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The Effect of Social Information on Giving from Lapsed Donors: Evidence from a Field Experiment

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Abstract

Using data from an experiment carried out by a large nonprofit organization, this paper finds that lapsed donors who received a solicitation letter referencing a relatively high donation made by another donor (high social information) were more generous in giving, but overall less likely to make a donation, relative to the baseline (low social information) group. After using the propensity score matching to correct for pretreatment differences in the two experimental groups, the estimated effect of high social information on the average donation amount is an increase of $14.95 (45 %). However, high social information is also found to reduce the probability a lapsed donor will give by 4.1 %. Thus, high social information can have potentially offsetting effects when applied to lapsed donors. Nonprofits should consider this trade-off when employing social information fundraising techniques to solicit donations from lapsed donors.

Résumé

À l’aide des données obtenues dans le cadre d’une expérience réalisée par une grande organisation à but non lucratif, cet article constate que les anciens donateurs ayant reçu une lettre de sollicitation mentionnant un don assez élevé réalisé par un autre donateur (informations sociales élevées) étaient plus généreux lorsqu’ils faisaient des dons, mais dans l’ensemble moins susceptibles d’en faire par rapport au groupe de référence (informations sociales faibles). Après avoir utilisé le score de propension correspondant pour corriger les différences de traitement préalable dans les deux groupes, l’effet estimé des informations sociales élevées sur le montant moyen des dons est en hausse de 14,95 $ (45 %). Toutefois, l’on découvre également que les informations sociales élevées réduisent la probabilité de don d’un ancien donneur de 4,1 %. Ainsi, les informations sociales élevées peuvent avoir d’éventuels effets compensatoires lorsqu’elles sont appliquées aux anciens donateurs. Les organismes à but non lucratif devraient envisager ce compromis lorsqu’ils utilisent des techniques de collecte de fonds d’informations sociales pour solliciter les dons d’anciens donateurs.

Zusammenfassung

Unter Verwendung der Daten aus einem Experiment einer großen Non-Profit-Organisation zeigt dieser Beitrag, dass ehemalige Spender, die einen schriftlichen Spendenaufruf erhielten, in dem auf eine relativ große Spende eines anderen Spenders verwiesen wurde (hohe soziale Information), großzügigere Spenden leisteten, die Wahrscheinlichkeit einer Spende jedoch insgesamt im Verhältnis zur Basislinie-Gruppe (niedrige soziale Information) geringer war. Nach Anwendung des Propensity Score Matching zur Korrektur von Pre-Treatment-Differenzen in den beiden Experimentgruppen entspricht der geschätzte Effekt hoher sozialer Informationen auf den durchschnittlichen Spendenbetrag einem Anstieg von 14,95 USD (45 %). Allerdings zeigt sich auch, dass hohe soziale Informationen die Wahrscheinlichkeit, dass ein ehemaliger Spender eine Spende leistet, gleichzeitig um 4,1 % reduzieren. Folglich können hohe soziale Informationen möglicherweise kompensierende Effekte haben, wenn sie ehemaligen Spendern überlassen werden. Gemeinnützige Organisationen sollten diesen Zielkonflikt berücksichtigen, wenn sie soziale Informationen als Mittel zur Spendensammlung bei ehemaligen Spendern einsetzen.

Resumen

Utilizando datos de un experimento llevado a cabo por una gran organización sin ánimo de lucro, el presente documento encuentra que los ex donantes que recibieron una carta de solicitud haciendo referencia a un donativo relativamente elevado realizado por otro donante (información social elevada) fueron más generosos dando, pero en general menos probables de realizar un donativo, con relación al grupo de base (información social baja). Después de utilizar la nivelación del grado de propensión para corregir las diferencias previas al tratamiento en los dos grupos experimentales, el efecto estimado de la información social elevada sobre el importe promedio del donativo es un aumento de 14,95 $ (45 %). Sin embargo, también se encontró que la información social elevada reduce la probabilidad de que un ex donante vuelva a dar en un 4,1 %. De este modo, la información social elevada puede tener efectos potencialmente compensatorios cuando se aplica a ex donantes. Las organizaciones sin ánimo de lucro deben considerar este compromiso cuando empleen técnicas de recaudación de fondos de información social para solicitar donativos de ex donantes.

通过查阅大量非盈利组织的试验数据,本文发现对于失效捐赠人来说,如果收到的宣传信引用了另一个捐赠人提供的较高金额捐赠(高社交信息),他们的捐助通常更多;但对于基准(低社交信息)小组,他们的整体捐赠更不太可能。使用倾向分数匹配修正两个试验小组的预处理差别后,高社交信息对平均捐赠金额的预计影响为增加$14.95 (45 %)。然而,试验还发现,高社交信息会降低失效捐赠人的概率4.1 %。由此,涉及失效捐赠人时,高社交信息会存在潜在的抵消影响。采用社交信息筹款技术吸引失效捐赠人进行捐赠时,非盈利组织应考虑这一权衡。.

