Big Data Insights or Big Headaches, It’s Your Choice

Navigating Big Data Challenges with Data Platforms

Big data can be a big headache if it’s improperly managed. One symptom: marketers cannot tell if their data set supports their desired outcomes. Put another way, mismanaged data never yields actionable insights. Marketers perceive that solving data management problems is costly, and many are discouraged from tapping valuable first-party data in a privacy-conscious manner. 

Thankfully, things are changing. 

A big data management platform can solve these issues, and it’s becoming a necessity due to two macro factors: first, the enactment of more stringent U.S. data privacy laws, and second, an uncertain economic landscape resulting in tighter ad spend budgets. With the rise of AI- and ML-based data platforms and technologies, the quest to maximize efficiencies and ROAS drives the adoption of big data platforms to solve big data problems in programmatic advertising.

From Data Lake to Data Platform

While data lakes offer a solution for marketers’ data infrastructure needs — given data lakes house structured and unstructured data — it can be difficult to manage the mass amount of data coming in, much less to make sense of all of it. This is increasingly true in today’s increasingly complex and fast-evolving media landscape.

Enter a data platform. 

Data platforms can replace data code-based queries found in data lakes with buttons and automation, making them much easier to operate. Marketers can also rest assured that these streamlined tools are backed by the granular data needed to power everyday programmatic media operations. 

That said, marketers need a data platform that offers clean room technologies of their choice to onboard third-party data sources, activate ad campaigns and measure their effectiveness. Data platforms that offer integrated clean room technology can not only give marketers peace of mind that their first-party data is onboarded in a safer environment, but also yield more granular and meaningful insights at an increased speed thanks to automation. 

Plus, data platforms that don’t rely on cookies can, of course, help marketers succeed as Google moves to deprecate cookies on Chrome in 2024.

By leveraging a data platform that encompasses all available identifiers — everything from IP to home address — marketers can make additional sense of their data and, thus, further define audiences for segmentation.

How Big Data Platforms Perform

So what does a big data management platform look like in action? A marketing team we know onboarded a Data Platform to illustrate campaign effectiveness to their clients, who primarily work in CPG and Retail. They had worked with other DSPs in the past but found many did not provide attribution in cookieless channels, like CTV. Given how effective upper-funnel messaging can be to CPG and Retail consumers, the ability to tie CTV ad exposure to KPIs like purchases from one of their client’s ecommerce sites or in-store purchases, was a game-changer in today’s physical-digital shopping experience. Reports can be customized to suit a client’s particular KPIs or target level of detail.

Self-Service or Full-Service?

For many organizations, a self-service approach to data analysis is the most efficient and cost-effective approach. Yet many marketing teams, including ad agencies, are increasingly opting to utilize a service model to augment their in-house data analytics. Deploying a Big Data Platform as a service can broaden a marketing team’s sources of premium data, reporting and automation infrastructure, storage and querying capabilities, BI visualization tools and more. 

Using a Big Data Platform on their own or with assistance, marketers will find that leveraging a clean room integrated Data Platform creates a safe environment for first-party data onboarding, activation and closed-loop measurement to understand the impact of their offline converters. 

Here’s where to find out more about data platforms