Marketing and advertising have been rapidly evolving with the rise of social media, influencer marketing and artificial intelligence. As a result, there have also been two big shifts in the digital marketing industry. One is a greater focus on data privacy, including GDPR and CCPA. The other is an emphasis on data science and AI in digital marketing analytics. 

As a full-service performance marketing and advertising agency, Tinuiti services some of the biggest brands like Rite Aid, Nestle and Instacart. The agency’s modern approach to building its data stack has enabled the agency to successfully serve a diverse range of data consumers, including several channel teams, a cross-channel strategy team, the analytics team and its clients.

In this article, we dive into some of the topics discussed with Lakshmi Ramesh, Vice President of Data Services at Tinuiti, in the latest episode of the “Data Drip” podcast. 

Easy access to data is key to scaling data products

The challenge to unite data from so many marketing and advertising platforms, as well as client data and third-party sources, has always been present in the digital marketing space. “I remember sitting in conference rooms with seasoned marketers and being stupefied at the amount of data being crunched behind the scenes just to serve up an ad,” recalls Ramesh. 

With growing privacy regulations and the need to enable a personalized customer experience, the challenges have only gotten bigger. “We knew that if we were going to build data products at scale, we had to get our basics right,” says Ramesh. 

Ramesh adds: “We've been tackling problems like, how do we get quick and easy access to a new data source? How do we make our data pipelines, data preparation and transformation more efficient and quicker? How do we reduce the time to market for sourcing data from a data source and making that available to end users?”

In a world where data teams have never had to juggle as much as they do today, Ramesh has built a data foundation that enables Tinuniti to efficiently collect data from hundreds of marketing platforms and synthesize it to derive strong client outcomes. 

“Fivetran gives us the flexibility to enable self-service connectors, quick out-of-the-box plug-and-play connectors,” Ramesh adds, noting that Fivetran has helped to significantly reduce time to market when sourcing data and making the data available to end users.

With a greater emphasis on data science and AI in digital marketing analytics, Tinuiti is bringing data into a data lake to improve its predictive analytic capabilities – whether it’s forecasting or building products that enhance day-to-day workflows.

“The data space is constantly evolving. You want to constantly be reassessing and continuing to modernize your stack,” says Ramesh.

Listen to the full episode of the Data Drip podcast to hear more from Lakshmi Ramesh, Vice President of Data Services at Tinuiti.