If you're running a large-scale marketing operation, your "solved" reporting approach is likely costing you millions each year.

If you're managing an 8- or 9-figure marketing budget across multiple channels and markets, you probably think your reporting challenges are behind you. Your 2025 roadmap is focused on “sexy” initiatives like Marketing Mix Modeling, incrementality testing, and AI-powered creative optimization.

After all, your data team has invested years building marketing reporting on top of your company's modern data stack:

• Data warehouse (Snowflake, Redshift, BigQuery, Databricks) as source of truth

• ETL pipelines (Fivetran, Airflow, Funnel) to ingest marketing data

• BI tool (Looker, Tableau, Power BI) to visualize data

With so much time and resources invested, it’s painful even to consider: what if this approach isn’t the right solution anymore?

The big fallacy - marketing reporting is “nearly” solved

The fundamental problem? Marketing reporting isn't static – it's dynamic and ever-evolving. While most teams chase the myth of "completing" marketing reporting - by modeling more metrics or hiring another marketing analyst to enable "self-service" and free analytics resources to focus on measurement.

The reality, however, is quite different. You think this doesn't apply to your organization? Ask yourself: How long do your marketers wait for data requests to be fulfilled? How many spreadsheets do they maintain just to track budget pacing and delve into channel performance?

Marketing & Data Teams: the real struggles behind reporting

What's the root cause? Digital marketing inherently requires constant testing and iteration – and with that comes constant change. As marketing strategies evolve, so do data needs. The real problem is that marketers must rely on data teams for insights because they lack true self-service capabilities.

Why this challenge is reaching a breaking point

3 market forces are making traditional approaches increasingly unsustainable (read more into the new paradigm and how the best teams are staying ahead):

1) Acceleration of change: AI-powered campaigns like Google PMax and Meta Advantage+ are reshaping the landscape. Combined with new channels proliferation and AI-generated creatives, understanding performance in real-time is more critical than ever.

2) Heightened Financial Scrutiny: The economic climate demands profitable growth. Marketing teams must do more with less while facing unprecedented pressure to justify every dollar spent.

3) The privacy shift and signal loss: OS 14, SKAN, and the death of cookies have fundamentally broken traditional attribution. Teams need new approaches to measurement, yet most data teams are stuck in reactive reporting work.

Data Teams: trapped in the cycle of reactive marketing reporting maintenance

The actual cost of your marketing reporting

Our analysis of hundreds of enterprise marketing teams reveals two common approaches, both with significant hidden costs:

1 - Data resources dedicated to marketing include data engineers, analytics engineers and data analysts

You probably fall somewhere on the spectrum between these two approaches. To understand the true financial impact, let's break down the costs into two key components:

1) Lost marketing efficiency - wasted ad spend due to missed insights/optimization opportunities, slow time to insight, lower experimentation and silos.

2) Total cost of ownership - labor and tools required to run marketing reporting. This includes data warehouse storage and compute, ETL tools and dedicated data resources (data engineers, analytics engineers and data analysts).

Ready to dive into the numbers? Learn how to calculate the real cost of your marketing reporting.

A new way - marketing reporting as a product

The solution isn't “throwing” more resources at the problem or limiting reporting to campaign-level. It's rather fundamentally rethinking how to deliver insights and data needed for marketing teams. Drawing inspiration from product analytics platforms like Mixpanel and Amplitude, we believe marketing reporting should function as a product, built on two core principles:

1) True Marketing Self-Service: Performance marketing requires rapid iteration. Marketers need the ability to customize dashboards, metrics, and dimensions without depending on data teams.

2) Automated Marketing Reporting: Valuable data resources should focus on advanced measurement (MMM, Incrementality, MTA, etc), not reinventing the wheel on marketing reporting. Data harmonization across channels down to asset level, data matching (backend, attribution, channel) and marketing pipelines maintenance should be 100% automatic.

Why marketing reporting as a product is the future

In today's data-driven, fast-changing marketing landscape, here's why purpose-built marketing reporting platforms are becoming the new standard for companies managing significant marketing budgets:

New advanced optimization capabilities

Purpose-built marketing reporting platforms deliver specialized capabilities that drive real impact, such as:

• Real-time creative analytics with performance metrics alongside ad previews

• Intelligent budget pacing and automated segmentation

• Advanced keyword clustering and analysis

• Auction insights

• Etc

For teams managing 8 or 9-figure marketing budgets, these capabilities translate directly into significant efficiency gains —without more data tickets or manual spreadsheets.

Time to insight

Marketing steering can't wait for data support. Marketing reporting as a product empowers marketers with no-code solutions to create and modify custom dimensions and metrics, build specialized reports and ultimately make data-driven decisions faster and more independently. Without SQL or spreadsheets.

Marketing Analytics workflows: Traditional vs. Product-driven Approaches

Affordability

The traditional approach to marketing reporting comes with staggering costs. Every change requires data team support, consuming valuable resources. Data storage and compute costs often skyrocket for large-scale teams as reporting becomes more granular (ad group and ad level). Add expensive ETL tools like Fivetran to the mix, and costs quickly become unsustainable.

The marketing reporting as a product approach automates data joining, harmonization and matching, and enables marketers to effectively self-serve. This frees up valuable data resources while eliminating marketing compute and ETL costs. Its unique, proprietary data warehouse designed for scale allows companies to run effective reporting at significantly lower costs.

Enterprise-grade data governance

Enhanced self-service shouldn't lead to data chaos. Data teams rightfully prioritize governance to prevent inconsistencies in numbers and definitions. Modern companies need an ultimate source of truth in their data warehouse.

This new approach is built with these priorities in mind. Robust governance measures, including Role-Based Access Controls (RBAC) and structured workspaces, prevent data chaos. This framework has been co-developed with complex enterprises like Uber and Delivery Hero. 

Harmonized marketing data exports to any data warehouse ensure a single source of truth while saving precious time and reducing tool costs, powering everything from C-level dashboards to marketing measurement models and cost pipelines for finance teams.

Marketing reporting as a product: analytics without compromise

Time to value

While traditional data migrations and projects often stretch across months or years—even a "simple" GA4 update can take quarters—this approach is purposely built for short time to value. 

It offers automatic harmonization of ad platform data across common dimensions (cost, keywords, campaign types, assets, videos, etc.) and automatic backend and attribution data joining at the most granular level. Teams can be up and running within one week, requiring minimal data and BI support (read more about the process here). 

Security

Data security remains paramount when adopting new marketing and data technology. This approach processes no Personally Identifiable Information (PII) or user data. All processed data comes pre-aggregated from the sources themselves through reporting APIs, with no pixels or SDKs required. This makes compliance straightforward and secure (read more here).

Clarisights approach is fully compliant and secure (no PII, user data, pixels or SDKs)

The road ahead

As this approach gains traction, some of the largest, most sophisticated teams are adopting it, including Uber, HelloFresh, Delivery Hero, and others. The platform is purpose-built for large-scale performance marketing teams, designed to meet their specific needs while aligning with data teams' vision of a single source of truth and proper data governance.

Hundreds of large teams have embraced this approach, implementing Clarisights alongside their company-wide modern data stack:

• How Delivery Hero democratizes data to 300+ marketers

• On scales efficiently through 3x more tests and new optimization levers

• HelloFresh reduced CAC by 10-20% with Clarisights

• Bitpanda drives efficient growth in a highly competitive and volatile market

Ready to explore how this approach could transform your marketing operations? Reach out to our team for a demo. If you're interested in discussing the future of performance marketing and data, contact me directly at arun@clarisights.com