Monetizing insight in an enterprise SaaS company

Client Background

Universum is a global leader in employer branding insights, dedicated to providing businesses with valuable data-driven recommendations that help them attract and retain top talent.

Data is at the heart of Universum's mission. The company operates by collecting, processing, and delivering insights from vast survey data.

As Prakash Rajagopalan, the Head of Technology at Universum, explained, "We provide game-changing recommendations to our clients based on our data.

Challenges

The Universum project was unique since it involved modeling market research data. Data veterans of the industry can attest to the challenges involved in using a questionnaire with more than 100 questions generating even more KPIs used and combined in different ways. Modern data technologies provide opportunities to model and process the data in more effective, scalable and efficient ways.

Before partnering with 205 Data Lab, Universum recognized the need for enhancements to its data infrastructure to support the growing complexity of its business. Here are some of the ways this underlying data modeling challenge manifested itself before working with 205 Data Lab:

We work with highly intricate survey data, where each country introduces unique elements, and building a scalable system capable of managing this diversity presented a significant challenge," noted Prakash.
The existing platform required a high level of manual intervention and operational effort, which limited its efficiency. "The data platform was operationally intensive and required considerable manual processing.
Initial attempts to build an internal data warehouse using Postgres and AWS fell short due to data complexity and scalability needs.

Solution

205 Data Lab began with a comprehensive assessment of Universum's existing data architecture and its alignment with their business goals. Through stakeholder interviews across various departments, they gained a deep understanding of both technical and operational challenges.

Additionally, 205 Data Lab developed a flexible data model that allowed for processing survey data in a way that allowed modifications of the previous years to address newer KPIs introduced, while maintaining older periods reports 100% accurately.

The team then proposed a flexible roadmap that emphasized iterative prototyping and collaboration, implementing a modern data stack including:

Snowflake for scalable data warehousing
dbt for streamlined data transformations
Cube for seamless API creation
Tableau for self-service BI capabilities

The phased implementation enabled Universum to transition legacy systems to a modern, scalable platform without disrupting ongoing operations.

Results

Significantly reduced time to insight, generating reports in minutes instead of hours
The new infrastructure allowed Universum to start working with the data before the field period is completed, giving the insight teams a head start on their analysis
Improved cross-team collaboration, with more engineers, analysts, and cross-functional teams now able to access and work with the data
Enhanced capabilities for real-time insights and innovation
Positioned for AI implementation and digital transformation initiatives planned for 2025 and 2026

The new data infrastructure powered by technologies like Snowflake and DBT has made our data more robust, scalable, and flexible. This has been a game-changer for our ability to innovate and deliver better insights to our clients.

— Prakash, Head of Technology, Universum

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Impact

The biggest impact has been on our internal report production. We used to spend a lot of time creating PowerPoint reports with an operationally intensive process. Now, with Tableau integrated into the system, we can automate much of that work," shared Prakash.

The new infrastructure has also paved the way for product innovation. "We are looking into connecting live data to our BI platform and providing real-time insights. This is something we couldn't even consider before," Prakash said.