Analytics SaaSConceptSignalboard
Product analytics with funnels, retention and plain-English questions.
A product analytics SaaS: dashboards, funnels, cohort retention, experiments and an AI assistant that answers questions and shows the SQL.
- Category
- SaaS · Product Analytics
- Designed for
- Web
Why Signalboard exists
The problem
Product teams have data in many tools but still struggle to answer simple questions about activation, retention and what drives upgrades.
The product
Signalboard brings events together into dashboards, funnels and cohorts, and answers plain-English questions with the query shown.
Built for: SaaS and app teams, product managers, growth teams and founders.
- Dashboards for activation, engagement and revenue
- Funnels with step conversion and breakdowns
- Cohort retention heatmaps
- Experiments and feature impact
- Plain-English questions with visible SQL
- Multi-platform event tracking with privacy controls
Walkthrough
Answers, Not Just Charts
Every view is built to answer a product question and suggest the next step.
- 01
Product Health
Active users, activation, trial conversion, revenue retention and feature usage.
- 02
Funnels
Conversion by step, biggest drop-off and breakdown by channel.
- 03
Cohort Retention
Weekly retention heatmap by sign-up cohort.
- 04
Ask Your Data
Answers with charts, the SQL behind them and suggested next steps.
Every screen
The full experience.
What makes it different
Trustworthy AI Answers
The assistant writes SQL over a governed data model, shows the query and labels correlation as correlation.
Funnels
Step conversion and drop-offs.
Retention
Cohort heatmaps over time.
Experiments
Measure the impact of changes.
Ask Your Data
Plain-English questions, visible SQL.
How it’s built
The technology stack.
The architecture we would build this on today, and why each piece earns its place.
- Web app
Next.js (App Router), React, TypeScript, Tailwind CSS
Fast, accessible interfaces with server rendering where it helps
- API
NestJS on Node.js · REST + WebSockets
Typed modules, clear boundaries and live updates for busy screens
- Database
PostgreSQL with row-level security
Relational integrity for money and stock, with tenant isolation in the database itself
- Background jobs
Redis + BullMQ
Imports, emails, reports and integrations run reliably off the request path
- Event store
ClickHouse
Fast aggregation over billions of events
- AI assistant
LLM text-to-SQL over a semantic layer with validation
Answers constrained to governed metrics
- Infrastructure
AWS (ECS Fargate, RDS), Terraform, GitHub Actions
Reproducible environments and automated deploys from day one
- Observability
OpenTelemetry, Sentry, structured audit logs
Every error traced and every sensitive change attributable
More inside
Understand Your Product.
The analysis a product team runs every week.
Experiments
Variants, guardrail metrics and statistical results.
Data Sources
SDKs, warehouse sync and privacy controls.
What comes next
On the roadmap.
What a second release would add once the first one is in real users’ hands.
- 01Session replay with masking
- 02Revenue analytics from billing data
- 03Alerts on metric changes
- 04Warehouse-native mode
- 05Embedded customer dashboards
Concept project
Need Something Like This?
This is concept work: the product design, screens and architecture we would start from. If your business needs SaaS analytics or data products, we can scope a first release with you, usually within a week.
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