بإستخدام بيانات من التجربة التي قامت بها منظمة كبيرة غير هادفة للربح، هذا البحث وجد أن المانحين الذين توقفوا عن التبرع الذين تلقوا رسالة إلتماس يتحولوا إلى تبرع عالي بالنسبة للذي قامت بها جهات مانحة أخرى (معلومات إجتماعية عالية) كانت أكثر سخاء في العطاء، لكن عموما˝ أقل إحتمال للقيام بالتبرع، نسبة إلى خط الأساس (معلومات إجتماعية منخفضة) المجموعة. بعد إستخدام محاولة التقدير لتصحيح الإختلافات قبل المعالجة في المجموعتين التجريبية، التأثير التقديري لمعلومات إجتماعية عالية على متوسط مبلغ التبرع هو زيادة قدرها 14.95$ (45٪). لكن، وجدت معلومات إجتماعية عالية أيضا˝ لتخفيض إحتمال أن المتبرع الذي يتوقف عن التبرع سوف يعطي بنسبة 4.1٪. هكذا، يمكن من أن معلومات إجتماعية عالية يكون لها آثار تعويض عندما تطبق على الجهات المانحة التي توقفت عن التبرع. يجب أن المنظمات الغير ربحية تنظرفي هذه المفاضلة عند إستخدام تقنيات المعلومات الإجتماعية لجمع التبرعات لإلتماس عطاء من الجهات المانحة التي توقفت عن التبرع.

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Notes

  1. Another branch of this literature evaluates survey and focus group responses in an attempt to discover what affects individuals’ decision to continue or discontinue donating to an organization [e.g., Beldad et al. (2015), Beldad et al. (2012), Bennett (2009), Germain et al. (2007), Mathew et al. (2007), Sargeant and Jay (2004), Sargeant (2001a), and Sargeant (2001b)].

  2. For simplicity, these variables are discretized into two categories, although the same pattern exists with more categories.

  3. The results from this estimation and summary statistics for the estimated propensity scores are included in Appendix C. To ensure that the results would not be sensitive to different probit model specifications, variants of this model were estimated (e.g., including interactions), but the predicted probabilities were nearly identical to those from the original model (i.e., the correlation coefficient was never lower than 0.998).

  4. This method of implementing the propensity score-matching estimator is known as the nearest-neighbor match. Kernel matching yields nearly identical results.

  5. An alternative method of controlling for selection bias is using Heckman Two-Stage regression analysis (Heckman 1979), which accounts for the selection process that led to only a small number of the solicited donors making a contribution during this experiment. This method produces a very similar estimate of $14.58, which is significant at the 5 % level.

  6. Although it seems like this is the most likely effect, it may also be true that because the low informational treatment is earlier in the letter, it could have had a greater impact on the giving behavior of potential donors than did the high treatment. In the extreme case of this possibility, the treatment effect would then measure the impact on donations of the low informational treatment relative to a control group that received no social information.

  7. Note that n can be normalized to one without loss of generality. In general, the “breakeven” baseline response rate (i.e., the point at which low and high social information yield the same revenue) for any given average donation amount is computed as \(p = \frac{1}{14.95}(0.041 \times d + 0.61295)\). This is found by setting the expected revenue for low social information equal to that for high social information and solving for p.

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Acknowledgments

Sincere thanks to Marianne Bitler, Manisha Shah, Mike McBride, Tim Wong, and participants of the UC-Irvine Institute for Mathematical and Behavioral Science Lunch seminar for useful comments and suggestions. This paper benefitted greatly from the comments of four anonymous referees. All errors are my own.

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Authors and Affiliations

  1. Department of Economics, University of California-Irvine, 3151 Social Science Plaza, Irvine, CA, 92697-5100, USA

    Kristoffer Jackson

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  1. Kristoffer Jackson
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Correspondence to Kristoffer Jackson.

Appendices

Appendices

Appendix A

High treatment letter for the NPO

Appendix B

Low treatment letter for the NPO

Appendix C

Probit regression to obtain predicted propensity scores.

A. Coefficients and standard errors

Dependent variable

Probability of being assigned into the high treatment group

Most recent donation

0.049***

(0.002)

Highest donation

−0.044***

(0.002)

Gender

−0.027

(0.021)

Intercept

0.021

(0.075)

N

15,166

B. Summary statistics for predicted probabilities (i.e., propensity scores)

 

High treatment

Low treatment

Difference (high treatment–low)

Mean

0.530

0.487

0.042***

(0.002)

Minimum

0.002

0.0004

0.0016

Maximum

0.685

0.692

−0.007

N

7712

7454

 
  1. Standard errors are in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01

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Jackson, K. The Effect of Social Information on Giving from Lapsed Donors: Evidence from a Field Experiment. Voluntas 27, 920–940 (2016). https://doi.org/10.1007/s11266-015-9566-2

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