Lob Innovation & Technology Culture

Everybody is knowledgeable and equipped to tackle digital channels today, but less equipped on how to send direct mail — or even if they can do direct mail. Our job is to integrate into customers’ existing systems, creating more trigger-based programmatic sends and relevance around their campaign goals. We can even help them acquire new customer lists with updated addresses and bring additional transparency into their native systems.

Our work is all about understanding who you’re speaking to, how they like being spoken to, and the medium in which they speak and communicate. I’m showing that direct mail can get even smarter, and you can spend less money than before to get more insights on your customers to send more relevant content.

What’s it like to work on the data and analytics team at Lob?

Here at Lob, we compare our data platform to a garden — an organic, evolving ecosystem that changes over time. We on the data team are the gardeners; we plant the seeds, water the sprouts and prune religiously. All our colleagues are invited to explore the garden and search for the most vibrant blooms.

Lob’s data team is small but mighty. With just four people on the team today, we’ve been able to transform the Lob data ecosystem. Although we all have our specialties, everyone gets the chance to become familiar with the entire pipeline.

On this team, we have a tri-fold responsibility: We faithfully replicate data from product engineering teams, surface data to our customers in the Lob UI and empower internal stakeholders via access to dashboards and the warehouse. Being between worlds gives us a unique perspective and a unique ability to translate their concerns.

What tools, systems or processes help your team deliver useful insights?

On the Lob data team, we follow the Extract > Transform > Load pattern and use a variety of tools from the modern data stack.

Extract: We ingest data from third-party sources like USPS and other logistics providers. We replicate data from internal application Postgres databases using CDC and AWS DMS. 

Load: All extracted data sources are deduped, reconciled and stored in Iceberg tables.

Transform: Using dbt Core and Prefect, we orchestrate incremental refreshes of core and domain-specific data models.

Ultimately, this data is surfaced to internal stakeholders via Omni, a BI tool that offers a conversational interface powered by the context of our curated semantic layer. Omni connects directly to dbt, so we’re able to maintain close alignment with our data lineage.

How does your team partner with stakeholders to turn data into action?

The data and analytics engineers on the core data team focus on building out clean, curated and performant core data models so that we can enable stakeholders across the entire company to discover domain-specific insights. We each develop a focus on one or two domains, which helps us answer specialized questions.

Data analysts, who sit directly within business teams, use this data to build dashboards, insights and predictive models for their teams. They can also contribute to the shared dbt project and build custom data models to power their own use cases.

All Lob employees — from the operations team to customer success to the C-suite — have access to Omni and our shared dashboards. We’ve all grown fond of our data agent, Lobbie, where we ask questions about everything from logistics bottlenecks to customer trends to financial projections. Empowering stakeholders to answer their own questions, no matter their technical background, is our top priority.