleague. 3. Get a table or chart instantly. 4. Save it to a dashboard that refreshes automatically.
Funnel Questions You Can Ask in Plain English
These are real queries you can type directly into AI for Database:
"How many users signed up last month and completed onboarding within 7 days?"
"Show me the drop-off between signup and first purchase for the last 90 days."
"What percentage of trial users converted to paid in Q1 2026?"
"Which pricing plan did most users choose when converting from trial?"
"Show a weekly breakdown of signup-to-activation conversion for the last 12 weeks."
"How long does it take the average user to go from signup to their first paid invoice?"
Each of these maps to real SQL under the hood — you just don't have to write or debug it.
Building a Live Funnel Dashboard
One-off queries are useful. But what you really want is a dashboard your whole team can check every week without asking you to run anything.
In AI for Database, each query becomes a dashboard panel. Set the refresh interval — hourly, daily, weekly — and the data stays current without any manual work. Your CS lead can check activation rates on Monday morning. Your founder can see trial conversion every day. No one needs to ping engineering.
A useful funnel dashboard typically includes:
- Signups this week vs last week - Signup-to-activation rate (7-day and 30-day) - Trial-to-paid conversion rate by cohort - Time-to-convert distribution - Drop-off by step for the current onboarding flow
What Data Do You Need in Your Database?
Funnel analysis requires that you're already storing key user events. Most SaaS products do this by default. You need at minimum:
- A users table with a created_at timestamp - Some record of key actions: onboarding completion, first usage event, subscription start - A way to link users to their actions (user_id)
If you're using Supabase, this data is almost certainly already there from your auth and application tables. Same for apps built on PostgreSQL, MySQL, or any standard relational database.
Funnel Analysis vs. Mixpanel: When to Use What
Mixpanel and Amplitude are purpose-built for event tracking. If you're starting fresh and want rich behavioral analytics with session replay and cohort analysis, those tools are worth considering.
But if your data is already in a database — which is true for most B2B SaaS products, internal tools, and anything built on Supabase or PostgreSQL — you don't need to duplicate it into a third-party platform. Query what you already have.
AI for Database doesn't require you to re-instrument your app or change how you store data. It meets your data where it is.
Common Questions (From Teams Who've Been Here)
Q: I need to see where users drop off in my onboarding but I don't know SQL. What should I use?
If your event data is in PostgreSQL, MySQL, Supabase, or any standard database, AI for Database lets you ask this in plain English and get a table back instantly. No SQL, no analyst.
Q: Can I do funnel analysis without Mixpanel?
Yes, especially if you're storing user events in your own database. Mixpanel requires you to send events to their platform. If your data is already somewhere, skip the duplication.
Q: My team wants to check conversion metrics but no one knows SQL. Is there a self-serve option?
That's exactly what AI for Database is built for. Connect once, then your whole team can ask questions and view shared dashboards — without anyone needing to know SQL.
Q: What databases does this work with for funnel analysis?
PostgreSQL, MySQL, Supabase, SQLite, MongoDB, BigQuery, Snowflake, MS SQL Server, PlanetScale, and more.
Get Started
If your team is flying blind on conversion and activation because no one wants to write SQL, that's a solvable problem today. Connect your database at aifordatabase.com, ask your first funnel question in plain English, and have an answer in under a minute.
No setup, no re-instrumentation, no waiting on engineering.
Start querying your database for free → Connect in 2 minutes at aifordatabase.com, no SQL required.