• A recent GiveDirectly poll of potential donors found
    • nearly half agreed that it’s a good idea to give $1000 to families in extreme poverty
    • but only 13% knew about GiveDirectly’s work 
    • and giving cash was the least popular way address extreme poverty
  • We could deliver more cash to people in need if more high-earners were
    • aware of the opportunity to give through GiveDirectly
    • disabused of the common myths around direct cash aid

In May, GiveDirectly ran a panel survey of 750 Americans who fit our common donor profile to better understand their familiarity and sentiments around direct cash. Below, we outline the most relevant findings and how they’ll inform our communications and marketing strategy. 

Note: we’ll continue to update this blog as we further analyze the survey results

Knowing what potential donors think about direct cash aid will improve our fundraising

GiveDirectly began building a dedicated fundraising team 7 years ago, and since then we’ve grown 

However, this success does not capture the potential of how much more we could be delivering to people in need. So to better understand the impression and awareness potential donors have about our work, we ran a survey. Below we break down the major takeaways. 

Our survey of high-earners found direct cash aid was the least popular way to help people in extreme poverty

80% of randomly selected respondents were at least somewhat aware of the issue of extreme poverty (Q1).

When asked what types of aid would most help those in extreme poverty, “direct cash assistance” was the least popular. When asked how helpful 9 types of aid would be, direct cash came in last. (Q2)

Similarly, when asked to rank 9 types of aid they’d be likely to donate to, only 16% of respondents put direct cash in the top 3 spots and 56% put it in the bottom 3 spots. (Q3)

About half of respondents thought GiveDirectly’s model was a good idea

46% agreed that “it’s a good idea to give $1,000 to families living in extreme poverty with no strings attached,” about half of which “strongly agreed.” (Q4)

31% of all respondents disagreed that GiveDirectly’s model was a good idea and 24% were neutral.

The most compelling benefit of direct giving was that it lets recipients meet their basic needs

Of those who agreed GiveDirectly’s model was a good idea, the most common unprompted benefits mentioned were that giving cash… 

  • helps meet basic needs (food, shelter, healthcare) – 58%
    • Ex. “clean water, shelter, clothing, education, medical care.”
  • can be life-changing (long-term benefit, escaping poverty) – 12%
    • Ex. “Families can invest the funds into long-term solutions to their situations”
  • helps because recipients know best what their needs are – 11%
    • Ex. “It lets recipients define their own needs.”
  • grants agency and dignity – 6%
    • Ex. “It gives them autonomy and dignity.”
  • helps the local economy – 2%
    • Ex. “Stronger economy, decreased social blight, increased empowerment and responsible citizenship”
  • is direct with no middlemen – 2%
    • Ex. “The money goes there directly”

The biggest concerns about direct giving were unwise spending, the need for training, and a lack of lasting impact

Of those who did not agree GiveDirectly’s model was a good idea (54%), the most common unprompted concerns mentioned were that cash recipients…

  • may spend the money unwisely – 30%
    • Ex. “Anyone could spend that money in a way that is not in their best interest. They could even do something illegal.”
  • need something else (training, education, resources) – 29%
    • Ex. “Families  living in extreme poverty would lack the education or financial knowledge to use it wisely” 
    • Ex. “They wouldn’t know what to do with it. It would be more beneficial to provide them with wells, seeds, farming equipment, clinics etc”
  • won’t be able to make lasting improvements – 19%
    • Ex. “$1000 to a family doesn’t sound like it will get anything done. It will help just for that very short time.”
  • should have rules on how they can spend their money (11%).
    • Ex. “There need to be stipulations on how its used”

Even those who “somewhat agreed” GiveDirectly’s model was a good idea (25%) shared these concerns, saying they felt recipients…

  • need something else (training, education, resources) – 14%
  • may spend the money unwisely – 10%
  • should have rules on how they can spend their money – 9%
  • won’t be able to make lasting improvement – 7%

Direct giving options like GiveDirectly are not widely known

When asked unprompted to list nonprofits that help people in extreme poverty, no one listed GiveDirectly or any other direct giving organization. The most common answers were UNICEF (22%), Red Cross (17%), and ‘can’t think of any’ (15%). (Q5)

Only 13% of respondents were familiar enough with GiveDirectly to correctly say what we do unprompted, and 1 in 5 of those said they had given through GiveDirectly before.

More people in poverty will be helped if we can make direct cash more widely known and disabuse more people of these concerns

The more high-income people favor direct giving, the more people in poverty will receive cash. Rather than being satisfied we’ve convinced some people, we should be striving to convince many more people.  Based on this survey, there are three clear ways to do this. 

Address the major common concerns about direct giving, not the minor ones 

We’ll orient more of our communications and marketing to address these most common concerns, that recipients…

  • may spend the money unwisely – 30%
  • need something else (training, education, resources) – 29%
  • won’t be able to make lasting improvements – 19%
  • should have rules on how they can spend their money – 11%

We’ll spend less time focusing on the least common concerns, that recipients may…

  • grow dependent or should work for the money – 6%
  • not receive the money due to fraud or theft – 5%
  • not have access to resources or opportunities to spend on — 3%
  • be put at risk by receiving a large sum of money – 2% 

We have a webpage on mythbusting that we’ll be updating based on these results – though are happy to report it helped unconditional cash make the big screen→   

Emphasize the diverse benefits of direct giving

Cash supporters clearly understand it will help people meet their basic needs as 58% mentioned it as a benefit. However, we can devote more of our marketing to the potentially overlooked benefits – that direct cash…

  • can be life-changing (long-term benefit, escaping poverty) – 12%
  • helps because recipients know best what their needs are – 11%
  • grants agency and dignity – 6%
  • helps the local economy – 2%
  • is direct with no middlemen – 2%

Grow awareness both with our core audience and new audiences

Our survey found 18% of people who knew what GiveDirectly does had donated. While self-reported and not vastly representative, it shows how important it is for more people to learn about our model. With an average one-time donation of $1,450, spreading the word could transform many more lives. We’re pursuing more mass-audience engagements with influencers, podcasters, and YouTubers. We’re also helping you share word-of-mouth by offering merch and tips

If you have ideas on what this survey data suggest we should be trying next, email us at [email protected].

