How It Works
A platform that keeps getting smarter, making it easier for you to win audio.
The Veritonic platform has been ingesting audio assets from the biggest brands in the world — ads, branding elements, voiceovers, and more — for over six years. It analyzes their innate characteristics (like melody) and content components (like copy), records how they resonate with people, and compares them to other, similar assets in the platform.
Veritonic Machine Listening and Learning (MLAL™) is trained through years of taking each audio asset, extracting a number of specific features, and correlating them with Veritonic’s set of second-by-second human response data.
Assets get an instant predictive score to start.
The machine continues to learn by capturing the realtime emotional response, recall and purchase intent of the audiences you’re interested in. From the general population to any custom segment you wish to create, the live human response data helps to validate the prediction and ensures that the platform is always getting smarter.
Veritonic Audio Score is the first rating standard for audio creative. It incorporates all of the above learning into one, simple metric, making it easy for you to understand the overall value of a particular asset (audio ad, voiceover, sonic brand element, music, script and more) and compare it to others in the market.
That clear guidance empowers you to make more informed decisions about how to optimize audio creative — in less time — and ensure that it resonates most effectively with customers.
We’ve made ratings even more comprehensive and meaningful by evolving our methodology to incorporate more data points and, with Machine Listening and Learning, producing smarter insights.
Each audio file’s Veritonic Audio Score builds in its individual measure for:
Most importantly, context is now incorporated into every metric, making it easier for you to compare an audio asset’s relative power to achieve your goal.
Since each creative is tagged for a range of characteristics, you can weigh assets against numerous benchmarks — from industry sector to competitive set — for a practical sense of their relative value.
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