💡
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
Powered by GitBook
On this page
  • Organizations and 'do' initiatives
  • EA-related giving initiatives
  • Non or semi-EA initiatives
  • EA or 'effective giving' orgs working with foundations and wealthy donors
  • Research and information-gathering initiatives

Was this helpful?

Edit on GitHub
Export as PDF
  1. Partners, contexts, trials

Related/relevant projects/orgs

PreviousOther partnersNextTesting Contexts: Overview

Last updated 2 years ago

Was this helpful?

Note 7 Mar 2023: I just started this page, it is far from complete

Organizations and 'do' initiatives

: Including (new) EA-aligned marketing groups

EA-related giving initiatives

Non or semi-EA initiatives

EA or 'effective giving' orgs working with foundations and wealthy donors

Research and information-gathering initiatives

We are an academic collective and research non-profit, dedicated to providing public communication campaigns with cutting-edge research and rigorous tools for message development.

"Crowdsourcing" ... Recent research suggests that regular people can often be far more effective than experts at predicting which messages will best resonate with others in their community.

On Adaptive design/sampling, reinforcement learning...

-->

  • Efficient message search. We design research pipelines that allow campaigns to explore the large space of potential messages more efficiently, and to quickly zero-in on the most impactful messaging strategies. Our methodology is based on a combination of large-scale adaptive online survey RCTs, Bayesian machine learning and surrogate metrics.

Which links spreadsheet

Much of which is embedded into as well (which will have some further comments on the relevance, as well as organizations that are not-so-EA related, with discussion)

(a list of orgs in the 'EA effective giving' space; private gitbook atm)

- "The IiF wiki collects and presents evidence on the most successful approaches to motivating effective and impactful charitable giving, and promotes innovative research and its application." This precedes and is partially integrated into the current resource

The challenge is that the “space” of messages for campaigns to decide between is enormous — there are very many things a campaign could say and many different ways to say them. Unfortunately, research shows that relying on theory and expert guidance about “what works” when designing campaign messages is unlikely to be effective by itself, because “what works” is difficult to predict and can change dramatically across contexts (e.g., see , , , ).

🤝
THIS
THIS Airtable view
innovationsinfundraising.org
Rhetorical.org
[1]
[2]
[3]
[4]
Other marketing/implementation resources
Overview of effective giving organisations - EA Forum
Logo