Custom SEO Dashboards

A dashboard your team will actually use.

The wrong dashboard tool is worse than no dashboard at all. A Power BI report at a company where no one has Power BI Desktop installed is a PDF that never opens. We start by understanding your team's technical environment, then recommend the tool that will get looked at every Monday morning. Looker Studio for most teams, Power BI where enterprise infrastructure demands it, Metabase where self-hosted data sovereignty matters, or a custom React dashboard where none of those fit.

Build Your Dashboard

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Dashboard platforms we build on

3wk

Typical Looker Studio delivery timeline

100%

Built on your BigQuery data, not tool exports

Blended data sources per dashboard average

Which Tool We Recommend

Four platforms, each for a different team profile.

Looker Studio (Google)

Free, fast to build, native BigQuery connector, and accessible to anyone with a Google account. The right choice for most marketing and SEO teams. Limitations: no complex calculated metrics, limited custom visualizations, and Google-controlled updates that occasionally break existing reports.

Best for: teams already in Google Workspace
Timeline: 2 to 3 weeks from BigQuery data to live dashboard
Native connectors: GA4, GSC, BigQuery, Google Sheets, Google Ads
Access control via Google Workspace roles

Power BI (Microsoft)

The enterprise standard for organizations that use Microsoft 365. More powerful calculated metrics and custom visualizations than Looker Studio. Requires Power BI Desktop for report editing and a Power BI Pro license ($10/user/month) for sharing. Right choice where IT already runs the Microsoft stack.

Best for: enterprises with Microsoft 365 and IT-managed BI
DAX calculated metrics for complex SEO KPI definitions
Direct Query to BigQuery for real-time data
Embedded dashboard option in SharePoint or Teams

Metabase (Self-Hosted)

Open-source BI tool that runs on your infrastructure. No per-user licensing cost at scale. Right for teams that have engineering resources, care about data sovereignty, or need to embed analytics inside their own product. Connects directly to BigQuery or PostgreSQL.

Best for: engineering-led teams or product-embedded analytics
Self-hosted on AWS, GCP, or your VPS (we configure this)
SQL-based questions or GUI question builder for non-technical users
Public embed links for client-facing dashboards without login

Custom React Dashboard (Supabase)

For teams that need full control over the visual design, the data model, or the user experience. We build custom dashboard applications using React and Supabase with direct BigQuery data pulls through a serverless API layer.

Best for: agencies building client-facing white-label dashboards
Fully custom design matching your brand system
Real-time updates via Supabase realtime subscriptions
User authentication and role-based data access control

Blended Multi-Source Dashboards

Every dashboard we build blends multiple data sources. GSC impressions and clicks, GA4 sessions and conversions, Ahrefs share-of-voice, CRM pipeline, paid media spend. The power is in the joins. a dashboard that only shows one data source is a glorified export.

Up to 8 data sources blended in a single BigQuery dataset
Custom calculated metrics: organic pipeline rate, SOV index, keyword velocity
Unified date dimension across all sources
Source-of-truth documentation for every metric definition

Dashboard Maintenance and Evolution

Dashboards decay. Data sources change, business questions evolve, and new metrics become relevant. We offer monthly maintenance retainers that keep your dashboard current as your analytics needs change.

Monthly data source validation and schema drift correction
New metric additions as business questions evolve
Quarterly dashboard review with your reporting stakeholders
Performance optimization for slow queries or loading times

How We Build Dashboards

Four steps from scattered data to a dashboard your team checks every Monday.

Step 01

Understand your team and your questions

We start with two questions: who reads the dashboard (technical or non-technical, how many people, what decisions do they make with it) and what are the three most important questions the dashboard needs to answer. Most dashboard projects fail because they try to answer 30 questions instead of three. We scope ruthlessly and add additional views only after the core three are working correctly.

Step 02

Select the right tool for your environment

Based on your team profile, technical infrastructure, and access requirements, we recommend a specific tool with explicit reasoning. If you have a strong preference for a tool we have not recommended, we will explain the tradeoffs and build what you want. but we will not pretend the tradeoffs do not exist.

