Data Engineering

Data engineering that makes your marketing data accurate, automated, and useful

Data engineering graphic showing data sources flowing through ThriveStack into a report, with ROAS, MQL and CPC metrics
Automated pipelines that clean and centralize every marketing data source, so your numbers are accurate and fresh every day.
Data engineering graphic showing data sources flowing through ThriveStack into a report, with ROAS, MQL and CPC metrics
We help companies build sustainable growth programs, powered by the right platforms and tools.

Where data engineering can go wrong

Thinking you're tracking something when you're not. Broken pixels, misfiring conversion events, and cross-platform discrepancies are common. Nobody notices until a major budget decision has already been made on numbers that were never reliable.

Data lives in silos. Ad platforms, CRMs, and analytics tools each produce their own numbers with no way to reconcile them automatically. Doing it manually every week is slow, error-prone, and pulls analysts away from work that actually drives decisions.

Two or three weeks of missing tracking data makes every week-over-week comparison useless and every decision that followed suspect. Most teams find out when the numbers stop making sense, at which point the damage has already compounded.

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Our approach to data engineering

Every program runs on a single integrated system where measurement informs creative, creative informs media, and media decisions are validated by data. The result is a cycle of learning that compounds over time, not a set of disconnected tactics that reset every quarter.

Centralized data

ThriveStack, Thrive's proprietary ETL platform, pulls data from every marketing source, transforms it into a consistent format, and loads it into a centralized data warehouse that is automated, fresh every day, and built with accuracy.

Automated QA

Automated QA and alerting catches broken pixels, misfiring conversion events, and tracking anomalies in hours rather than weeks, before bad data drives a major budget decision. Authentication and access management are handled at the infrastructure level so data stays secure.

Optimization

CRM data is blended with performance data so optimization decisions get made against real business outcomes. Dashboarding connects directly to the warehouse so clients can use Looker Studio, Tableau, Power BI, or any existing reporting tool without being locked into a proprietary environment.
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How we've helped brands like yours

From proving which channels really drive sales to creative that beats in-house ads, here's what we delivered.

Thrive empowers companies big and small to build sustainable growth programs.

uber
tempurpedic
masterclass
square
asana

“Thrive worked hand-in-hand with our in-house team to craft a bold strategic vision for our digital marketing program, and then ensured that every detail and dollar was accounted for in our campaigns. Asana's acquisition program is more effective thanks to our partnership and co-creation with Thrive.”

smith

“Thrive has been a key partner for helping Smith transform from a traditional wholesale business to a digitally minded consumer-first brand. Helping us acquire new customers for all our channels. They move fast and are extremely proactive”

snapchat
classpass
earnest

“The team at Thrive Digital is great to work with. They are diligent, strategic and deeply focused on the details. Thrive is a rare breed among digital marketing agencies.”

arcteryx
lululemon
coinbase
gofundme
Every optimization decision, attribution model, and strategic recommendation is only as good as the data it's built on. Broken tracking, siloed data sources, and manual reconciliation are where errors compound into real consequences. Data engineering fixes the foundation so everything built on top of it is reliable.
Explore measurement
ETL stands for Extract, Transform, Load. An ETL tool pulls data from multiple sources, transforms it into a consistent format, and loads it into a centralized database. Without one, data lives in silos and reconciliation happens manually, which is slow, error-prone, and gets harder as the number of sources grows.
Explore marketing mix modeling
Through a systematic audit: pixel firing verification across all pages and events, conversion event testing, UTM consistency across all campaigns, and cross-platform reconciliation against GA4 and CRM data. Thrive runs this at the start of every engagement and monitors it continuously with automated alerts for anomalies.
Explore analytics and attribution
A data warehouse is a centralized database that stores marketing data from every source in a structured, queryable format. It's populated by an ETL pipeline that pulls from ad platforms, CRMs, and analytics tools, reconciles discrepancies, and makes everything accessible to reporting tools and analysts. Thrive builds on Google BigQuery using ThriveStack.
Explore analytics and attribution
Each client's data is kept entirely separate and never shared across accounts or used beyond that client's program. Role-based access controls ensure the right internal teams see the right data, all managed at the infrastructure level.
Explore measurement
Looker Studio is the default. It connects directly to BigQuery and produces clean, automated dashboards. If a client has existing infrastructure in Tableau, Power BI, or another tool, the data warehouse connects to those instead. Clients are never locked into a proprietary reporting environment.
Explore analytics and attribution