Stop Rewind Play

Suze Cooper · Business

YAPP has Smart‑Skip data for 8 episodes of Stop Rewind Play. Recent episodes average 0.3 minutes of ads per 8.6‑minute episode.

2.2ad minutes per hourof runtime
3.7%of runtimeis advertising
1.1ad breaksper episode, on average
8episodesmeasured by YAPP

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Recent episodes

Ad time detected in the 8 most recent episodes of Stop Rewind Play that YAPP has processed.
Episode Published Length Ad time Breaks
🎧 Wondery’s Shake-Up, Sonic Branding at the Airport, and Pixel Buds Go Premium 5:38 0:13 1
🎧 What podcasters can learn from flash briefings (remember them?) 6:54 0:09 1
🎧 Does Your Audience Even Want a Podcast? 10:12 0:17 1
🎧 The Hidden Cost of Personalised Podcast Feeds 7:26 0:14 1
🎧 From Page to Podcast - Turning Articles Into Audio 8:54 0:21 1
🎧 The Smart Way to Repurpose Written Work into a Podcast 9:42 0:21 1
🎧 How much bad audio will listeners really forgive? 12:35 0:46 2
What your podcast is telling listeners - before you say a word 7:34 0:13 1

Ad load varies by listener. Most podcast advertising is dynamically inserted, so figures reflect ad load as observed by YAPP's processing pipeline at the time each episode was fetched, not what any individual listener hears. Methodology

Listening to Stop Rewind Play with YAPP

Stop Rewind Play carries a light ad load — typically a single break per episode. Across the episodes we have processed, that comes to about 0.3 minutes per episode, or 2.2 minutes for every hour of listening.

YAPP maps each episode before you play it, so you get the show and not the rest of it. Because the ads are stitched in per listener, YAPP matches what you are actually hearing rather than replaying a fixed set of timestamps.

How these numbers are measured

YAPP transcribes each episode, classifies advertising segments, and refines their boundaries using audio fingerprinting. Figures cover the 8 episodes of this show that YAPP has processed. Because most podcast ads are dynamically inserted and vary by listener, these figures reflect what our pipeline observed rather than what every listener hears. Full methodology

Boundaries for 50% of detected segments were refined by audio fingerprinting; the rest rest on transcript timing and are less precise.

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