Podscribe is excited to announce the launch of automated ad scoring!
Using ChatGPT, Podscribe automatically assigns each ad read a score from 1 to 10, based on the degree to which the host personally endorses the product. If they say they used the product, how it benefited them in detail, and emphatically recommend it to listeners — high score! If they don’t mention that they used the product, the score will be lower.
This real-time scoring system lets advertisers gauge their read quality, discern future improvements, and see at a high level how effectively hosts talk about their product and brand.
The Need for Automated Endorsement Scoring
Host read endorsements are an incredibly effective performance driver for DR advertising.
Listeners often hear a genuine personal endorsement of a product like it came from a trusted friend or respected authority source.
Before now, confirming hosts gave a personal endorsement across dozens or hundreds of ads per week was a big headache! Advertisers, publishers, networks, and agencies score endorsements manually with teams of people listening and grading the ad read one-off.
No longer! Thanks to Podscribe, podcast advertisers can see the quality of their host-read endorsements in one consolidated dashboard, automated in real time.
How Podscribe’s Automated Endorsement Scoring Works
Using ChatGPT-powered Podscribe lets you easily assess how well a host endorsed a product by analyzing these factors:
1. Podscribe identifies if the ad is a host read or producer read using ChatGPT. Helps explain how personalized and related to the show the ad read is. 2. Podscribe identifies if this is a Direct Response or awareness ad based on whether the ad contains clear CTAs, URLs, or other promotional language. 3. Podscribe grades the ad read based on how well and clearly the host endorsed the product and brand. 4. Podscribe provides reasoning for the score and specific recommendations on how it could be improved including examples.
Get in real-time:
- Transcribed Ad Read
- Ad Read Score
- Score Justification
- Personalized Recommendations
What’s Next?
This is far from complete. The tool only answers the simple question of did the host talk about their personal experience with the product.
This question does not apply to all reads, and many questions can be used to evaluate the quality of a read.
To improve this, we will add additional questions to evaluate ads, and even let clients pass in their own custom questions to score their ads on.
Podscribe has been evaluating length, CTA, placement and other more cut-and-dry qualities of an ad, but this is our first automated qualitative evaluation.
We look forward to helping brands, agencies and publishers get faster, more comprehensive and automated of all their ads!
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