Data-driven Analytics PaaS
Marketing Research Company
In progress
Project Challenges:
Fragmented Operational Infrastructure
The client’s core processes relied on multiple disconnected third-party services, leading to inefficiencies, frequent maintenance, and limited scalability.
Uncertain Technical and Financial Feasibility
There was no clear understanding of whether building a proprietary platform would be a viable, cost-efficient, or technically scalable alternative.
Integration with Existing Data Pipelines
Any new solution had to integrate smoothly with the client’s established data pipelines for analytics and business operations to ensure continuity and compatibility.
Our Solutions:
Modular PoC Platform
We developed a proof-of-concept platform based on Strapi’s headless architecture, providing a scalable and easily extensible foundation for future growth.
Machine Learning-Driven Insight Discovery
We applied Machine Learning algorithms to uncover hidden correlations in behavioral data, enabling more accurate performance analysis and revealing key optimization opportunities.
Data Science Integration
We leveraged Data Science methodologies to adapt insights from scientific research, deriving the golden behavioral formulae that informed smarter decision-making and enhanced platform logic.
Project Overview
The client’s operations relied heavily on several third-party tools, none of which they owned or controlled. This fragmented setup caused constant maintenance overhead, limited flexibility, and increased costs. To evaluate whether building a proprietary platform could solve these issues, we were brought in to consult on architecture, feasibility, and execution strategy.
Our proposal was to develop a proof of concept (PoC) – a minimal yet functional version of the potential in-house platform – delivered in just one month and with a minimal budget. Through multiple stakeholder interviews and technical workshops, we defined the essential requirements and integrations covering about 60% of the client’s business logic.
Outcome
The platform was built on Strapi, chosen for its headless, API-first architecture, ideal for modular, scalable infrastructure. The PoC included:
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A functional backend with an API layer.
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A custom builder for surveys and question types.
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A frontend with an advanced analytics layer for testing and visualizing survey structures.
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Integration with existing data pipelines for analytics.
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Machine Learning (ML) modules that identified behavioral correlations.
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Data Science processes that adapted insights from scientific research to find the golden behavioral formulae for improved decision-making and logic optimization.
What next?
After one month, the PoC was tested with internal and external stakeholders and fully validated. The client confirmed that developing an in-house infrastructure was not only feasible but also significantly more effective and sustainable. Following validation, the project advanced to the design and implementation of a full-scale production platform based on the tested concept.