Step 03

Build on your BigQuery data layer

All dashboards connect to BigQuery as the source of truth. If you do not have BigQuery set up, we build the data layer first. The dashboard layer is a read interface on top of the data model; getting the data model right is the work that makes the dashboard trustworthy. We never build a dashboard that connects directly to raw API endpoints. that is how you get dashboards with sampling discrepancies and stale data.

Step 04

Deliver, document, and hand over

We deliver the dashboard with a written metric definition guide (so anyone reading it knows exactly what each number means and where it comes from), a walkthrough session for the primary audience, and documentation for whoever will maintain it. Ownership is yours from day one.

Custom Dashboards in Practice

Building a Looker Studio dashboard that replaced five weekly manual reports.

The Challenge

A digital marketing agency was producing five separate reports for each client: organic traffic, keyword rankings, technical health, backlink profile, and competitive share-of-voice. Each report took 90 minutes to compile and pulled from different tools with different data definitions. Clients were confused by inconsistencies across reports. The team spent 15 hours per week per client on reporting instead of strategy.

Our Solution

We built a unified BigQuery data model pulling from GSC, Ahrefs, GA4, and the agency's proprietary keyword tracking data. A single Looker Studio dashboard replaced all five reports: one tab per report type, all pulling from the same data source, all using consistent metric definitions. An automated weekly data refresh ran on Sunday night so the dashboard was current by Monday morning. Client access was managed via Google account sharing.

Results Achieved

Weekly hours saved per client on reporting

From 15 hours to 3 hours review time

Number of tools clients now need to check

Down from 5 separate reports

Client questions about data inconsistencies

Single source of truth eliminates discrepancies

12hr

Agency capacity freed for strategy work per client per week

Redirected from manual report production

FAQ

Custom dashboard questions

We use a four-factor decision matrix: technical environment (Google Workspace vs. Microsoft 365 vs. custom), audience technical level (can they run a SQL query or do they need a GUI), access and sharing requirements (internal only, client-facing, embedded in a product), and data freshness needs (daily batch is fine vs. near-real-time required). Most teams end up on Looker Studio because it is free, fast to build, and native in the Google ecosystem where most SEO data already lives. Enterprise Microsoft teams typically need Power BI. Teams with engineering resources who need embedded analytics or self-hosted data control go to Metabase or a custom build.

We prefer to build on BigQuery because it gives us a single source of truth and eliminates sampling discrepancies between tools. If you already have a BigQuery dataset with clean, documented data, we can build a dashboard directly on top of it. If you are starting from scratch, we set up the data layer first (typically two to three weeks) and then build the dashboard. Building dashboards directly on raw GA4 or GSC APIs without a data layer in between creates maintenance headaches and metric inconsistencies that always surface at the worst moment.

GA4 Explore reports are flexible but locked inside GA4. They can only use GA4 data, they are not shareable outside the GA4 property, and they have GA4's sampling limitations. Looker Studio connects to BigQuery where we have joined GA4 data with GSC, Ahrefs, CRM, and any other source. It produces a fixed-layout report that anyone with a link can view without a GA4 login. For reporting to stakeholders who do not have GA4 access, Looker Studio is always the right choice.

Yes. For agencies that want to deliver branded analytics dashboards to their clients, we build the dashboard template, configure client-specific data connections, and set up access management so each client sees only their own data. Looker Studio supports this via report copying and data source swapping. For more complex multi-tenant requirements, Metabase self-hosted or a custom React build gives more control over the access model and branding.

The most valuable custom metrics we build: organic pipeline rate (organic sessions to CRM lead conversion, not just form fill), share-of-voice index (your impressions as a percentage of total estimated impressions for your target keyword universe), keyword velocity (rate of position improvement per week weighted by revenue relevance), content decay score (pages where impressions are declining faster than traffic. indicating ranking loss before traffic drop), and incremental organic revenue (organic revenue minus what direct and branded search would have driven without SEO investment).

Ready to Build a Dashboard Worth Opening?

Tell us what questions it needs to answer.

We start by scoping the three core questions your dashboard must answer. Most teams are surprised how focused and fast the build goes once those three are clear.

Tool recommendation with explicit reasoning included
First dashboard delivered within 3 weeks (Looker Studio) or 6 weeks (custom)
Metric definitions documented so anyone can read it