💡
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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  1. Partners, contexts, trials

The Life You Can Save (TLYCS)

Leads: Bilal Siddiqi, Neela Saldhana; Other partner contact: Jon Behar (Giving Games)

PreviousPreregistration: OftW pre-GTNextAdvisor signup (Portland)

Last updated 2 years ago

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We have completed various trials in conjunction with , the most recent being theAdvisor signup (Portland) city-level YouTube test. There are a number of additional proposed trials and tests, however, at the moment these considerations are limited to the private Gitbook.

Note that in the past TLYCS has worked with the Graduate Policy Workshop School of Public and International Affairs at Princeton University, who produced the report embedded below.

Quick takeaways from the "Princeton" report

(From 'summary'... the report authors' takes are given except where italicized)

  • 5 key principles: choice architecture, social norms, empathy, overhead cost aversion, and anchoring

Factual:

  • TLYCS demographics are predictable (White, Male, tech...)

  • Donations cluster at the end of the tax year

Pages and promotion

  • Social media channel is promising

  • The "Best charities" page underperforms: there is a high bounce rate

    • DR: Maybe because Givewell etc do better at this?

  • "Visual presentation of charities does have an effect

    • DR: Not clear how this is causally identified

  • Ran "social media tests' they claim are underpowered.

    • DR: but these could be analyzed with Bayesian methods for actionable insights

  • They suggest simplified presentation/navigation, and a 'decision tree quiz' to reduce cognitive load

🤝
The Life You Can Save
'Behavioral Insights to End Global Poverty'