Insighta Partner with Rittman Analytics to Build the Foundations of their Multi-Tenant Marketing Analytics Application

The Download

Insighta is a cutting-edge technology company focused on empowering businesses with comprehensive and precise marketing attribution insights. Their flagship application provides marketers with a unified view of attribution data, allowing them to track, analyse, and optimise their campaigns effectively.

Insighta aims to solve a prevalent issue in marketing analytics—the fragmentation and inconsistencies caused by siloed data from multiple platforms like Facebook, Google, and Pinterest. By consolidating and standardising this data, Insighta enables marketers to make more informed, data-driven decisions.

Founded by a team of experienced marketing and data professionals, Insighta combines deep domain expertise with advanced technologies such as predictive analytics, machine learning, and dynamic comparison models.

Their core product allows users to apply attribution models such as linear touch, time decay and first action or even use Insighta's proprietary approaches, all in a plug-and-play fashion. The product's user-centric design and rapid deployment capability have made it leader in the competitive marketing attribution technology landscape.

The Challenge

Insighta faced several hurdles while building the core functionality of their marketing attribution application. The primary challenge lay in designing a scalable multi-tenancy architecture that could support multiple clients with differing data sources and requirements. Traditional approaches to multi-tenancy lacked the flexibility and efficiency Insighta needed, especially given the diverse formats and structures of their clients' data.

Additionally, Insighta needed to ensure that their application could seamlessly integrate with a variety of marketing platforms and data sources. Achieving standardisation across disparate datasets, while maintaining accuracy and flexibility, was a complex undertaking. They also sought to incorporate predictive analytics and machine learning to provide actionable insights into future customer behaviours and campaign performance.

Compounding these technical challenges was the need for rapid deployment. Insighta required a solution that not only solved these foundational issues but also allowed for the quick onboarding of new clients without disrupting ongoing operations.

The Solution

Rittman Analytics worked closely with Insighta to deliver a comprehensive solution addressing their technical and operational challenges. The project began with the design and implementation of a scalable, mono-repo architecture to support multi-tenancy. Using advanced techniques such as factory patterns and dynamic runtime variable injection, the team created a system that allowed for efficient configuration management and ensured that each client's data was handled uniquely while adhering to a common structure.

Key components of the solution included:

• Multi-Tenancy with dbt and Dagster: The solution leveraged dbt for data transformations and Dagster for orchestration. A centralised mono-repo structure allowed for dynamic parsing and configuration based on client-specific parameters stored in Supabase.
• Customised Conforming Layers: Rittman Analytics designed a flexible conforming layer that standardised data ingestion while accommodating the unique requirements of each client. This ensured seamless integration of disparate data sources like Shopify, NetSuite, and custom marketing platforms.
• Predictive Analytics and Machine Learning: The solution integrated machine learning workflows to predict future customer values and campaign performance. These workflows were tightly coupled with dbt transformations to deliver actionable insights.
• Rapid Deployment and Automation: Automation was built into the solution, enabling faster onboarding of new clients and reducing manual overhead. Pull requests and automated testing processes ensured that updates could be deployed quickly without risking system stability.

Business Benefits Delivered

The collaboration between Insighta and Rittman Analytics resulted in a highly scalable and efficient marketing attribution application. The benefits to Insighta included:

• Enhanced Scalability: The multi-tenancy architecture enabled Insighta to onboard new clients quickly and efficiently, significantly reducing the time-to-market for their services.
• Operational Efficiency: Automation and standardisation streamlined data integration and transformation processes, freeing up Insighta's resources to focus on innovation and client engagement.
• Improved Accuracy and Insights: The robust conforming layer and machine learning workflows ensured that marketing data was accurate, consistent, and actionable. Insighta's clients could now trust their attribution models to make better decisions.
• Future-Proofed Architecture: The solution's modular and flexible design positions Insighta to easily incorporate new features and adapt to evolving client needs.
• Accelerated Growth: By addressing foundational challenges and enabling rapid deployment, Insighta was able to focus on scaling their business and expanding their market presence.