Brand tracking, attribution, incrementality testing, Marketing Mix Modeling: Which measurement method should ​​you use, when, and why?

Nowadays, marketing teams have access to a plethora of tools to measure performance, including digital marketing attribution, incrementality testing, brand tracking, and Marketing Mix Modeling (MMM). Each method promises answers that are often accurate, but are rarely convergent. These ​​contradictory results are difficult to link up, and ​​can slow down decision-making and getting teams on board with field measurement.

Behind a simple question—"Which method should I choose, for what use, and toward which objective?”—lies a veritable orchestration challenge. In this article, we decipher the specificities of each approach, their use cases, and how they can complement each other with a triangulation logic. The objective: to help you develop a unified measurement strategy that is aligned with your business priorities and capable of informing your short-term decisions as well as managing your long-term challenges.

Which method should ​​you use?

Performance marketing is not limited to click or impression attribution. It is built up over time, at the intersection of several dimensions, including brand image, activation, customer experience, and competitive environment. To effectively assess this performance, several methods coexist, each with its own scope, strengths, and limitations. Understanding their use cases helps to ​​connect them better.

1. Brand tracking and studies

Useful for tracking changes in brand perception over time, this method often relies on quantitative/qualitative surveys. It allows you to track indicators such as brand awareness, consideration, or purchase ​​intention.

• Strengths: Supporting brand strategy diagnostic and management by revealing the emotional factors.
• Limitations: A ​​comprehensive, but not very operational, view with little granularity in the analysis of specific campaigns or activations.

2. Marketing Mix Modeling (MMM)

MMM models the ​​actual impact of all your marketing levers—media, pricing, promotions, distribution—as well as external factors such as seasonality or competition.

• Strengths: Thanks to its holistic approach to the effectiveness of marketing investments, it allows you to look objectively at your budgetary choices and trade-offs and to align marketing and finance.
• Limitations: A less pertinent method for ​​managing operational decisions in real time, MMM requires an analysis of robust historical data and fits with a strategic rather than a tactical logic.

3. Incrementality testing

This experimental method allows you to assess the impact of a modification by comparing an exposed group and a control group. It is particularly adapted to testing specific elements in a quick and targeted manner, such as differences in creative content, geographic targeting, or population segmentation.

• Strengths: Agility, ​​quantified evidence, and a continuous learning process
• Limitations: It requires high statistical rigor and a properly controlled environment for interpretation (​​side effects, sample size, bias)

4. Digital marketing attribution

Digital marketing attribution aims to measure, often in real time, how digital channels contribute to conversions. It supplies media optimization platforms (e.g., Google and Meta) with indicators such as ROAS or CPA.

• Strengths: High granularity, daily management of online campaigns
• Limitations: Partial view, biased by platforms’ algorithms and rules, difficulty integrating off-line levers and long-term effects, so little correlation with global business results

A frequent error: Isolating methods instead of blending them

Each method has its strengths. Yet many organizations rely exclusively on one approach, leading to:

• Media decisions based solely on the most recent clicks on platforms.
• Campaigns tested in isolation, without integration into the global performance context.
• Brand tracking research focused on monitoring brand awareness, without linking to sales fluctuations.

Doing this is akin to staying on the surface of the data.

The complementary nature of the approaches: Toward a 360° view of performance

The real strength of a marketing measurement strategy does not lie in the use of a method in isolation, but in its capacity to combine several approaches intelligently. This articulation enables the development of a coherent, robust vision that is truly aligned with your business objectives.

Each method addresses a specific need: incrementality testing provides a quick and thorough interpretation of targeted activations; digital marketing attribution helps manage performance per channel in real time; brand tracking captures changes in brand perception over time; and MMM acts as a strategic ​​arbitration engine, modeling mid- to long-term global impact.

By combining them in a logic of triangulation, you take advantage of their natural complementarity: MMM provides depth to attribution insights, the test results fuel the models, and tracking enriches the understanding of ​​brand impact. Therefore, the challenge is not choosing a method but fostering dialogue between them to develop a unified interpretation of performance—one that is reliable, actionable, and reciprocal.

Example:

• A/B tests enable validation of hypotheses to integrate into the MMM to model at a larger scale.
• In return, MMM corrects the digital marketing attribution results by integrating indirect or deferred effects.
• The long-term tracking results fuel the models to reflect the global impact of branding actions.

This cross-calibration creates a “common measurement currency” shared between marketing, data, and financial ​​functions.

Result: A strategy that is guided, not simply tracked

• An enhanced strategic vision, thanks to a refined understanding of the true drivers of growth, both in the short- and long-term. This clarity allows you to align marketing decisions to fundamental business dynamics.
• A heightened operational agility, made possible by access to reliable, tactical, and continuous feedback. Teams can quickly test, adjust, and ​​redirect their efforts based on ​​actionable and contextualized data.
• A more coherent governance creates a common language between marketing, data, finance, and partner agencies. Decisions are no longer made in silos, but in a shared ​​framework that facilitates budget allocation, multi-lever management, and actual performance measurement.

How do ​​you choose the ​​best method(s)?

Each method addresses a type of question. Your objectives, your temporality, and your level of data maturity must therefore guide your choices.

According to your objectives

• Long-term vision and portfolio strategy: brand tracking et MMM
• Short-term optimization and activation: A/B Testing and attribution
• Innovation and testing new levers: field testing and pre-/post-testing

Depending on your digital and data maturity

• Reliable historical data: maximal MMM potential
• Agile team equipped for activation: harness the full potential of A/B Testing
• ​​​Decentralized or multi-market organization: centralize measurement via ​​​​coherent, inter-method KPIs

For maximal effectiveness: structure and decompartmentalize

• Create touchpoints between your marketing, data, and finance teams
• Train your teams toward a shared measurement culture
• Avoid the “rapid data” vs. “reliable data” duality: both are necessary, but we don’t ​​expect the same thing from them

Concrete example: How Sky structured its marketing measurement around a unified method

In 2015, facing the acceleration of its operations (new market, product, and channel launches), the media group Sky—a key player in media and entertainment in Europe—embarked on a complete overhaul of its marketing measurement strategy.

Before: Analyses were split across several service providers and tools. MMM was outsourced, tests were rarely industrialized, and performance indicators varied from one tool or team to another, with no coherence or unified ​​framework. Result: Decisions were guided by the data available… rather than by pertinent data.

After: Sky assembled an internal team of 30 marketing modeling specialists to take back control of the MMM and establish a unified decision-making framework. Articulating the different methods (tests and experiments, digital marketing attribution, brand tracking) within a triangulation logic, each technique fuels and validates the others. MMM acts as a common foundation—a “common currency”—facilitating cross-reading between methods, coherence of KPIs, and alignment between short-term performance and long-term vision.

Concrete results:

• Adoption of a common reference framework for effectiveness used to manage media budgets, annually and during the year
• Integration of brand tracking, attribution, and A/B tests in a unified decision-making methodology
• Improved collaboration between marketing, finance, and data, with a results-oriented management
• Capacity to quantify the impact of strategic trade-offs on business KPIs

Key takeaways

• Good marketing measurement relies less on mastering a tool than on the capacity to develop a coherent ecosystem that is aligned with your priorities.
• By combining brand tracking, attribution, testing, and MMM, you can create a more valuable and more robust interpretation, essential for arbitrating, innovating, and growing your investments.
• This holistic approach promotes dialogue between professions, speeds up decision-making, and uses data to drive growth.