Marketing Measurement Framework: 4 Layers That Connect with iridio by RRD

Performance data isn’t decision clarity. Learn the 4-part marketing measurement framework that helps marketers actually decide.

Marketers have more measurement tools at their disposal than ever before. Dashboards, attribution models, incremental lift studies, media mix modeling platforms… the list keeps growing. But more data hasn’t translated into more clarity. Most marketing teams still find themselves stuck on the same question: what should we actually do next?

In this episode, Derek DeGroat walks through the four-part measurement framework his team built at iridio by RRD to solve exactly that problem. Instead of treating measurement tools as a stack of standalone reports, the framework connects them into a system where each layer answers a different question across the campaign life cycle.

Jesse and Derek get into how segmentation, marketing mix modeling, in-campaign testing, and weekly optimization actually fit together, and why connecting them is what separates performance data from decision clarity.

What this episode covers

  • Why marketers still struggle with measurement despite having more tools than ever
  • The difference between performance data and decision clarity
  • How segmentation, MMM, in-campaign testing, and weekly optimization work as a system
  • When to refresh each layer (annually, quarterly, weekly)
  • How to connect upper-funnel impressions to bottom-line sales and profit
  • What it looks like to reconcile MMM forecasts against actual performance
  • Why data infrastructure is the foundation underneath any measurement framework

Key takeaways

  • Performance data and decision clarity are not the same thing. Marketing teams have more measurement tools than ever, yet most still get stuck on the question, “what should we do next?”
  • iridio by RRD’s measurement framework consists of four connected layers organized by frequency: segmentation, marketing mix modeling, in-campaign testing, and weekly optimization. Each layer answers a distinct question, and the layers feed each other rather than operating in silos.
  • Marketing mix modeling sits at the strategic center of the framework, forecasting incremental ROI by channel, points of diminishing returns, and the impact of different budget scenarios.
  • The framework connects upper-funnel marketing impressions to bottom-line revenue and profit, giving marketers a way to report marketing’s contribution in P&L terms that CMOs, CFOs, and CEOs can act on.
  • Data infrastructure is the foundation underneath the entire framework. A CDP for first-party data and accessible media spend tracking are what make faster decisions possible.

The 4-part measurement framework, explained

Derek’s framework is organized by frequency, not by sequence. Each layer answers a specific question, and the layers feed each other.

Layer 1 – Segmentation: Who are we trying to influence?

Segmentation defines the customer. New versus existing buyers, high-value versus low-value, lapsed buyers, product affinity, and so on. It pulls from first-party data and the CRM, then sets the stage for everything downstream.

For multi-location brands, segmentation also surfaces market-by-market dynamics. Two stores might sell the same product but have completely different customer penetration, demographics, and product opportunity. That changes targeting, messaging, offers, and budget allocation by market.

Refresh cadence: Occasional. Once a segmentation strategy is in place, it doesn’t need weekly attention.

Layer 2 – Marketing mix modeling (MMM): Where should we spend, and how much?

MMM sits at the strategic center of the framework. It analyzes historical data across marketing channels and external factors, then forecasts incremental ROI by channel, points of diminishing returns, and the impact of different budget scenarios.

“Performance data isn’t the same thing as having decision clarity.”

This is where iridio’s partnership with Keen comes in. The Keen engine captures seasonality, market dynamics, and cross-channel interactions, then answers questions like:

  • Are we overinvesting in a channel?
  • Is there still room to scale?
  • What happens if we shift budget from one channel to another?
  • What happens when we introduce a new channel?

MMM is also where actual performance gets reconciled against forecast. When the model recalibrates, you can see whether results are tracking with projections, and adjust the plan based on the latest data.

“It’s not just about understanding what happened, but knowing what to do next.”

Refresh cadence: Quarterly or semi-annually.

Layer 3 – In-campaign testing: Which audiences and creatives are working?

MMM tells you where to invest at a strategic level, but it isn’t designed to test individual campaigns, creatives, or audience strategies. That’s the job of in-campaign testing.

This layer answers near-term questions through structured A/B tests:

  • Which messages move the needle in which markets?
  • How do different products perform against each other?
  • Which audience strategies are actually working?

It’s the bridge between strategic planning and day-to-day execution.

“It’s less about individual tools and more like a system for answering different questions across the entire campaign life cycle.”

Refresh cadence: Campaign by campaign.

Layer 4 – Weekly optimization: Are campaigns running efficiently?

The final layer is the day-to-day work of monitoring CTR, engagement, frequency, and pacing inside DSPs and ad platforms. The metrics haven’t gone away, but they’re now informed by the layers above.

