ABOUT THIS EPISODE
Bot traffic passed human traffic on the web this year. TIME decided to sell the bots ads. One month in, COO Mark Howard explains what advertisers are buying, why the AI seems to remember what it scrapes, and what Perplexity got wrong.
Pete Pachal talks with Mark Howard, chief operating officer of TIME, about agent ads: brand-verified facts, labeled as sponsored, placed on the machine-readable versions of TIME pages for the AI crawlers it allows in. They cover the infrastructure TIME built first (TollBit, ScalePost, a 70-agent allow list), the Mobian brand-gap method behind each campaign, the two measurement studies, the referrals-versus-citations puzzle, what an advertiser actually buys, whether the models can read the disclosure, the Perplexity dispute, what counts as a legitimate crawler, and why pay-per-crawl is both Howard's biggest worry and biggest hope. This is part one of a two-part look at ads for bots; part two is Oasy co-founder Choy Travers.
In this episode
- Why TIME chose to learn by doing instead of waiting for the market to settle
- The infrastructure underneath agent ads: TollBit, ScalePost, and a 70-agent allow list
- The markdown page built for machines, and what an agent ad actually is
- Which bots show up, and what they're there for
- The TIME100 Creators moment that made the case for the product
- Mobian's method: visibility, favorability, and accuracy across the major models
- Why TIME believes the agents remember what they scrape
- One month of data: causal lift and model impact over time
- What the advertiser is buying when there's no guaranteed placement
- Whether the models can read the sponsored label, and what they do with it
- The Perplexity dispute, and what OpenAI thinks
- What counts as a legitimate crawler
- Pay-per-crawl as both the biggest worry and the biggest hope
Guest: Mark Howard, Chief Operating Officer, TIME: LinkedIn | time.com
Watch the video version: https://www.youtube.com/watch?v=rjz-GEaibbI
Full post and transcript: mediacopilot.ai
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Music: "Favorite" by Alexander Nakarada, licensed under CC BY 4.0
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