BI & Analytics Studio

Your First Real
Data Function.

Senior-level analytics architecture, implementation, and ongoing support — without building an internal team before you're ready for one.

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Live in 4–8 weeks Fraction of team cost Production-ready output
Growth Overview — Q4 2024 Live
Monthly Revenue €124,800 ↑ 18%
Active Users 8,342 ↑ 12%
CAC €38.20 ↓ 9%
Churn Rate 2.1% ↑ 0.3%
Revenue by Channel
Organic Paid Referral
AugSepOctNovDec
Funnel
Visitors
24.1k
Signups
14.9k
Activated
9.2k
Converted
4.3k

The Smarter Approach

A Smarter Way to Build Your Data Function

Most growing companies don't need a full internal data team on day one. What they need is clear architecture, reliable infrastructure, and reporting that supports real decisions.

Hiring a full analytics team early is expensive and slow. Recruiting alone can take months, and the foundations still need to be designed before meaningful reporting exists.

There is a simpler path: build the system first.

An experienced partner can design the data architecture, implement the warehouse, establish tracking, and deliver reporting across product, marketing, and leadership. Once the foundation is in place, an internal team can grow on top of it when the company is ready.

Modern tooling, automation, and AI-assisted workflows have dramatically improved the speed of delivery. Much of the repetitive engineering work is compressed, while the strategic decisions remain human.

The result: a functioning data system within weeks instead of years.

The traditional path

Hire a senior data or analytics lead early. €120k–€160k annual cost including overhead. Months spent recruiting before the work even begins. Once hired, that person still needs time to design the architecture, implement infrastructure, and build the first reporting systems.

The structured alternative

Work with an experienced partner who designs the architecture, builds the infrastructure, and establishes reporting from the start — while staying embedded as the company grows. Operational within weeks instead of months.

✓ Typically 30–50% less cost than hiring a senior full-time role at the early stage
✓ Continuous support as new questions, tools, and reporting needs emerge
✓ When an internal data lead is eventually hired, the foundation already exists — infrastructure, pipelines, dashboards, and a clear metrics framework

Process

How We Work

Three structured phases — from blank slate to a living data infrastructure that grows with the business.

1

Design

We define tracking plan, data architecture, and core metrics before a single line of code is written. Every metric is documented and agreed upon. No surprises downstream.

1 – 3 weeks
2

Build

We implement the data warehouse, pipelines, and transformation models in a clean, tested, and documented way. Production-ready from day one — not a prototype.

3 – 6 weeks
3

Evolve

As the business grows, the analytics setup is maintained, extended, and adapted. New data sources, new metrics, new questions — handled without rearchitecting from scratch.

Ongoing

Packages

Scoped for Where You Are

Three engagement models designed to build a complete data foundation - from architecture to reporting

Marketing Intelligence

Focused performance visibility.

A structured data warehouse centralizes marketing platforms into one source of truth. Standardized metrics, attribution logic, and automated reporting provide clear visibility into acquisition performance, spend efficiency, and channel effectiveness.

Setup €4k – €7k
Monthly €300 – €400
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Most Popular

Growth Analytics

Connected growth visibility.

Marketing platforms, product tracking, and spend data are integrated into unified models that map the full customer journey. Funnel analysis reveals exactly how users move from acquisition through to retention, and where conversion gaps appear.

Setup €8k – €12k
Monthly €600 – €800
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Full BI Platform

Company-wide decision infrastructure.

A broader data architecture combining advanced modeling, metric governance, and executive reporting into one scalable decision framework. Built for companies where data is becoming a cross-functional dependency, not just a marketing tool.

Scope Defined after system review
Pricing is scoped individually based on existing infrastructure, integration complexity, and reporting requirements.
Discuss Scope

Built for Continuity

After implementation, the studio remains responsible for monitoring, maintaining, and evolving the data infrastructure as systems grow and change. This embedded BI model gives you dedicated data ownership at a fraction of the cost of building an internal team — with the continuity of someone who knows every corner of the setup.

Book a Free Consultation Scope and pricing defined together — no commitment required.

Client Feedback

What Clients Say

★★★★★

"Ghiath supported us as an external freelance BI partner, building tailored Looker dashboards for performance channels across multiple EU markets. He proactively improved our data setup, fixed GA4 and tracking issues, and consistently recommended effective solutions. Beyond his technical expertise, he was highly collaborative, empathetic, and easy to work with. I would gladly recommend him to any team looking for a proactive and skilled BI expert."

Neonail
Sachin Mathew Performance Marketing Manager, Neonail
★★★★★

"The tracking strategy work alone was worth the engagement. We had always treated tracking as a developer task. Seeing it approached as a business logic problem changed how our whole team thinks about data. The dashboard we got at the end is something we actually use every day."

Company logo
Placeholder Name Head of Growth, [Company Name]
★★★★★

"We hired three analytics contractors before this and got prototypes none of us could maintain. This was different from the first conversation — opinionated, structured, and built to last. Six months later, everything is still running exactly as designed."

Placeholder Name CTO, [Company Name]
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Free Consultation

Discuss Your Analytics Initiative.

A focused conversation to understand the scope and identify the right path forward.

High-level evaluation of scope, complexity, and expected investment
Advisory input on data architecture, tracking strategy, and technology stack
Perspective from comparable implementations and scaling environments

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