That context matters. You’re not optimizing in a vacuum. You know who you’re targeting (segmentation), how much you should be spending (MMM), and what’s working creatively (in-campaign testing). Weekly optimization is about making sure you deliver in full and stay responsive to what’s actually happening in market.

“You can actually connect impressions to short and long term sales revenue and profits. The real P&L level metrics that make the business grow.”

Refresh cadence: Weekly.

Why this framework matters now

Most brands still default to last-click attribution, even as the limitations have become harder to ignore. Privacy changes, signal loss, and fragmented media have made it tougher to attribute outcomes to a single touchpoint. At the same time, CFOs and CEOs want clearer answers about what marketing is actually contributing to the business.

This framework gives marketers a way to meet both demands. It produces real forecasts that can be reconciled against actuals, organizes when decisions get made and which questions each layer answers, and connects upper-funnel marketing activity to bottom-line revenue and profit.

It also sets expectations across the organization. Stakeholders know when they’ll get certain insights, when an answer requires a quarterly MMM refresh, and when the team is making real-time adjustments based on weekly data.

About iridio by RRD

iridio by RRD is a full-service marketing agency with end-to-end capabilities across data management, audience identity, media activation (including its own DSP and print operations), and performance measurement. iridio partners with Keen Decision Systems to deliver media mix modeling as part of its measurement framework.

Connect with Keen

Keen Decision Systems helps marketers connect upper-funnel impressions to short- and long-term sales, revenue, and profit through marketing mix modeling. To learn more about how Keen can fit into your measurement framework, visit keends.com.

FAQs

What is a marketing measurement framework?

A marketing measurement framework is a connected system of analytical layers that work together to answer different questions across the campaign life cycle. Instead of treating tools like dashboards, MMM, and lift studies as standalone reports, a framework organizes them so each layer informs the next, helping marketing teams move from raw data to clear decisions.

How often should marketing mix modeling be refreshed?

Marketing mix modeling should be refreshed quarterly or semi-annually. Refreshing on this cadence lets the model recalibrate as new data comes in, so marketers can reconcile actual performance against the forecast and adjust budget allocations based on the latest market dynamics, channel results, and external factors.

What questions does each layer of the four-part framework answer?

Each of the four layers answers a specific question:

  • Segmentation: Who are we trying to influence?
  • Marketing mix modeling: Where should we spend, and how much?
  • In-campaign testing: Which audiences and creatives are working?
  • Weekly optimization: Are our campaigns running efficiently in market?

What is the difference between marketing mix modeling and last-click attribution?

Last-click attribution credits only the final touchpoint before a conversion, missing the contribution of upper-funnel media. Marketing mix modeling analyzes historical data across all marketing channels and external factors, forecasting incremental ROI, points of diminishing returns, and the impact of budget shifts. MMM connects upper-funnel impressions to short- and long-term sales, revenue, and profit.

How does customer segmentation connect to media planning?

Customer segmentation defines who you’re targeting (new versus existing buyers, high-value versus low-value, lapsed buyers, product affinity) and surfaces market-by-market dynamics. For multi-location brands, segmentation feeds directly into MMM by informing customer penetration around stores, budget constraints within trade areas, and product opportunity by market.

Why is last-click attribution no longer enough for marketers?

Last-click attribution misses upper-funnel media contribution and cannot connect marketing activity to long-term business outcomes like revenue and profit. With privacy changes, signal loss, and fragmented media, a single-touchpoint model gives an incomplete picture. Marketers need a framework that ties impressions to P&L-level metrics CFOs and CEOs care about.

What is in-campaign testing in marketing analytics?

In-campaign testing is the layer of marketing measurement that runs structured A/B tests during a live campaign. While MMM forecasts where to invest at a strategic level, in-campaign testing answers near-term questions: which messages move the needle in which markets, how different products perform against each other, and which audience strategies are actually working.

What role does data infrastructure play in marketing measurement?

Data infrastructure is the foundation underneath any measurement framework. A customer data platform (CDP) for first-party data and accessible media spend tracking by channel make faster decisions possible. Without that infrastructure, teams spend weeks compiling data to load into analytics tools, which slows down every decision the framework was built to support.

Links & Resources

Hosts & Contributors

Jesse Math

VP of Strategic Partnerships,
Keen Decision Systems
Jesse partners with agencies and brands to implement data-driven marketing strategies, optimizing cross-channel investments and building collaborative solutions for business growth.

Derek DeGroat

Director of Marketing Analytics,
RRD
Derek DeGroat is Director of Marketing Analytics at RRD (RR Donnelley). He leads the team responsible for the analytics tools and frameworks that help iridio’s clients make data-informed decisions across segmentation, media mix modeling, in-campaign testing, and ongoing campaign optimization.

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