If Match.com can predict who we should date using behavioral algorithms...
Why can't similar tech predict where we should allocate ad budgets?
Having conducted countless consumer focus groups, I can tell you they are both quite expensive and often significantly flawed... and flawed consumer data throws off your entire marketing plan from creative execution to media placement. So when we set out to create our Podcast Optimizer, it was with the promise that it had to produce clear, accurate, actionable marketing data.
Here's what our shrinks and data geeks came up with...
To keep it simple, we limited our Podcast Optimizer to just 10 questions. In marketing terms, 10 data points is ok, but not statistically significant. So, we focused on 10 behaviorally essential questions that marketers could answer about their consumers. Next, our platform amplifies the responses and aligns them with known data so each consumer profile becomes statistically meaningful. In addition to traditional demographics, here are a some of the directional findings that help direct where your media should be placed.
• Personality traits • Behavioral tendencies • Social alignment
• Income demo • Political alignment • Parental involvement
• Education • Leisure activities
Now we simply play matchmaker within our database of audiences to place your campaign on platforms and programs with the highest probability of success.
Adam Carolla, podcast partner
There are 115,000+ podcasts...
Our Podcast Optimizer reveals the podcasts your consumers download most frequently