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Sept 6, 2017
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Intro
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BuzzFeed are opening up programmatic display.
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They are using Facebook & Google.
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Why not estimate the incremental gain they're likely to see.
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As they race towards an IPO it's an interesting datapoint.
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Source: www.businessinsider.com/buzzfeed-just-sent-out-a-message-to-the-digital-publishing-business-2017-8
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Assumptions in my models
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1 impression per page view BUT 4.86 avg pageviews/session. Which I think should account for the infinite scroll.
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Pageviews source: https://www.similarweb.com/website/buzzfeed.com#overview
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100% fill rates. Google + FB should have an ad for pretty much everyone.
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Relied on Quantcast + SimilarWeb data.
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Global device breakdowns mirror the US data Quantcast supplies.
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Effect of adblocking, data here: https://www.emarketer.com/Article/eMarketer-Scales-Back-Estimates-of-Ad-Blocking-US/1015243
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Quantcast data used from here: https://www.quantcast.com/buzzfeed.com?qcLocale=en_US
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US Mobile vs Desktop, 71.6M mobile, 16.5M desktop.
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*For global, assume same desktop/mobile ratio as US.
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Improvements
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Credible substantiated ranges on CPMs.
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Assumptions on Google vs FB CPM yields and a breakout between them.
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Tidying up, the two models aren't the same structure, as I evolved them.
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CPM suggestion, to look at high end of entertainment comps.
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Header Bidding vs JS alternative scenarios.
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Adjust model so you can tweak the variables to see the impact.
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Does Quantcast include in-app viewership or not? | TBC, BuzzFeed referencing Quantcast data suggests maybe so. https://www.buzzfeed.com/advertise
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Including a Video model.
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Other Models
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Simple model just looks at CPMs vs Geography.
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Advanced model improves it by providing a ranges based on device CPMs and exploring effects of adblocking.
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Contributors
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Kicked off by Ben Young @bwagy
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Various contributors, Matthew McIntyre @mjpmcintyre
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