Answers Gallery
Business Questions to Ask Your Database
Question packs for the problems founders actually face — churn, MRR, signup funnels, inactive customers — answered from your database in plain English. No SQL required.
SaaS Churn
How to Measure SaaS Churn in Postgres — Without Writing SQL
Measure SaaS churn straight from your Postgres database in plain English. Monthly rates, at-risk accounts, and revenue lost — no SQL, no data team.
How to Measure SaaS Churn in Supabase — Without Writing SQL
Measure SaaS churn from your Supabase project in plain English. Combine auth.users with your subscriptions tables — no SQL editor, no data team.
How to Measure SaaS Churn in MySQL — Without Writing SQL
Measure SaaS or membership churn from your MySQL database in plain English. Monthly rates and at-risk customers — no SQL, no DATE_FORMAT headaches.
Stripe MRR
How to Track Stripe MRR in Postgres — Without Writing SQL
Track Stripe MRR from the data synced into your Postgres database — ask in plain English. Growth, expansion, and churn MRR without writing SQL.
How to Track Stripe MRR in Supabase — Without Writing SQL
Track Stripe MRR from your Supabase project in plain English. Turn synced subscription tables into growth, expansion, and churn MRR — no SQL.
How to Track Stripe MRR in MySQL — Without Writing SQL
Track Stripe MRR from billing data in your MySQL database in plain English. Growth, plan mix, and failed payments — no SQL or date-math required.
Signup Funnel
How to Analyze Your Signup Funnel in Postgres — Without Writing SQL
Analyze your signup funnel straight from Postgres in plain English. Find drop-off steps, conversion by source, and activation rates — no SQL.
How to Analyze Your Signup Funnel in Supabase — Without Writing SQL
Analyze your signup funnel in Supabase using plain English. auth.users signups, verification, and activation drop-off — no SQL editor required.
How to Analyze Your Signup Funnel in MySQL — Without Writing SQL
Analyze your signup or registration funnel in MySQL with plain English questions. Drop-off, activation, and weekly trends — no SQL, no date math.
Inactive Customers
How to Find Inactive Customers in Postgres — Without Writing SQL
Find inactive customers in your Postgres database with plain English questions. Win-back lists, at-risk revenue, and dormancy trends — no SQL.
How to Find Inactive Customers in Supabase — Without Writing SQL
Find inactive users in your Supabase project with plain English. Use auth.users last sign-in data to build win-back lists — no SQL editor needed.
How to Find Inactive Customers in MySQL — Without Writing SQL
Find inactive or lapsed customers in your MySQL database using plain English. Win-back lists and revenue at risk — no SQL, no DATEDIFF wrangling.
Cohort Retention
How to Calculate Cohort Retention in Postgres — Without Writing SQL
Calculate Postgres cohort retention in plain English. No complex CTEs or window functions required.
How to Calculate Cohort Retention in Supabase — Without Writing SQL
Analyze Supabase cohort retention without writing complex joins between auth and public schemas.
How to Calculate Cohort Retention in MySQL — Without Writing SQL
Get MySQL cohort retention insights in plain English. No more fighting with DATEDIFF or DATE_FORMAT.
Customer LTV
How to Calculate Customer LTV in Postgres — Without Writing SQL
Calculate Customer LTV in Postgres using plain English. No SQL or complex window functions required.
How to Calculate Customer LTV in Supabase — Without Writing SQL
Track Supabase Customer LTV using plain English. Easily join auth and public schemas without writing SQL.
How to Calculate Customer LTV in MySQL — Without Writing SQL
Get Customer LTV from MySQL using plain English. No more DATEDIFF or complex joins required.
ARPU
How to Calculate ARPU in Postgres — Without Writing SQL
Calculate Postgres ARPU in plain English. No SQL, CTEs, or window functions required for founders.
How to Calculate ARPU in Supabase — Without Writing SQL
Get Supabase ARPU insights without writing cross-schema SQL. Link auth.users and public tables in plain English.
