If you're running a large-scale marketing operation, your "solved" reporting approach is likely costing you millions each year. This article breaks down the rationale and math behind this claim.

If you're managing an 8- or 9-figure marketing budget across multiple channels and markets, you might think your reporting challenges are behind you. Your 2025 roadmap likely focuses on high-impact initiatives like Marketing Mix Modeling, incrementality testing, and AI-powered creative optimization.

After all, your data team has spent years building marketing reporting on top of your company's modern data stack—data warehouse (e.g., Snowflake), ETL pipelines (e.g., Fivetran), and BI tools (e.g., Looker).

With so much time and effort invested, it’s painful to consider: what if this approach is no longer the right solution? Your marketing reporting approach is costing you millions annually—both in wasted ad spend and operational costs.

Understanding the true cost of your marketing reporting

A CMO managing a 9-figure marketing budget recently shared their challenge: “I have the dashboards I need for my bird’s-eye view, but my marketers don’t have what they need.”

Despite a dedicated marketing analytics team (six people) supporting her 30-person marketing team and leveraging Looker, Fivetran, and Snowflake, her team struggled. Data requests took weeks to fulfill, and her analytics team spent most of their time on reporting tasks, taking time away from MMM and incrementality testing. Marketers resorted to spreadsheets for deep dives and daily analysis (e.g., budget pacing, creative reporting). Worse, they couldn't analyze performance at the asset level without waiting for Looker dashboards to load.

“Is this normal?” she asked. Unfortunately, yes—and it’s costing organizations like hers millions each year.

Two approaches, similar costs

We've observed two distinct approaches among enterprise organizations, depending on the level of dedicated marketing analytics resources and reporting depth.

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

The cost of relying on a company-wide BI stack extends beyond frustrated data teams and marketers stuck in spreadsheets. It significantly impacts both marketing efficiency and operational costs.

Impact on marketing efficiency

While budgets are decided at a higher level, execution happens daily with performance marketers at the asset, ad group, and campaign levels. For teams managing 8- or 9-figure marketing budgets, missed optimization opportunities can result in significant wasted ad spend.

Missed insights

Many analyses are either impossible on generic BI platforms or require excessive manual work. Even when asset-level reporting exists in Looker, gaps remain. Common issues teams recognize soon after switching include:

• Creative analytics: No ad preview next to performance metrics and limited key drivers analysis (e.g., which creative concepts/elements drive performance)

• Gaps in keyword cannibalization (paid search - SEO)

• Manual budget pacing, without automated breakdowns

• Keyword gap analysis

• Auction insights

• Etc

Slow time to insight

Data requests for new dashboards, metrics, dimensions or breakdowns often take weeks or even months, leading to wasted ad spend. Performance marketing demands real-time iteration—marketers must be able to shift budgets and adjust tactics quickly. Yet, they often find themselves waiting on data teams just to create or modify a dimension or metric.

This approach works well for static dashboards but fails to provide the flexibility and speed performance marketers need.

Marketing Analytics workflows: status quo leads to long turnaround times

Slower experimentation and iteration cycles

Performance marketing thrives on rapid testing and iteration. When marketers depend on slow data workflows or manual spreadsheets, they test less frequently and iterate more slowly—resulting in missed optimization opportunities.

Silos

When different teams rely on separate tools for operational reporting (e.g., paid search in Looker Studio, paid social in Smartly), collaboration suffers. The problem worsens when marketers resort to daily analysis in spreadsheets. Cross-channel insights become limited, ultimately impacting marketing performance.

Operating cost

Total cost of ownership includes dedicated people and tools used for marketing reporting:

• Labor costs: Data analysts, analytics engineers, and data engineers.

• Tool costs: ETL tools (e.g., Fivetran) and data warehouse expenses (storage + compute).

Calculating the total cost

The formula for annual marketing reporting costs is straightforward: 

Marketing Reporting Cost = Wasted Ad Spend + Operating Costs (Labor + Tools)

Breaking it down:

Keep in mind that this equation will vary by company, but we’ve found that our framework can get most teams started. Let’s apply the formula to the example previously mentioned:

These are the underlying assumptions:

• The average fully loaded cost of a data FTE is $120,000 per year (source: Glassdoor).

• Time spent on reporting ranges between 50% and 90% (source: interviews and surveys with 150+ enterprise marketing data teams across industries).

• ETL tool costs (e.g., Fivetran) can be estimated online based on Monthly Active Rows (e.g., Fivetran pricing estimator).

• Data warehouse costs (e.g., Snowflake) are often difficult to segment by business function, as they depend on data volume and query frequency. Based on 50+ data points, we estimate annual costs between $75,000 and $1,000,000.

Based on our experience (100+ data points), the total estimated costs vary depending on the approach to marketing reporting previously described:

Measuring the cost of your marketing reporting is the first step towards fully understanding the implications of this approach to data and insights. Fortunately, this cost is avoidable. With the right approach to data and insights, you can enable deeper, faster insights for marketers and run reporting much more efficiently.

The Solution: marketing reporting as a product

As you can see from the calculations above, marketing reporting is no small problem. As the marketing landscape evolves faster than ever, uncovering what’s working in time is critical. Reporting is becoming a key strategic lever. The best way to solve this problem is by adopting a product-centric approach built on two principles:

1) True Marketing Self-Service: Marketers should be able to go from question to insight in minutes without relying on data teams. This requires custom dimensions and metrics that can be modified by marketers themselves.

2) Automated Marketing Reporting: Valuable data resources should focus on advanced measurement, not basic reporting. The key is full automation of: data harmonization across channels, data matching (backend, attribution, channel) and marketing pipelines maintenance. 

The only way to achieve this is by enabling self-service operational marketing reporting while maintaining a single source of truth through harmonized marketing data exports to the company data warehouse.

Marketing reporting as a product: the right approach for effective self-service

Have another way to measure the cost and impact of marketing reporting? Schedule a demo or reach out to me directly - arun@clarisights.com