What TIME Learned From a Month of Selling Ads to Bots, With COO Mark Howard

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 settleThe infrastructure underneath agent ads: TollBit, ScalePost, and a 70-agent allow listThe markdown page built for machines, and what an agent ad actually isWhich bots show up, and what they're there forThe TIME100 Creators moment that made the case for the productMobian's method: visibility, favorability, and accuracy across the major modelsWhy TIME believes the agents remember what they scrapeOne month of data: causal lift and model impact over timeWhat the advertiser is buying when there's no guaranteed placementWhether the models can read the sponsored label, and what they do with itThe Perplexity dispute, and what OpenAI thinksWhat counts as a legitimate crawlerPay-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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