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./services --analytics

One Screen That Actually Answers What Leadership Asks

A custom analytics dashboard unifies revenue, traffic, and pipeline data from tools like Stripe, GA, and a CRM into one normalized KPI layer with scheduled reports, so leadership stops requesting one-off exports before every meeting.

Build time
3-5 weeks
Sources
Unified into one layer
Reports
Scheduled, not manual
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// built_for

Who this is actually for.

Founders and CEOs

You need one number for revenue, one for pipeline, one for retention, without pinging three different people the night before a board meeting.

Agency owners reporting on client performance

You report the same metrics to every client monthly. Right now that means rebuilding a deck from four dashboards instead of generating it.

Revenue and RevOps leads

Sales, marketing, and finance each define "revenue" slightly differently, and reconciling those definitions eats a day every month.

Marketing directors reporting upward

You can prove channel performance in GA, but tying that back to closed revenue in the CRM means a manual join nobody enjoys doing.

// status_quo

Where this usually breaks down.

Revenue lives in Stripe. Traffic lives in Google Analytics. Pipeline lives in a CRM. None of them talk to each other, so the monthly leadership update gets assembled by hand: export a CSV from each tool, paste it into a spreadsheet, build pivot tables, and hope the numbers reconcile. They often don't, because each tool defines basic terms like "customer," "active user," and "qualified lead" slightly differently.

This process usually takes a half day to a full day every month, performed by whoever drew the short straw, and it produces a static snapshot that's already stale by the time it reaches the board deck. If someone asks a follow-up question mid-meeting, such as "what did that look like last quarter," the honest answer is usually "let me pull that and get back to you."

Generic BI tools like Looker Studio can connect to some of these sources, but they still require someone to define what a KPI actually means across systems, and they rarely enforce role-based access cleanly enough to hand a client or an investor a scoped view without exposing everything else.

// what_gets_built

Five systems. One build.

01

Source unification + ETL

Data pulls automatically from wherever it already lives: Stripe for revenue, Google Analytics for traffic, a CRM for pipeline, and any other API-accessible tool, all into one warehouse,

On a schedule, without anyone manually exporting a CSV again. The ETL layer handles the translation work: different tools use different field names and different definitions for similar concepts, and that gets normalized once, centrally, instead of being re-interpreted by whoever happens to be building this month's report. Because this runs on a schedule rather than a manual trigger, the dashboard is never more than a few hours stale, which is the difference between a report that describes last month and a dashboard that describes right now. For a business running on four or five disconnected tools, this single step usually eliminates the majority of the manual reporting workload.

02

Normalized KPI layer

Every team gets the same definition of revenue, the same definition of an active customer, and the same definition of a qualified lead,

Calculated once and reused everywhere instead of redefined by whichever spreadsheet built it. This is the layer that ends the recurring argument between sales, marketing, and finance about whose number is correct: because after this is built, there's exactly one number, derived from one calculation, and every dashboard and export pulls from it. It also means historical comparisons hold up: if a KPI definition changes, it changes once at the source, and every past report using it can be recalculated consistently instead of leaving old reports built on a now-outdated definition in place. For a growing company, this KPI layer becomes the foundation every future dashboard, export, or automated alert gets built on top of.

03

Executive dashboard

One screen, ordered around the handful of numbers leadership actually asks about every month (revenue, growth rate, pipeline coverage,

Retention) instead of a generic BI template with forty widgets nobody opens. Role-based views mean an agency can hand a client a scoped dashboard showing only their own metrics, while internal leadership sees the full picture, all from the same underlying system rather than maintaining two separate tools. Because the dashboard pulls from the normalized KPI layer, drilling into any number, say going from "revenue" down to "revenue by channel," stays consistent instead of requiring a jump into a different tool with a different definition. This is the artifact that actually gets opened in a board meeting instead of a static slide deck that's already out of date.

04

Scheduled jobs + alerts

Reports generate and land in an inbox or a shared channel on a schedule (weekly, monthly, whatever the business rhythm requires) without anyone remembering to run them manually.

Alerts go further: a threshold breach, like churn crossing a defined limit or pipeline dropping below a target, triggers a notification the moment it happens instead of surfacing three weeks later during the next scheduled review. This shifts reporting from a reactive monthly ritual to a proactive early-warning system, where the people who need to know about a problem find out when it's still small enough to address. For a founder or RevOps lead managing multiple priorities, this is what actually reduces the mental overhead of "did anyone check the numbers this week," because the system checks continuously and only interrupts when something needs attention.

05

Export + share

Any view can be exported as a clean PDF or shared as a scoped link, so board decks, investor updates, and client reports stop being assembled by hand from four different dashboards.

A shared link can be locked to a specific date range and a specific set of metrics, which means an agency can send a client exactly their numbers without granting access to the underlying system or to other clients' data. Exports pull live from the same normalized KPI layer as the dashboard itself, so there's no risk of a stale number making it into a board deck because someone forgot to refresh before exporting. For businesses that report the same structure of information repeatedly (monthly investor updates, recurring client reports) this turns a half-day assembly task into a scheduled export that just arrives.

// what_it_replaces

Instead of duct tape, one system.

Instead of this

Manual CSV exports every month

You get this

Automated, scheduled ETL

Instead of this

Spreadsheet pivot tables

You get this

Normalized, reusable KPI layer

Instead of this

Ad hoc Slack screenshots

You get this

Scheduled reports and threshold alerts

Instead of this

Separate logins per stakeholder

You get this

One shared, role-scoped dashboard

// how_it_ships

Four steps. 3-5 weeks.

01

Discover

A scoping call maps the real workflow before anything gets designed.

02

Define

Written scope, milestones, and a fixed timeline you can plan around.

03

Ship

Weekly demos, weekly deploys, so you see progress every Friday.

04

Hand off

Docs, a walkthrough, and 30 days of post-launch support included.

[ proof ]Unified KPI layer | ModelFounders & revenue leaders | Audience3-5 weeks | Timeline
Data modelingETLInformation design

// faq --this-service

Answers, up front.

Which tools can this pull data from?

Any source with an accessible API can be connected, which commonly includes Stripe, Google Analytics, HubSpot, Salesforce, and internal databases. Sources are unified into one warehouse rather than left as separate connected tabs.

How is this different from a generic BI tool like Looker Studio?

A generic BI tool connects to sources but still requires someone to define KPIs consistently across them. This ships with a normalized KPI layer built for the business's own definitions, plus role-based access and scheduled delivery designed around leadership's actual reporting rhythm.

Can different stakeholders see different scoped views?

Yes. Role-based access means an agency can hand a client a dashboard showing only their own metrics, while internal leadership sees the full picture, all built on the same underlying system.

What happens if a source tool changes its API?

The ETL layer is built to isolate source-specific logic, so a change to one integration is handled at that connection point without requiring a rebuild of the KPI layer or the dashboard itself.

Can this dashboard be white-labeled for agency clients?

Yes. Agencies commonly use a scoped, branded version of the dashboard as a client-facing reporting deliverable, generated from the same data pipeline used for internal leadership reporting.

// related

More ways we build.

Every engagement is scoped to the business, not a template. See completed case studies across other industries, or browse the other service lines below.

Tell us what's slowing you down. We'll tell you what to build.

Two minutes, eight questions, one tailored recommendation, or send a fit check for analytics dashboard directly.

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