💡
EA market testing (public)
  • Introduction/overview
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      • EAMT progress & results
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    • Introduction
    • Giving What We Can
      • Pledge page (options trial)
      • Giving guides - Facebook
      • Message Test (Feb 2022)
      • YouTube Remarketing
    • One For the World (OftW)
      • Pre-giving-tues. email A/B
        • Preregistration: OftW pre-GT
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      • Facebook
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      • Facebook ads interface
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      • Profiling 'existing traffic'
  • 📋(In)effective Altruistic choices: Review of theory and evidence
    • Introduction...
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      • How little we know...
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    • Tools and trials: overview
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      • Outcomes: Effective gift/consider impact)
        • (Effectiveness information and its presentation)
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          • (Moral duty (of well-off))
        • Give if you win/ conditional pledge
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  • Appendix
    • How this 'gitbook' works
      • Other tech
    • Literature: animal advocacy messaging
    • Charity ratings, rankings, messages
    • "A large-scale online experiment" (participants-aware)
  • Innovationsinfundraising.org
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  • YouTube Remarketing
  • Understanding assignment, proposing experimental design @Joshua Lewis’s questions:
  • Results summary (Early, JS Winchell; may need update)

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  1. Partners, contexts, trials
  2. Giving What We Can

YouTube Remarketing

GWWC youtube remarketing campaign (trial)

PreviousMessage Test (Feb 2022)NextOne For the World (OftW)

Last updated 2 years ago

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See also the cross-organization (=placeholder for now) and the tips on Doing and funding ads

YouTube Remarketing

July 20, 2021: GWWC launched a YouTube remarketing campaign. That means that when someone goes to the GWWC website, leaves, and then goes to YouTube we show them one of the following videos:

Algorithm decides which video to present to people.

Understanding assignment, proposing experimental design ’s questions:

Q: Is each video assigned to a different situation or are videos randomly chosen to be displayed? If the latter, you could randomize videos by location and see if the different videos were more or less effective. Alternatively, just randomizing the whole campaign seems like a good idea to me....

A: Videos are selected based on the likelihood of the user watching >30 seconds (by the algorithm) ... randomization by individual will be hard because users don't click and act right away. Instead I think we have to randomize by geography

Results summary (Early, JS Winchell; may need update)

Most important takeaway: It costs $1 to get a website visitor to watch 1h of your videos! High level metrics

  • Cost: $205

  • Views: 6,071 (a view is when a user chooses to watch >30s of an ad)

  • Total watch time: 223 hours (~$1/h)

  • Unique viewers: 4,937 (this is an estimate)

  • Average impressions per user: 5.8

  • View rate: 20% (20% of the time people choose to watch more than 30s)

  • CTR: 0.37%

  • Average CPC: $1.83

  • Conversions (users spending >30s on the website): 2

  • Thinking: 'This is not a good tactic for driving site traffic or donations (although we could optimize for this instead if we wanted)'

Interesting observations\

  1. Efficiency has significantly improved over 3 weeks

  • Cost per view has gone down from $0.05 per >30s view to $0.02 per >30s view

  • Views have increased 75% without increasing budget (from 220/day to start to 386 yesterday)

  • You can see this data by video if you are interested to control for video length

3. Your best video had a view rate (% of time people choose to watch >30s) twice as good as your worst video 4. You can see view rate by age, gender, and device in the "Analytics" tab

Possible next steps

  • Could add "similar audiences" which is when we let Google use machine learning to find people similar to your website visitors and also show ads to them

  • Could walk David Reinstein and Joshua Lewis through the UI so they can get a sense of the metrics/reporting available and how it could be used for research

2. 10% of the time people watched the full video! \

E.g., 5% of people chose to watch the entire 13 minutes of _

For the , older people and men were more likely to choose to continue watching

🤝
notes on advertising, google, youtube, etc
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@Joshua Lewis
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