One dashboard, not five exported spreadsheets
Looker Studio dashboards that answer specific business questions, refreshed automatically.
What is Marketing Dashboards?
A marketing dashboard is a live reporting layer - typically built in Looker Studio and backed by a warehouse like BigQuery when native connectors are not enough - that pulls data automatically from ad platforms, analytics, and CRM systems into a single view built around specific business questions, rather than a static export that someone has to manually refresh and reassemble every reporting period.
A marketing dashboard is an automated reporting view, built around specific business questions, that pulls live data from your marketing and analytics platforms instead of requiring manual export and assembly.
Why this matters for the business
A dashboard nobody built for a specific question just becomes another tab nobody checks. The more common failure is not a missing dashboard but an over-built one - a wall of charts assembled because the data was available, not because anyone needed to answer a question with it. That version gets opened once and never again.
The real cost of not having this is usually invisible until someone adds it up - a recurring block of time each week or month spent manually exporting, reconciling, and pasting numbers from five different platforms into a spreadsheet, time that a properly scoped, automated dashboard eliminates entirely.
What makes this hard to get right
- Most dashboard requests start from "show me everything" instead of a specific decision the dashboard needs to support
- Data sources change - a platform renames a field or deprecates an API - and a dashboard can silently break or show stale numbers
- Different stakeholders genuinely need different levels of detail from the same underlying data
How we approach Marketing Dashboards
Question-First Design
- Starting from the specific decision or question the dashboard needs to answer
- Actively resisting "show everything" scope creep
Data Pipeline & Warehousing
- A BigQuery or SQL-backed data layer for anything beyond native connector limits
- Scheduled, automated refresh from every source platform
KPI Selection By Stakeholder
- Executive-level summary views versus practitioner-level detail views
- Consistent metric definitions used across every dashboard
Visualisation & Layout
- Chart types chosen for the specific comparison being made
- Layout that surfaces the answer, not just the underlying data
Maintenance & Source Monitoring
- Monitoring for broken connections or schema changes at the source
- Scheduled review as data sources or business questions evolve
Scope, area by area
| Area | What we deliver |
|---|---|
| Data Layer | A BigQuery or SQL pipeline pulling from source platforms on a schedule |
| Dashboard Build | Looker Studio dashboards scoped to specific stakeholder questions |
| Documentation | Metric definitions and a data source map for handover |
| Maintenance | Ongoing monitoring for broken connections and source schema changes |
How it actually runs
Question Discovery
We identify the specific decisions each dashboard needs to support before designing anything.
Data Source Mapping
Every required data source is identified and checked against native connector limitations.
Pipeline Build
Where needed, a BigQuery or SQL layer is built to handle joins or history native connectors cannot manage alone.
Dashboard Design
Layout and chart choices are built around the question at hand, not a generic template.
Review & Iteration
The dashboard is reviewed with stakeholders and refined based on what they actually use, not what was originally requested.
How this compares
| Question-Built Dashboard | Generic Template Dashboard |
|---|---|
| Built around a specific decision stakeholders need to make | Built around whatever metrics were easy to connect |
| Refreshes automatically from source | Requires manual export and assembly |
| Maintained as data sources change | Breaks silently when a platform changes its API |
A dashboard with fewer, well-chosen charts is usually used more than one with more of them.
Who needs this
Teams manually assembling reports from spreadsheet exports
If someone spends a recurring block of time each period exporting and pasting data, that time is what an automated dashboard replaces.
Businesses with data spread across many platforms
Ad platforms, GA4, and CRM data rarely line up natively - a warehouse layer is often needed to unify them into one view.
Where this applies
- A leadership team wants one view of blended paid, organic, and CRM pipeline data instead of five separate platform logins
- A team currently rebuilds the same report manually every month and wants it automated instead
- A business needs a client-facing reporting dashboard that refreshes without manual intervention
The dashboards that actually get used are almost always the ones with the fewest charts, not the most. A recurring request to add another chart is usually a sign the first version did not actually answer the question it was built for, and the fix is rethinking the question, not adding another visual.
Other services in this area
Set up properly, not just installed
GA4 implementation with the event structure and custom dimensions your business actually needs.
One place to manage every tag, cleanly
GTM implementation and container management so every tracking tag is documented, tested, and reliable.
Know which conversions actually count
Conversion tracking configured across ad platforms and analytics so spend decisions are based on real outcomes.
Credit assigned to what actually worked
Attribution modelling that reflects your actual sales cycle, not a default last-click assumption.
Consistent tagging is the whole point
UTM naming conventions and governance so campaign data stays clean and comparable over time.
A report that says what to do next
Regular reporting that includes analysis and recommendations, not just a wall of numbers.
Common questions
Looker Studio's native connectors are enough for many straightforward setups. BigQuery becomes necessary when you need to join data across sources, retain more history than a native connector allows, or run calculations native connectors cannot handle.
Refresh frequency depends on the data source - most platforms support daily or near-real-time refresh through Looker Studio's native or BigQuery-backed connections.
Yes - client-facing dashboards are a common use case, usually with a simplified view and access controls appropriate for an external audience.
That is why maintenance is part of the scope rather than an afterthought - broken connections are monitored for and fixed, rather than discovered by a stakeholder noticing stale numbers.
No - different platforms sometimes use different attribution windows or sampling logic than their own native reporting UI, which can produce small, explainable discrepancies even in a well-built dashboard. What we guarantee is that any discrepancy is understood and documented, not silently ignored.
Usually more than one - an executive summary view and a practitioner-level detail view serve different purposes and rarely work well as a single dashboard trying to do both jobs.
Tired of rebuilding the same report every month by hand?
Tell us the specific questions your team needs answered, and we will scope a dashboard around those, not around everything that happens to be available.
Ready to get started?
We usually reply within 24 hours.