DIY MMM

Silverlabs offers a unique service: “Do It Yourself” Marketing Mix Modeling (MMM). Instead of relying on expensive external vendors or SaaS tools (“black boxes”), Silverlabs helps advertisers to:

  • Take Ownership: Internal data teams (econometricians/data scientists) are trained to build attribution and MMM models themselves in Python.
  • Transparency (Code Sharing): Silverlabs shares all developed code. There is no ‘black box’; the client understands exactly how ROI/ROAS is calculated.
  • Cost Savings: No expensive licenses or vendor lock-in with parties like Objective Platform, Kantar, or Gain Theory.
  • Cultural Change: The focus is not just on the model, but on creating a ‘test & learn’ culture where marketers conduct experiments to feed and validate the model.

2. Market Context & Challenges (Why Now?) We address the following urgencies in the current market:

  • The End of Cookies: Due to privacy legislation (GDPR/iOS14) and the disappearance of third-party cookies, traditional attribution models (Multi-Touch Attribution) no longer work effectively. Marketers are flying blind.
  • Black Box Frustration: Many agencies provide reports without the client understanding how the numbers are derived. This creates distrust with the CFO.
  • Efficiency vs. Effectiveness: Many companies focus too much on short-term efficiency (clicks, cheap leads) and lose sight of long-term profitability (brand building). MMM helps restore this balance.
  • The Experimentation Gap: Modeling alone is not enough. A model only truly learns when there is variance in the data. Companies that do not actively experiment (e.g., ‘geo-lift tests’ or media blackouts) do not get reliable predictions.

The Ideal Client Profile

Our services are most relevant for companies meeting these criteria:

  • Media Budget: Estimated > €1,000,000 per year (characterized by TV commercials, large outdoor campaigns, and a heavy digital presence).
  • Internal Capacity: The company likely already has a Data Science team, BI specialists, or Econometricians (or has vacancies for these roles).
  • Sector: Retail, E-commerce, Finance, Telco, FMCG, Automotive (sectors with significant data, knowledge and media spend).

In this program we will coach your teams toward datadriven marketing. In our experience, Data Scientists can not perform Marketing Mix Modeling by themselves. Knowledge about marketing, media metrics, campaign specifics, relevant hypothesis and variables need to be trained first. Also, a solid KPI framework highlighting the most important KPI’s and metrics in your consumer funnel is essential. This KPI framework will guide the measurement setup and methodology of your company. We will perform a gap analysis to see what data points are missing for predictive modeling. Next we will train your data team to build Marketing Mix Models on the job, in order to predict future sales and make a decomposition of the media ROI’s. The teams will work in their own environment on code that will be owned by your company after our program ends. No strings attached. No black boxes. No hidden fees. We will be brutally honest in the process about feasibility, insights and interpretations. Let’s get in touch!