Testing Marketing Models with Tried-and-True Experimentation

It’s no secret that how people consume media has changed drastically over the last 20 years as more and more internet connected devices come online. Add on the evolving ways people can transact with businesses, and you have a modern-day marketing reality that is far more complex than it has every been in history. 

A direct result of this is the emergence of statistical models as a staple to quantify and evaluate marketing performance. When deployed correctly, they can be used to inform decisions, forecast potential outcomes, and help justify marketing investments. But even the best models are not flawless. They require maintenance, calibration, and above all, testing. At Media Culture, we believe all measurement models should earn their keep, and the best way to ensure that is through tried-and-true experimentation.

Why testing matters

It is not uncommon for marketing models to be deployed and then left untouched, treated as finished tools that make life better and remain reliable in perpetuity. But customer behavior evolves, channel performance fluctuates, and external factors influencing business are in constant motion. When models aren’t tested regularly, they risk drifting from reality and could lead teams down misinformed paths.

Testing and validation provide marketers with confidence that a model remains aligned with the business it’s meant to represent, even if the outcome requires no change be made.

proven techniques

Whether you’re a do-it-yourself business or one who chooses to use a measurement partner, every model should be tested through structured experimentation. Here are two tried-and-true methods:

Matched Market Testing

Deploy your marketing campaign in carefully selected test markets and pair them with control markets selected with equal care. It is best practice to test in at least 3 markets with reasonable geographic separation and a balanced population of your target audience.  By analyzing the differences in performance, you can isolate the marketing impact and compare it to your model’s predictions.

Audience Split Testing

Segment your audience into test and control groups. Run a campaign for your brand with the test group and compare their visit and conversion metrics with the unexposed control group. If the lift aligns with your model’s predictions, it’s a good sign your model is functioning properly. This approach is generally most effective within digital channels given their precise targeting capability.

Adopt a schedule

Testing shouldn’t be a one-time event. It is recommended that a testing schedule be established for any new or existing model used for measuring marketing impact. The appropriate cadence will vary from one business to another but should generally be done once every year. This will put you in a strong position to catch issues early and ensures your model remains an asset, not a liability.

key takeaways

For marketing and finance leaders looking to bring more rigor to their measurement strategies, here are a few key steps:

• Schedule Testing into Your Roadmap: Make validation a recurring calendar event. Don't wait for a falloff in performance to check your model.
• Include Stakeholders Early: Involve finance and analytics leaders in the test process as you see fit. Communication and collaboration can offer insight into the expectations held by other stakeholders and increase trust in outcomes.
• Clearly Define Success: Before designing and executing a test, clearly define what constitutes an acceptable and unacceptable outcome. This will help ensure compatibility of your test design and analysis.

Final Thoughts

Measurement models are only as good as their ability to inform sound decisions. At Media Culture, we know that confidence in data comes not from blind faith, but from intentional testing and refinement. When businesses test their models with discipline and regularity, they can trust their measurement and invest with confidence.

If you're ready to bring rigor and reliability to your marketing measurement, let’s talk. Media Culture can help you implement a strategy that combines sound modeling with strategic experimentation for results you can count on.