 | Guest Nick Weldon Co-Founder, 5×5
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What does it actually take to build and scale a modern data platform? In this episode of SpringDB Data Exchange, we sit down with Nick Weldon, Co-Founder of 5×5, to break down how today’s leading platforms are powered by identity graphs, data enrichment, and intent data. Nick shares how 5×5 built a unique data co-op model where companies collaborate and exchange first-party and behavioral data to create a massive, unified data ecosystem without relying on traditional data vendors or expensive data licensing.
5×5 is a data co-op platform that enables companies to collaborate and exchange first-party and behavioral data to build a unified, large-scale data ecosystem. Rather than relying on traditional data vendors or expensive licensing agreements, 5×5 lets participants contribute and access a shared identity graph that connects B2B, consumer, device, and behavioral data. The result is a richer, more accurate data foundation for CRM enrichment, intent modeling, and product intelligence at petabyte scale.
How identity graphs connect B2B, consumer, device, and behavioral data into a single unified record, and why this foundation is critical for any modern data platform.
Why enrichment has become a baseline requirement for CRM, MarTech, and AdTech platforms, and how companies are using it to fill gaps in their first-party data.
A candid look at how intent data is collected and scored, why most solutions get it wrong, and what separates genuinely predictive intent from noise.
The real engineering and operational challenges that come with processing and maintaining data pipelines at petabyte scale, and how modern platforms are solving them.
How modern platforms unlock powerful insights by combining multiple data sources into a single identity graph, and what this means for product development and customer experience.
Product Leaders Building data-driven platforms and looking for a framework to think about data infrastructure and enrichment. | Founders Exploring data as a competitive advantage and considering co-op or collaborative data models. | |
Data Engineers and Architects Working with large-scale datasets and looking for real-world perspective on pipeline design and identity resolution. | Growth, RevOps and Marketing Teams Using enrichment and intent data to improve targeting, lead quality, and campaign performance. | |
Anyone Curious About Modern Data Ecosystems Wanting to understand how large-scale data platforms are actually built and operated behind the scenes. |
