Science

Develop data models, statistical hypotheses, and exploratory analyses in a simple, actionable way to improve the results of your media investment.

Discover the modules included on Science

Demonstrate the true impact of your marketing

With Marketing Mix (MMM), you can measure how much of your sales is explained by media investment and how much by external factors such as price, promotions, or seasonality. This advanced statistical model allows you to assign real credit to each channel, optimize budgets, and justify investments with scientific evidence. Unlike last-interaction reports, the MMM offers a multi-channel, cookie-agnostic view, adapted to the new era of digital privacy.

The result: smarter strategies, better allocated budgets, and decisions based on reliable data.

Marketing Audits: media and creative under the microscope

Audits are the foundation of more efficient marketing. Your team can comprehensively evaluate both media investment and creative performance. Why? Because media and creative are two sides of the same coin. Auditing the combination of both unlocks a marketing strategy that reduces waste, maximizes results, and builds executive confidence in your marketing decisions.

With a media audit, detect inefficiencies in media buying and your digital campaigns. Analyze audiences, costs, frequency, and configurations to identify budget leaks and maximize the ROI of every dollar invested.

With a creative audit, evaluate the real impact of each ad. Discover patterns of creative success and gain input for future evidence-based campaigns.

Measure the real impact of your campaigns with market experiments

With geoexperimentation, you can validate the effectiveness of your marketing actions through controlled tests in equivalent geographic regions. The platform automatically divides test and control zones, ensuring statistically significant results and clear attributable incremental metrics.

It works for both digital and traditional campaigns, allowing you to calculate the real increase in sales, traffic, or leads generated by your advertising investment. The value lies in having causal evidence, beyond correlation: scientifically demonstrating what works and what doesn't.

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Reference material

blog

blog

16 | 06 | 2025
The current challenge of measuring marketing: what can we do better?

In recent years, traditional attribution models have become less accurate. Privacy restrictions, the disappearance of cookies, and "last-click" models are no longer sufficient to understand how each marketing effort contributes to the bottom line. Main Pain Points Privacy and Individual Data: New regulations prevent individual user tracking, reducing the effectiveness of models that rely on cookies. In a more private world and less efficient cookies, attribution based on individual data loses statistical effectiveness in favor of anonymized aggregated data. Last-Click Attribution: Last-click attribution overvalues the last channel prior to a sale and underestimates the contributions of previous interactions (awareness, consideration, remarketing). Lack of incremental and holistic vision: Fragmented measurement fails to understand the true impact of each channel on the entire funnel or how external factors (promotions, economics, seasonality) affect results. Marketing Mix Modeling: Beyond Attribution Marketing Mix Modeling (MMM) is an analytical approach that uses statistical and econometric models to quantify the impact of multiple variables—such as paid and organic media, promotions, pricing, and seasonality—on business outcomes (sales, revenue, and leads). Why is it important today? In an environment where data is more limited but decisions must be more precise, MMM becomes an essential tool: It works without personal data: It operates on aggregated data, without the need for cookies or individual identifiers. It optimizes budgets: It allows reallocation of investment to channels with the highest marginal ROI. It offers a full-funnel view: It considers the entire marketing ecosystem, beyond the digital channel. In this way, MMM doesn't replace attribution models: it complements them. While attribution models (such as MTA) trace the path of an individual user, MMM measures the aggregate effect. Both models enhance each other when combined with experimentation (A/B testing or GeoLift). Una visión 360°: lo que el MMM realmente mide A diferencia de los modelos de atribución tradicionales, el MMM ofrece una comprensión integral de todos los factores que influyen en los resultados. Medios online: Tráfico pago, orgánico, redes sociales, influencers, email, podcasts. Medios offline: TV, radio, vía pública, prensa, eventos. Factores comerciales: Precios, promociones, descuentos, canales de distribución. Estacionalidad: Verano/invierno, días festivos, eventos clave. Variables macroeconómicas: Inflación, desempleo, tipo de cambio, clima, regulaciones. Este enfoque ayuda a responder una pregunta clave: ¿Qué parte de las ventas puede explicarse por nuestras acciones de marketing y qué parte por factores externos? ¿Cómo implementamos MMM en Bunker DB? Nuestra metodología combina precisión técnica y aplicabilidad real. Así trabajamos: Recolección y normalización de datos internos y externos. Unificamos toda la información necesaria —desde inversión en medios hasta variables macroeconómicas— asegurando coherencia estadística. Modelado econométrico y estimación de impacto. Aplicamos modelos iterativos para estimar cuánto aporta cada variable a las ventas, incluyendo el ROI marginal por canal. Curvas de saturación por medio. Identificamos puntos donde la inversión deja de ser eficiente y sugerimos realocaciones óptimas. Calibración con estudios de incrementalidad. Contrastamos el modelo con test reales para mejorar su precisión. Optimización del presupuesto. Evaluamos la diferencia entre el presupuesto original y el optimizado, mostrando claramente las ganancias posibles en ROAS. Impacto de negocio en casos reales No hablamos solo de teoría. Varias marcas en LatAm ya están usando MMM para transformar su estrategia: Telecomunicaciones: Para Liberty Latin America, desarrollamos un marketing mix modeling que incrementó en 15% su potencial de optimización. Lee más del caso en: Servicios financieros: Para cinco (5) marcas distintas, nuestros resultados revelaron que la implementación efectiva de MMM puede incrementar entre un 3% y un 15% las conversiones con el mismo presupuesto publicitario. Lee más del caso en: Estos resultados muestran el potencial del MMM para generar eficiencia real y tangible. Conclusión: un marketing más inteligente y basado en datos El Marketing Mix Modeling es una respuesta moderna a un contexto más complejo. Permite a las marcas medir con precisión, decidir con evidencia y optimizar con confianza. Una mejor medición vendrá de utilizar los modelos correctos, no los datos individuales.

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