Tinuiti builds a scalable data lake for AI-driven marketing

“Fivetran has completely transformed our data operations. What used to take 2-4 weeks now takes minutes. It’s enabled our teams to focus and deliver on high-value work, like our new data lake that powers AI-driven insights for our clients.”
— Lakshmi Ramesh, VP of Data Services at Tinuiti

Tinuiti, the largest independent full-funnel performance marketing agency in the U.S., manages nearly $4 billion in media spend for its clients across every major digital marketing channel. Its innovative measurement product, Bliss Point by Tinuiti, provides clarity around the impact of every dollar spent. The product’s success comes from delivering highly accurate, real-time marketing insights thanks to advanced data science like causal inference and machine learning (ML).

As a leader in data-driven marketing, Tinuiti sought a modern data foundation to scale its analytics capabilities. The challenge fell to Lakshmi Ramesh, VP of Data Services at Tinuiti, whose team manages client reporting, business intelligence, and data operations. Prior to adopting Fivetran to build a modern data lake architecture, the company’s previous data architecture was riddled with manual processes that slowed customer onboarding and created performance bottlenecks.

Getting to a scalable system meant building a centralized, interoperable data lake — one that could ingest data automatically, scale across global campaigns, and enable real-time insights.

Building a scalable data foundation for modern marketing

Tinuiti faced a massive data challenge with their managed data warehouse: fragmented platforms, inconsistent schemas, and costly inefficiencies. Every source came with different schemas, formats, and API update cycles, creating several major challenges:

• Limited control over data: Tinuiti’s data warehouse didn’t provide full access, limiting flexibility and scalability.
• High operational overhead: Engineers spent up to 150 hours per month maintaining API connectors, rather than focusing on analytics.
• Amazon Redshift performance bottlenecks: As data volumes increased, query performance and scalability suffered.

Additionally, manually managing in-house data pipelines and constant schema changes was proving unsustainable. It took up to 6 weeks to onboard new customers during a critical period of relationship-building. Ramesh needed to quickly and reliably centralize customer marketing data to improve customer campaign performance and build client trust early on. 

She chose Fivetran for its library of 700+ connectors to seamlessly integrate data from 100+ different marketing platforms and data sources into Amazon S3. In addition to gaining full control and flexibility by moving away from their data warehouse, Ramesh’s team reduced onboarding time for new data sources to under an hour using the Fivetran API for programmatic setup. 

The move established a universal storage layer, allowing Tinuiti to store all raw and processed data in a single, scalable environment. With this architecture, teams can query data directly from Amazon S3, send structured data to a warehouse, or feed ML models without duplicating datasets. The results include faster insights, reduced compute and storage costs, granular access controls, and the ability to serve a wider customer base.

Previously with the old architecture, Ramesh could only serve 20% of Tinuiti’s customers, but on the Amazon S3 data lake architecture, she serves the entire customer base with a single, scalable, and centralized platform. Thanks to Fivetran, the migration also put an end to manual reporting and tedious monthly maintenance of DIY pipelines.

“Fivetran has completely transformed our time to value. I can fill in 2 fields in Fivetran’s setup form and onboard a client on up to 80 platforms. What used to take 2-4 weeks now takes less than an hour because Fivetran is so self-service and easy. In just a few minutes, we’re delivering insights on millions of data points.”
— Lakshmi Ramesh, VP of Data Services at Tinuiti

From manual pipelines to AI-ready data 

Fivetran’s Managed Data Lake Service brought new value to Tinuiti’s data operations, replacing fragmented, manually maintained pipelines with fully automated data integration. Unlike traditional warehouses that require structured data up front, the data lake ingests structured, semi-structured, and unstructured data for greater flexibility and scale.

Fivetran’s automated data ingestion provided on-the-fly conversion into an open table format, allowing teams to run exploratory analytics, build predictive models, and power AI/ML workflows on query-ready data. Analysts and data scientists query full-fidelity data in Amazon S3 before moving only what’s needed to the warehouse, reducing storage and compute costs.

To further streamline performance, Tinuiti uses Fivetran to automatically convert data into Apache Iceberg format for compliant querying, eliminating the need for manual format conversions. With Fivetran automatically populating the AWS Glue catalog, Tinuiti strengthened data governance and security while scaling back operational overhead.

“Fivetran’s Managed Data Lake Service gives us the flexibility to direct data anywhere we want and consume it any way we want. We can choose what to bring into the warehouse or send elsewhere, which has reduced our costs, increased security, and improved our data governance.”
— Lakshmi Ramesh, VP of Data Services at Tinuiti

Improving marketing with real-time insights and automation

With Fivetran, Tinuiti has eliminated at least 80% of manual pipeline maintenance and configuration work. This allows the data services team to direct more focus on analytics, ML, and data science. Tinuiti is pursuing AI and large language models (LLMs) to improve operational efficiency and perform deeper analysis on how media is performing across channels. With real-time data access, the agency can now predict campaign performance, optimize ad spend, and personalize marketing strategies.

Fivetran has drastically reduced engineering overhead, freeing the team to build advanced predictive analytics and forecasting tools on top of the marketing media mix. Tinuiti is also expanding to a global customer base and running international campaigns, with Fivetran ensuring data is delivered with the right country and currency labels — something the agency wasn't able to easily accomplish 2 years ago.

Most importantly, the data Tinuiti is providing to customers is more trustworthy, accurate, and reliable than ever. Bliss Point by Tinuiti can now proactively inform customers when there are data delays or issues, thanks largely to the visibility provided by Fivetran.

“Fivetran has provided a rock-solid data foundation, so now we can open the floodgates with data. Without Fivetran, we’d need a huge data ingestion team whose sole job is building and maintaining API connectors.”
— Lakshmi Ramesh, VP of Data Services at Tinuiti

Powering timely insights at Tinuiti

A newly centralized data foundation has led to breakthroughs in accurate, reliable data. It’s paving the way for more advanced analytics and AI-driven insights backed by standardized, taxonomized, and readily accessible data from across the organization, without being tied to a single system or platform.

A new marketing mix model (MMM) enables brands and marketers to strategically allocate budgets across channels based on timely performance data. At the same time, AI and ML-powered analytics provide forecasting capabilities, helping brands predict future campaign performance and ROI with greater accuracy.

Fivetran has unlocked new opportunities for Tinuiti’s global expansion, allowing the company to scale operations internationally and support a growing, diverse client base. What was impossible just 2 years ago — centralizing data across hundreds of platforms and seamlessly integrating global marketing insights — is now the foundation for what comes next.

“Before Fivetran, it was a time-consuming and operationally-heavy process to ingest data and we had no control over the quality or reliability of it. With Fivetran, we’re able to get to market quicker and I can see a future where we’re easily sharing powerful data directly from our data lake to clients.”
— Lakshmi Ramesh, VP of Data Services at Tinuiti

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