More Than Data

Dive-In and Case Study: A Data Scientist Sitting Next to a Media Planner

Feb 28, 2025By More Than Data
More Than Data

Bridging Media Planning and Data Science

This article is a follow-up to "A Data Scientist Sitting Next to a Media Planner", diving deeper into how these two roles collaborate to enhance media planning efficiency and productivity. By leveraging data-driven insights, media planners can make smarter, more informed decisions, bridging gaps in traditional media planning approaches.

The Role of Data in TV Programmatic Trading

A prime example of this collaboration is Channel 9’s TV programmatic trading and buying platform. Media planners rely heavily on this system to plan, justify, and optimize TV ad placements. Channel 9 has developed an internal system that captures detailed TV ad response, performance, and audience reach data, offering insights such as:

  • Program Genre: Movies, news, drama, etc.
  • TV Stations: 9GO, 9Life, and others
  • Ad Duration: 15s, 30s
  • Timing & Placement: Specific broadcast times, session placement, number of breaks
  • Audience Reach: Target audience rate points
  • Spend: Actual paid vs. bonus placements

While this programmatic buying platform simplifies media planning, two key challenges remain:

  • Limited Access for Media Planners: Media planners cannot directly interact with the platform; instead, they must email or call a Channel 9 customer relationship manager to launch campaigns and request ad placements.
  • Lack of Attribution to Business Growth: While TV spot data is well-labeled and tracked, there’s no direct link between individual TV ads and key business performance metrics like brand growth and product sales.

Due to these gaps, media planners face uncertainty in identifying which TV tactics drive real business growth and how to optimize future campaigns effectively.

The Role of Data Science: MMM and TV Attribution Modeling

This is where a data scientist can transform media planning. By developing a Marketing Mix Modeling (MMM) and TV Attribution Model, data scientists can track the impact of each TV spot on business KPIs. Establishing a clear linkage between TV ads and final business outcomes allows media planners to:

  • Quantify ad effectiveness and optimize future investments.
  • Eliminate uncertainty in campaign performance measurement.
  • Refine media strategies based on data-driven insights rather than assumptions.

Predictive Modeling & Scenario Testing

Using data from Channel 9’s programmatic platform, data scientists can design predictive models that empower media planners with actionable insights. This system enables planners to:

  • Configure campaign settings based on genre, timing, spend, and audience reach.
  • Predict campaign outcomes before investment, allowing for pre-campaign scenario testing.
  • Optimize media planning in real time, providing foresight into how TV spots will perform before actual execution.

Even before a TV plan is submitted, media planners gain full visibility into expected results, transforming media buying into a proactive, rather than reactive, process.

The Evolution of Data-Driven Media Planning

This TV planning system was originally built for a media agency and has been in continuous operation for six years as of 2025. Although the data scientist and media planner who developed it have since moved on, their intellectual property and system remain in active use, driving business growth.

And where is that data scientist now? The data scientist co-founded More Than Data—a company dedicated to helping media planners and agencies across the industry. If you're looking to elevate your media planning with advanced data-driven solutions, reach out to us today. We are More Than Data, and we are here to help!