How to Calculate ARPU in MySQL — Without Writing SQL
Calculate MySQL ARPU without the DATE_FORMAT headache. Plain English queries for founders and non-technical teams.
Net Revenue Retention
How to Calculate Net Revenue Retention in Postgres — Without Writing SQL
Calculate Net Revenue Retention in Postgres using plain English. No SQL, CTEs, or window functions required.
How to Calculate Net Revenue Retention in Supabase — Without Writing SQL
Get Net Revenue Retention for Supabase without writing complex joins across auth and public schemas.
How to Calculate Net Revenue Retention in MySQL — Without Writing SQL
Measure Net Revenue Retention in MySQL using plain English. No DATEDIFF or complex subqueries needed.
Daily Active Users
How to Track Daily Active Users in Postgres — Without Writing SQL
Get Daily Active User metrics for Postgres in plain English. No SQL or data team required.
How to Track Daily Active Users in Supabase — Without Writing SQL
Track Supabase DAU and user retention without writing complex SQL or managing schema joins.
How to Track Daily Active Users in MySQL — Without Writing SQL
Calculate MySQL Daily Active Users using plain English. No more struggling with DATE_FORMAT or DATEDIFF.
Duplicate Records
How to Find Duplicate Records in Postgres — Without Writing SQL
Clean up your Postgres database without writing a single line of SQL. Remove duplicate records using plain English.
How to Find Duplicate Records in Supabase — Without Writing SQL
Remove duplicate records from your Supabase project. Handle UUIDs and schema splits using plain English.
How to Find Duplicate Records in MySQL — Without Writing SQL
Clean your MySQL or WordPress database instantly. Remove duplicate records using plain English instead of SQL.
Anomaly Detection
How to Detect Anomaly Detection in Postgres — Without Writing SQL
Detect anomalies in your Postgres database using plain English. No complex SQL, window functions, or CTEs required.
How to Detect Anomaly Detection in Supabase — Without Writing SQL
Anomaly detection for Supabase made easy. Monitor auth and public schemas in plain English without writing complex SQL.
How to Detect Anomaly Detection in MySQL — Without Writing SQL
Detect anomalies in your MySQL database using plain English. No more struggling with DATEDIFF or complex WordPress schemas.
Inventory Reorder
How to Track Inventory Reorder in Postgres — Without Writing SQL
Manage your Postgres inventory reorders using plain English. No SQL knowledge required to track stock levels and lead times.
How to Track Inventory Reorder in Supabase — Without Writing SQL
Simplify Supabase inventory reordering. Query your stock and supplier data in plain English without worrying about RLS or UUIDs.
How to Track Inventory Reorder in MySQL — Without Writing SQL
Automate your MySQL inventory reorders. Get stock alerts and lead time analysis using plain English instead of complex SQL.
Sales Pipeline
How to Analyze Sales Pipeline in Postgres — Without Writing SQL
Get instant sales pipeline insights from your Postgres database using plain English. No SQL or data team required.
How to Analyze Sales Pipeline in Supabase — Without Writing SQL
Analyze your Supabase sales pipeline in seconds. Turn your auth and public tables into clear business insights without writing SQL.
How to Analyze Sales Pipeline in MySQL — Without Writing SQL
Turn your MySQL data into sales pipeline reports instantly. No more complex DATEDIFF or DATE_FORMAT queries.
Overdue Invoices
How to Find Overdue Invoices in Postgres — Without Writing SQL
Get instant answers about your overdue invoices in Postgres using plain English. No SQL knowledge required to track your aging accounts.
How to Find Overdue Invoices in Supabase — Without Writing SQL
Track overdue invoices in Supabase using plain English. Easily join auth users and public billing data without writing complex SQL.
How to Find Overdue Invoices in MySQL — Without Writing SQL
Analyze overdue invoices in MySQL using plain English. No more struggling with DATEDIFF or complex joins to find who owes you money.