• by Valerie Renda , March 17, 2025

In the last few years, with increasing focus on consumer privacy, new ad-tech platforms and offerings have sprouted up rapidly  -- and those that already exist are expanding capabilities. But what is truly necessary in an ad-tech stack that prioritizes data privacy and governance, marketing measurement, and audience targeting capabilities?

Much like in a game of Jenga, each block serves a structural purpose, and thoughtful placement is crucial. Just as randomly adding or removing pieces can cause a Jenga tower to collapse, implementing technology solutions without a strategy can destabilize your entire marketing infrastructure.

Let’s break down key ad tech in the identity and tracking space, and where they might fit into your stack:

CDPs: Customer data platforms. These are unified databases that collect first-party data from multiple sources, create persistent user profiles for cross-channel data, and allow activation of these audiences.

-- Use case: Most helpful for advertisers with significant first-party data across multiple channels and platforms or with complex customer journeys.

CRMs: Customer relationship management -- a platform that tracks and manages customer interactions and sales pipelines, often serving as the system of record for customer history.

-- Use case: Essential for advertisers with direct customer relationships (so you likely already have this capability).

DMPs: Data management platforms, which manage anonymous third-party audience data for extended reach. Their role is evolving amid privacy changes in the industry.

-- Use case: Historically have been great for advertisers heavily focused on prospecting.  However, with privacy evolution, you need to consider which DMPs or third-party partners have scalable, future-proofed solutions.

TMS: Tag management systems -- platforms that manage tracking tags/pixels across your digital properties to ensure website data collection.

-- Use case: Crucial for website tracking (so likely within your stack already). It might be time to consider tracking beyond browser-side tagging though, and evaluate whether server-side tracking would be beneficial for your measurement ecosystem.

Identity resolution: Technology that connects multiple digital identifiers to create a unified view of individual users across devices and channels.

-- Use case: Helpful for advertisers with significant cross-device customer interactions or offline/online touchpoints.

Data lake: Large-scale storage repository for raw, unstructured data from various sources.

-- Use case: Beneficial in handling massive amounts of varied data types requiring advanced analytics capabilities.

Data warehouse: Structured database that stores processed, ‘cleaned’ data in organized schemas for analytics and reporting purposes.

-- Use case: Essential for advertisers requiring regular reporting, complex data analysis, or looking to centralize data from multiple sources for business intelligence.

Balancing Clarity and Complexity: Finding the Perfect Stack

The key to building an effective ad-tech stack isn’t accumulating every possible technology. It’s about thoughtful integration of solutions that serve your needs while maintaining data governance and operational efficiency.

The most successful organizations are those that find the balance between capability and complexity, choosing tools that work together seamlessly while prioritizing both customer privacy and marketing effectiveness, and choosing the right partners to do so. After all, the goal isn’t to have the tallest or biggest tech stack -- it’s to have one that stands strong because every piece serves a purpose.