💡
EA market testing (public)
  • Introduction/overview
    • Introduction & explanation
    • 👋Meet the team
    • 📕Content overview
    • Progress/goals (early 2023)
      • EAMT progress & results
      • Goals, trajectory, FAQs
  • 🤝Partners, contexts, trials
    • 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
    • The Life You Can Save (TLYCS)
      • Advisor signup (Portland)
    • Fundraisers & impact info.
      • ICRC - quick overview
      • CRS/DV: overview
      • 📖Posts and writings
    • University/city groups
    • Workplaces/orgs
    • Other partners
    • Related/relevant projects/orgs
  • 🪧Marketing & testing: opportunities, tools, tips
    • Testing Contexts: Overview
    • Implementing ads, messages, designs
      • Doing and funding ads
      • Video ads/Best-practice guidelines
      • Facebook
      • Targeted ad on FB, with variations: setup
    • Collecting outcome data
      • Facebook ads interface
        • Pivot tables
      • Google analytics interface
      • Google A/B, optimize interface
      • Reconciling FB/GA reports
      • Survey/marketing platforms
    • Trial reporting template
  • 🎨Research Design, methodology
    • Methods: Overview, resources
    • "Qualitative" design issues
    • Real-world assignment & inference
      • Geographic segmentation/blocked randomization
      • Difference in difference/'Time-based methods'
      • Facebook split-testing issues
    • Simple quant design issues
    • Adaptive design/sampling, reinforcement learning
    • 'Observational' studies: issues
    • Analysis: Statistical approaches
  • 🧮Profiling and segmentation project
    • Introduction, scoping work
    • Existing work/data
      • Surveys/Predicting EA interest
      • Awareness: RP, etc.
      • Kagan and Fitz survey
      • Longtermism attitudes/profiling
      • Animal welfare attitudes: profiling/surveying
      • Other data
    • Fehr/SOEP analysis... followup
      • Followup with Thomas Ptashnik
    • Further approaches in progress
      • Profiling 'existing traffic'
  • 📋(In)effective Altruistic choices: Review of theory and evidence
    • Introduction...
    • The challenge: drivers of effective/ineffective giving
      • How little we know...
    • Models, theories, psych. norms
    • Tools and trials: overview
      • Tools/interventions: principles
      • Outcomes: Effective gift/consider impact)
        • (Effectiveness information and its presentation)
        • (Outcome: Pledge, give substantially (& effectively))
          • (Moral duty (of well-off))
        • Give if you win/ conditional pledge
      • Academic Paper Ideas
  • 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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  • Strategic considerations
  • Scoping and considering the value of doing this

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  1. Profiling and segmentation project

Introduction, scoping work

PreviousAnalysis: Statistical approachesNextExisting work/data

Last updated 2 years ago

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Strategic considerations

Previous sections considered... 'How to get more people to care about '. 'How to get the "Einsteins" of the next generation interested in this.' And 'how do we introduce this to people?'

But, an equally-important concern may be... WHOM do we target? How do we do market profiling? Not just 'what do we present', but 'who do we present it to'

In this section, we cover the limited work that has been done on this, and the scope to do more.

Scoping and considering the value of doing this

Leander Rankwiler's recently (17 Feb 2023) did a scoping exercise for this. See . This work focuses on "the rationale, literature research, and data collection", and comes to relatively negative conclusions ("it's much less valuable to pursue than previously assumed"). This particularly reflects concerns that doing, publicly reporting, and acting on this research to 'target promising groups' may do some harm (see fold).

Downside risks (Rankwiler)
  • Risk of harming the diversity (of personalities) within EA, by targeting the "typical" EA personality.

  • "Risk of negative public perception of the method of using personality traits to find promising users (à la Cambridge Analytica)"

He also sees many sources of (statistical) bias in any feasible analysis.

In the sections below, we present and link recent and ongoing direct work that may also be relevant and informative.

🧮
"Detecting affinity for the ideas of effective altruism on social media"
leander_profiling_Project1_final.pdfDropbox
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