Product Dashboards
Feature usage, funnel, and retention views built for your product team.
Dashboard Development
We design and build the dashboard itself: the product, ops, or executive reporting interface your team opens to make decisions. This is different from instrumenting analytics events or packaging metrics for investors; here we build the charts, tables, and role-based views on top of data you already have.
1-3 Weeks
Typical Build Time
What We Build When We Say Dashboard
1
Dashboard Types We Build
- Product dashboards: feature usage, funnel drop-off, and retention cohorts surfaced for your product team
- Operations dashboards: order status, queue depth, and error rates for day-to-day monitoring
- Executive dashboards: revenue, growth, and health metrics rolled up for leadership review
- Customer-facing dashboards: usage reporting embedded directly inside your product for your own users
2
Data Layer
- Connecting to your existing database (Postgres, MySQL, Supabase) rather than duplicating data into a new store
- Materialized views or scheduled aggregation jobs for queries that would otherwise be slow against live tables
- Real-time updates via WebSockets or polling where the use case genuinely needs live data, not a monthly revenue chart
- Read replicas or query-layer isolation so dashboard traffic never competes with production application load
3
Role-Based Views and Access
- Row-level and column-level access control so a regional manager sees their region, not the whole company
- Separate views for exec, ops, and product roles built from the same underlying data model
- Shareable links with scoped, time-limited access for external stakeholders
- SSO integration where the dashboard needs to sit behind your existing auth
4
Visualization and UX
- Charting built with Recharts, D3, or a BI tool like Metabase or Grafana, chosen based on your team's technical comfort
- Drill-down from summary charts into the underlying rows without a page reload
- Alert thresholds that notify Slack or email when a metric crosses a defined line
- A performance budget so dashboards load and filter quickly even against large tables
5
Build vs. Buy
- Metabase or Grafana on top of your existing warehouse when the audience is internal and reporting needs are standard
- A custom-built UI when the dashboard is customer-facing, needs specific branding, or needs interactions a BI tool can't do
- A hybrid approach: a BI tool for internal ops, custom embedded views for anything customers see
- We help make this call before building anything, since it changes both cost and timeline
Dashboard Types and Capabilities
Built for the specific audience and data each dashboard serves
Ops Dashboards
Real-time monitoring for queues, fulfillment, and operational error rates.
Executive Dashboards
Revenue and growth metrics rolled up into a leadership-facing view.
Customer-Facing Reporting
Usage dashboards embedded directly inside your product for your own users.
Data Modeling
Aggregation queries and materialized views built for dashboard-speed reads.
Role-Based Access
Scoped views and permissions so each role sees only what's relevant to them.
Custom Visualization
Charts built with Recharts or D3 when a BI tool's defaults aren't enough.
Threshold Alerting
Slack or email alerts when a tracked metric crosses a defined line.
How We Approach Dashboard Builds
Built on your existing data
We query your production database or warehouse directly. There's no duplicate data store to keep in sync.
We tell you when a BI tool is the better answer
Metabase or Grafana is often faster and cheaper than a custom build for internal reporting. We recommend that when it fits, rather than defaulting to custom work.
Role-based from the start
Access control is designed into the data model, not bolted on as a UI-level filter a determined user could bypass.
Dashboard queries stay off your production path
We keep reporting queries away from your primary application database path so a heavy dashboard query never slows down your product.
How We Approach Dashboard Builds
Built on your existing data
We query your production database or warehouse directly. There's no duplicate data store to keep in sync.
We tell you when a BI tool is the better answer
Metabase or Grafana is often faster and cheaper than a custom build for internal reporting. We recommend that when it fits, rather than defaulting to custom work.
Role-based from the start
Access control is designed into the data model, not bolted on as a UI-level filter a determined user could bypass.
Dashboard queries stay off your production path
We keep reporting queries away from your primary application database path so a heavy dashboard query never slows down your product.
Dashboard Development FAQ
Analytics setup is instrumentation: adding event tracking, PostHog or Mixpanel, so user behavior gets captured in the first place. Dashboard development is what happens after that data exists: building the actual reporting interface your team looks at, whether that's product usage, ops metrics, or executive revenue tracking. Many clients need both, analytics setup first, then a dashboard built on what it captures.
It depends on the audience. Internal reporting for your own team is usually cheaper and faster in Metabase or Grafana connected to your existing database. Customer-facing dashboards, or anything needing interactions a BI tool doesn't support, usually need a custom build. We look at your actual use case before recommending either.
Yes, where it matters. Ops dashboards monitoring queue depth or error rates typically need real or near-real-time updates via WebSockets or short polling intervals. Executive dashboards showing monthly revenue don't need that; a scheduled refresh every few minutes or hours is cheaper and sufficient. We match the refresh strategy to what the metric actually requires.
Yes. Role-based views are standard: a regional manager sees their region, a support lead sees ticket queues, an executive sees company-wide rollups, all built from the same underlying data model with access control enforced at the query level, not just hidden in the UI.
We design the query layer specifically to avoid this, using materialized views, scheduled aggregation jobs, or a read replica depending on your database and traffic pattern. A dashboard query should never compete with your application's live traffic for the same database connections.
Investor and KPI Readiness is a fundraise-specific package: the exact metrics and documentation investors expect to see during due diligence, delivered in a two-week sprint timed to your raise. Dashboards is the general-purpose reporting interface, product, ops, executive, or customer-facing, built for ongoing use rather than a single fundraising event. An investor-facing view is one example of a dashboard we might build, not the whole of this service.
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