Mechanical pencil laying on sheet of paper with chart comparing various options.

Embracing the Test: How to Make a Pilot Campaign Pay Off

If you are on the agency or ad tech side, you are familiar with the “pilot campaign.” We’ve all gotten requests to test the waters with our products and services before engaging in a full campaign or longer term commitment. Marketers often request tests as a means to compare vendors or to try out new technologies and media they view as unproven. The pilot is a necessary step, but without proper planning, it will yield results that muddy the waters on the best ways to move forward or maximize KPIs. Frequently, the proposed campaign length or spend allocation is too light to evaluate significance, or too little attention is given to defining what the key metrics of success will be.

Running a test that is not well thought out, too small, or lacking clear goals is an inefficient use of time, energy and dollars. It’s a waste for the marketer, agency and supplier. So, how do you run a test that is worth everybody’s time and resources? Perhaps the best way is to start by recognizing that pilots are an investment in a learning opportunity and not just a box to check. Additionally, creating a truly educational and beneficial pilot requires upfront investment—nothing ventured, nothing gained for anyone. Read the full post on The Makegood

Close up image of color pencils.

The Key to Programmatic Performance: Optimize Your Creative

Modern ad technology, data science and artificial intelligence allow us to constantly improve targeting and optimization. However, it’s fascinating how rarely, even in this age of data science, we use our analytic prowess to inform and optimize the creative we serve.

We know that creative factors into performance, And we know that we cannot expect automated systems alone to correct and achieve what should be our top priorities: fostering engagement and eliminating waste. But we are missing clear methods and strategies for using data to make our creative better—more personalized, relevant and effective.

After all, creative is at the very core of how consumers perceive personalization—it’s what engages us, or falls flat, based on strength and appropriateness of images, copy and interactivity.  Well-made ads served thoughtlessly to the wrong person and poorly crafted ads served to the right person result in the same things: lack of engagement and waste.  Read the full post on The Makegood

image of brain and various drawings of tables to represent learning from digital advertising campaigns.

All Learning is Not Created Equal: How Predictive Programmatic is Bypassing Traditional Digital Learning

The media industry celebrates and thanks digital for getting us quicker on our feet. Digital always has allowed us to measure, track, learn, optimize, and improve upon our own best efforts, well beyond what traditional ever could. We’ve long appreciated this contrast, with the improved capacity for learning being key. But, considering the advancements within digital itself—the growth of programmatic and the move toward machine learning—even typical digital methods are starting to feel “traditional.” Thanks to more powerful computing systems and science, there is so much more you can learn from a predictive programmatic campaign than you can from a traditional digital campaign. But, what’s the difference? Read the full post on The Makegood