Reclaiming marketing data: How The Economist drove better ROAS with Supermetrics

For The Economist, data isn't just about tracking subscriptions—it's about understanding the "why" behind every click. Mikhail Sladkomedov, Senior Acquisition Analyst, sits at the intersection of complex technical pipelines and commercial decision-making. His team ensures that every dollar spent drives growth.

By partnering with Supermetrics, the acquisition team reclaimed control of their marketing data—transforming from a manual reporting unit into an insights engine.

The engineering bottleneck and the cost of manual data

In the fast-moving media world, The Economist needs to react to global events in real time. But their data foundation lacked that agility. Fragmented data across dozens of social, search, and programmatic platforms meant the team lacked a single source of truth.

Because their data was fragmented and siloed, the business was losing money by being unable to react to market shifts in real-time. When a key metric like Cost Per Acquisition (CPA) spiked, the team couldn't pivot quickly. Instead, they had to manually dig into soft metrics—like impressions and clicks—to find the root cause. This was a resource-heavy process that drained the team's strategic capacity and delayed budget optimization.

Beyond the manual workload, the team faced a classic enterprise hurdle: a total dependency on engineering sprints. Any change to a data definition or a new tracking parameter required translating the business need and logic into technical requirements for the engineering team. This created a costly bottleneck, leaving the marketing team waiting for engineering capacity to answer urgent business questions while optimization windows closed.

The Economist didn't just need more data — they needed to reclaim control over their data structure to drive faster, data-backed decisions.

Reclaiming the marketing data foundation & self-serving data

The Economist implemented Supermetrics to automate the data flow from over a dozen sources—including LinkedIn, Meta, and GA4—into Amazon S3 and Snowflake. This allowed the acquisition team to move the business logic from IT into the hands of the analysts.

On top of centralizing data, the team uses Supermetrics for:

• Automated data transformation: Using Supermetrics' Custom Fields , the team standardizes their strict UTM taxonomy. They automatically break down campaign strings containing 10–15 parameters into granular dimensions such as landing page category and optimization type.
• Closing the loop with offline data: By using Custom Data Import to ingest offline data feeds, the team can combine traditional media spend with digital performance in one unified report.
• Currency standardization at scale: With ads running in dozens of countries, the team uses Custom Fields to convert currencies . This way, they can avoid the maintenance nightmare of building and fixing internal exchange rate APIs.
• Data democratization: By feeding cleaned data into Looker Studio dashboards, marketing executives can "self-serve" insights. They can build reports and get answers instantly, without waiting for the analytics team.

Mikhail explains, "We try to do as much as possible within Supermetrics using Custom Fields. It allows us to make changes on the fly without having to go back into the warehouse or write new SQL code. We're essentially translating business needs into technical logic ourselves."

When comparing providers, Mikhail found that Supermetrics offered a competitive advantage through AI capabilities . The ability to use AI for image and text labeling within the Platform matched The Economist's sophisticated analytical goals—allowing them to analyze creative performance without writing a single line of Python.

Results: Driving ROAS through AI and efficiency

The most significant impact was the shift from analysts being a reporting team to an intelligence team. With Supermetrics, the acquisition team gained ownership of the data. They can now view commercial metrics, such as CLTV and CPA, alongside engagement metrics. This combination gives leadership the background story of performance, moving the organization from guessing to knowing.

1. 80% reduction in data collection workload

The workload for collecting and preparing data for high-level modeling dropped from 10 people to just 2 analysts. This shift allowed the team to focus on analysis rather than piecing data together.

2. Significant ROAS improvement

Greater agility led to direct commercial gains. Instead of quarterly performance reviews, the team moved to weekly check-ins. This speed allows them to identify underperforming channels and reallocate budgets immediately—driving a significant improvement in ROAS over the last two years.

3. Powering Marketing Mix Modeling (MMM)

Supermetrics streamlined the data collection process that feeds The Economist's predictive models. This enables a two-pillar strategy: a long-term strategic view via MMM , and a tactical view to react to spontaneous market shifts.

4. Scaling with AI

The Economist's setup is now built for the future. Having already integrated AI into their creative analysis, the team is now bridging the gap between creative and data. By using Supermetrics to see creative assets directly alongside performance metrics, they can finally understand the "why" behind the performance.

The team is eager to further explore the Supermetrics AI roadmap. One key area of interest is the development of AI-driven connector building. While Supermetrics already automates most of their data sources, the ability to use AI to quickly build custom connectors for niche or internal sources would be a game-changer. Mikhail explains, "Even if the connector building happens in the future, I think we'll transfer it to Supermetrics to avoid the maintenance workload. It allows us to focus on the creative and insightful parts of our profession."

A shared vision for innovation

The Economist found a partner in Supermetrics, with a roadmap that aligns with its own. By continuously developing new AI capabilities, Supermetrics empowers The Economist to move fast and stay ahead of the curve.

Ultimately, this partnership has given The Economist a data foundation that thrives in an unpredictable media landscape—moving the team away from manual reporting and toward driving real revenue.