Appendix 1: full responses to select questions

Q1: “Extreme poverty” is defined as living on less than $2.15 per day. Today, 700 million people live in extreme poverty, most of them in sub-Saharan Africa. How aware were you of this information before this survey?

Not at all aware19% (142)
A little aware27% (205)
Somewhat aware30% (225)
Very aware17% (125)
Extremely aware7% (53)

Q2: How helpful do you think the following types of aid would be for people living in extreme poverty?

Very or extremely helpful for extreme poor

  1. Water & sanitation access – 85%
  2. Clinics & medical access – 82%
  3. Food assistance – 80%
  4. Vaccines & disease prevention – 76%
  5. Education access – 74%
  6. Job & skills training – 71%
  7. Fertilizer & farm materials – 57%
  8. Giving them livestock – 50%
  9. Direct cash assistance – 41%

Somewhat, very, or extremely for extreme poor

  1. Water & sanitation access – 95%
  2. Food assistance – 95%
  3. Clinics & medical access – 94%
  4. Education access – 93%
  5. Vaccines & disease prevention – 92%
  6. Job & skills training – 92%
  7. Fertilizer & farm materials – 86%
  8. Giving them livestock – 83%
  9. Direct cash assistance – 73%

Q3: If you were to donate to help people living in extreme poverty, which type of aid would you support? Rank this list from most interested in supporting at the top to least interested in supporting at the bottom.

Ranked 1st, 2nd, or 3rd 

  1. Water & sanitation access – 64%
  2. Food assistance – 56%
  3. Clinics & medical access – 43%
  4. Vaccines & disease prevention – 34%
  5. Education access – 28%
  6. Job & skills training – 26%
  7. Direct cash assistance – 16%
  8. Giving livestock – 13.5%
  9. Fertilizer & farming materials – 11%

Ranked 7th, 8th, or 9th (of 9)

  1. Direct cash assistance – 56%
  2. Giving livestock – 46%
  3. Fertilizer & farming materials – 39%
  4. Job & skills training – 23%
  5. Vaccines & disease prevention – 18%
  6. Education access – 17%
  7. Clinics & medical access – 16%
  8. Food assistance – 9%
  9. Water & sanitation access – 9%

Q4: How much do you agree or disagree with the following statement: “It’s a good idea to give $1,000 to families living in extreme poverty with no strings attached.”

Strongly disagree13.5% (103)
Somewhat disagree17% (127)
Neither agree nor disagree23.5% (178)
Somewhat agree24.5% (184)
Strongly agree21% (158)

Q5: Which nonprofits or charities come to mind that help people living in extreme poverty? List as many as you can.

  1. UNICEF – 22%
  2. Red Cross – 17%
  3. None / cannot think of any – 15%
  4. Save the Children – 7%
  5. Care – 6%
  6. Salvation Army – 6%
  7. Oxfam – 6%
  8. World Vision – 4%
  9. Feed the Children – 4%
  10. United Way – 3%
  11. Doctors Without Borders – 3%
  12. Feeding America – 3%
  13. Habitat for Humanity – 2%
  14. Catholic Charities – 2%
  15. Gates Foundation – 1%

Appendix 2: survey information

Survey constraints

  • GiveDirectly used AYTM to survey potential donors, constraining the respondents to those who are…
    • living in major US metro areas
    • employed, earning over $100k a year
    • over 21 years old with a 4 year degree
  • This is based on the common profile of existing GiveDirectly donors who…
    • most commonly live in US metro areas 
    • give an average one-time gift of $1,450 (11x higher than the $128 average for international nonprofits)

Panel survey limitations

  • There are clear limitations to this type of panel survey:
    • Details like donation behavior or household income are self-reported, so could be wrong
    • It’s a self-selecting group of people interested in taking surveys for money
  • We chose this survey design given budget constraints. A randomly sampled, mixed-methodology approach is simply prohibitively expensive. Panel research balances accuracy with expense.
  • It’s important to not draw overly precise conclusions from this data set. Relative weights are likely to be found across repeated surveying, but precise statistics on, say, name recognition could vary significantly.

Demographic breakdown of the 750 survey respondents (AYTM’s choosing)

  • Donation behavior
    • 💸80% have donated to some charity or nonprofit in past 3 years. 
    • Of those who have donated in the past 3 years,
      • 💰half gave over $1000+ in charitable giving last year.
      • 🌍half donated to a nonprofit working outside the U.S.
  • Gender
    • ♂️M: 46% 
    • ♀️F: 54%
  • Age
    • 🧒17% – 22-34 y.o. 
    • 👨‍57% – 35-54 y.o. 
    • 👨‍🦳27% – 55+ y.o.
  • Political beliefs
    • 🫏36% Strongly or somewhat liberal/left 
    • 🐘32% Strongly or somewhat conservative/right 
    • 🎯26% Center, neither liberal nor conservative 
    • 🙅6% Apolitical 
  • Household Income
    • $100-$199k – 76%
    • $200k+ – 24%
  • Education
    • 🎓53% – 4 year university
    • 🎓🎓28% – Graduate school 
    • 🎓🩺 19% – Professional degree
  • Race
    • White 74%
      • Hispanic origin 11% 
    • Asian-American 15%
    • Black / African-American 11%
    • Other 4%
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