Marketing Technology / Marketing ROI & Analytics
ROI Monitor Marketing Intelligence
Custom AI platform that transformed 15 years of proprietary marketing ROI expertise into a scalable system for attribution analysis and capital-allocation intelligence.
- 4 days → seconds
- Attribution analysis time
- ~50%
- Reported higher accuracy vs. correlation-based approaches
- 30%+
- Reported marketing budget savings across pilot use
The Challenge
ROI Monitor founder Pablo Turletti had developed a proprietary, causation-based methodology over 15 years for connecting marketing activity with business and financial outcomes. The methodology had been applied and taught extensively, but much of its value depended on expert knowledge, manual analysis, spreadsheets, and judgment. Attribution analysis could take up to four days, limiting how quickly the methodology could be applied across clients and larger volumes of marketing and financial data. The challenge was to turn that hard-won expertise into a scalable AI system without losing the business logic and rigor that made the methodology valuable.
What Cogya Built
Cogya designed and developed a custom AI marketing ROI and capital-allocation intelligence platform around Pablo Turletti’s methodology. The system translated the underlying decision logic into structured business rules and AI capabilities that could process marketing and financial data, perform attribution analysis, compare performance, calculate ROI, and support capital-allocation decisions. Rather than creating a generic analytics dashboard or chatbot, Cogya built a purpose-specific AI system around the methodology itself.
What Changed
Analysis that previously required days of expert work could be completed in seconds, allowing the methodology to operate at a much greater scale. ROI Monitor could bring fragmented marketing and financial information into one structured intelligence environment, helping users analyze marketing performance and support better capital-allocation decisions. Across pilot use, the client reported stronger analytical accuracy compared with correlation-based approaches and significant marketing budget savings.
The Business Challenge
ROI Monitor was built around 15 years of proprietary marketing ROI and capital-allocation expertise developed by founder Pablo Turletti.
The methodology connected marketing activity with real business and financial outcomes, but much of the analysis still depended on spreadsheets, manual work, and expert judgment.
Attribution analysis could take up to four days, making it difficult to scale the methodology across more clients and larger datasets.
The challenge was to capture the reasoning behind the methodology and turn it into a faster, repeatable AI system.
What Cogya Built
Cogya mapped the methodology, decision logic, and expert judgment behind ROI Monitor and translated them into a custom AI marketing ROI and capital-allocation platform.
The system connects:
Marketing Data → Financial Data → Business Logic → AI Analysis → ROI Intelligence → Capital-Allocation Decisions
Rather than adding a generic AI interface, Cogya built the system around the methodology itself so its logic could be applied consistently at scale.
Turning Expertise Into Structured Intelligence
Cogya identified the information, decision rules, comparisons, and expert judgment that shaped the methodology.
That reasoning was converted into structured business logic the AI system could use, preserving the core methodology while significantly reducing manual analysis.
AI-Powered Marketing ROI Analysis
The platform brings marketing and financial information into one intelligence layer that can:
Structure fragmented data Apply the methodology's business logic Compare marketing performance Calculate ROI and attribution Support capital-allocation decisions
This transformed a largely manual expert process into a repeatable AI-enabled system.
What Changed
Attribution analysis that previously required approximately:
4 days → seconds
The client also reported:
~50% higher analytical accuracy compared with correlation-based approaches
30%+ marketing budget savings across pilot use
The biggest change was not only speed. The methodology could now be applied across more data and more decisions without relying on the same level of manual expert analysis.
Business Impact
ROI Monitor transformed proprietary expertise into a scalable digital system.
The platform helped:
analyze marketing and financial data faster apply the methodology consistently reduce manual expert analysis generate structured ROI intelligence support better capital-allocation decisions scale proprietary knowledge beyond the availability of its creator
The project shows how artificial intelligence can help businesses structure, preserve, and scale valuable expertise.
How the System Works
01 — Collect Marketing and financial data enters the platform.
02 — Structure Information is organized for consistent analysis.
03 — Apply Business Logic The system applies the proprietary ROI methodology.
04 — Analyze AI evaluates performance, relationships, and attribution.
05 — Generate Intelligence ROI and capital-allocation insights are produced.
06 — Support Decisions Business users use the intelligence to guide investment decisions.
Human users remain responsible for final decisions.
Key AI Capabilities
Marketing ROI Intelligence Connects marketing activity with business and financial outcomes.
Attribution Analysis Evaluates how marketing activity contributes to performance.
Capital-Allocation Intelligence Supports decisions about where marketing investment should be allocated.
Structured Business Logic Turns proprietary methodology into repeatable system logic.
Marketing & Financial Data Integration Combines multiple data sources in one analytical environment.
Decision Support Transforms complex analysis into actionable business intelligence.
The Cogya Approach
Cogya did not start with the AI model. It started with the expertise.
The team mapped how the methodology worked, how decisions were made, and which relationships mattered before designing the AI system around that logic.
The result was not a generic AI tool, but a purpose-built intelligence system based on proprietary business expertise.
That same approach can apply to organizations with valuable methodologies, pricing models, diagnostic processes, frameworks, or decision systems that still depend heavily on a small number of experienced people.
Next step
Let's map your #1 bottleneck.
Bring us one operational problem that is taking too much time, creating too much manual work or limiting your business. We'll help structure the problem and determine whether a custom AI system could create meaningful value.
30-minute working session with a Cogya co-founder.