Marketing Science: What is it and how to implement it in 2026?

What is Marketing Science?

Marketing Science is the application of scientific methods and quantitative models to understand, predict, and optimize consumer behavior and marketing performance. Thru techniques such as econometric modeling, data analysis, and incrementality testing, this discipline transforms data into high-impact decisions.
Traditionally used in academic settings and large consulting firms, today it has become a key competitive advantage for brands seeking efficiency, precision, and measurable results.

Differences between Marketing Science and traditional marketing

Although both approaches seek to improve marketing performance, there are key differences between traditional marketing and Marketing Science:

• Focus: while traditional marketing relies on the experience and intuition of teams, Marketing Science uses data, statistics, and predictive models to make evidence-based decisions.
• Decision-making: in the traditional approach, many decisions are made after the campaign, analyzing results retrospectively. In contrast, Marketing Science enables real-time optimization, adjusting strategies on the fly.
• Measuring impact: traditional marketing often measures results with simple metrics (such as last-click attribution), whereas Marketing Science applies techniques like incrementality, multivariate analysis, or marketing mix modeling to understand which actions truly generate value.
• ROI: with Marketing Science, it’s possible to calculate the marginal return on investment for each channel or specific action, something that traditional marketing can rarely do with precision.
• Similarity: both approaches share the goal of better connecting with the consumer and maximizing results, but the path to achieving it is very different: one relies on experience, the other on applied science.

Solutions and tools that make up Marketing Science

El Marketing Science se apoya en un conjunto de soluciones integradas que permiten transformar grandes volúmenes de datos en decisiones accionables. Entre las principales herramientas y metodologías se encuentran:

• Marketing Mix Modeling (MMM): an econometric model that quantifies the impact of each marketing channel or tactic on sales. It allows for optimizing advertising investment and estimating the marginal ROI of each medium.
• Geo Experimentation (GeoLift): a statistical technique that uses geographic segmentation to test the causal effect of campaigns, eliminating biases and measuring true incrementality without relying on cookies.
• Media Audit: analysis of advertising performance on platforms such as Meta and Google, comparing current campaigns with industry best practices to identify immediate improvement opportunities.
• Creative Analysis: a tool that quantitatively evaluates the performance of advertising assets (formats, messaging, visual structures) and their impact on key KPIs, such as ROAS or engagement.
• Omnichannel data centralization (Data Collection): integrating all data sources into a single platform to provide a unified view of what’s happening at every consumer touchpoint (social media, e-commerce, apps, CRM, etc.).
• Generating insights with artificial intelligence: using AI and machine learning models to identify patterns, predict behaviors, and generate automated recommendations for decision-making.
• Attribution analysis and brand health: techniques that combine traditional metrics with advanced analytics to understand both the direct impact and the long-term effect of marketing actions.

These tools don’t work in isolation. Together, they enable the construction of a comprehensive and dynamic view of the marketing ecosystem, aligning strategy, creativity, media, and results under a single language: that of data.

Why is it important in the digital marketing era?

Data volume has skyrocketed by 230% since 2020, but 56% of professionals lack the time and tools to analyze it efficiently.

Marketing Science solves this problem by:

• Automate data analysis.
• Identify growth drivers
• Optimize advertising investment
• Reduce budget waste

Additionally, tools such as artificial intelligence and advanced attribution models make it possible to go beyond the “last click” and measure the true impact of each marketing action.

Real success stories: Marketing Science in Action

Whirlpool

Whirlpool measured the real impact of its channels with MMM, achieving an 8x ROI on TikTok thanks to a data-driven and creative strategy.

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Bunker, junto a TikTok, mide el impacto de campañas de Whirpool con Marketing Mix Modeling - Bunker DB

Rexona

Rexona used MMM to optimize its advertising investment and improve its Meta ROAS by 36%, prioritizing formats such as Reels and Carousels.

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Cómo Rexona optimizó su inversión en Paid Media con Marketing Mix Modeling de Bunker - Bunker DB

Liberty Latin America

Liberty partnered with Bunker DB to apply MMM, identifying a 15% media optimization and making decisions based on solid statistical evidence.

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Cómo Liberty identificó 15% de optimización con MMM - Bunker DB

Banco Galicia

Banco Galicia unified online and offline data with MMM, improving campaign efficiency and boosting customer acquisition.

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Galicia transforma su estrategia publicitaria y marca el nuevo camino de los bancos - Bunker DB

Do you want to see how it works in action?

Schedule a free demo and discover it for yourself.