Podcast and Streaming Media

There are roughly 500,000 podcasts in the U.S.
Which 100 do your customer’s download most often

If Match.Com Can Predict Who We

should date using behavioral algorithms...

Why can’t similar tech predict where we should allocate ad budgets? Now it can.

How well do you know your customer?

Having conducted countless consumer focus groups, I can tell you they are often significantly flawed... and flawed consumer data throws your entire campaign from creative to 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... and it does.

Matching Consumer Personality Type to Podcast Content

We start by identifying your consumer’s personality type and match that to the podcast content that appeals most to your customer's personality. This is is far more efficient than myopic focus on downloads and CPM

The Download Myth and Why it Leads to Failed Campaigns

Download stats are often wildly inaccurate and inflated
One listener downloading to multiple devices throws numbers off
Not every download is opened or listened to much less completed
Podcasters (rep firms) claiming they have clear listener data - don't!

Bigger is Not Necessarily Better

We focus on matching your customers to CONTENT vs. DOWNLOADS
50K-150K downloads vs. 150K-1M often offer more loyal and focused listeners
Fewer downloads often offer greater podcaster authenticity and cooperation (endorsements)
Pre and post roll should be viewed as marginally important --
Authentic, natural MIDROLL endorsements drive ROI
Extension across podcaster’s social channels

Now we simply play matchmaker within our database of audiences and podcasters to place your
campaign on platforms and programs with the highest probability of success.