The Impact of Greeting Personalization on Estimates of Sexual 

Assault Victimization

Ashley Richards1, Marcus Berzofsky1, Bonnie Shook-Sa1, Christine Lindquist1, Kimberly 

Peterson1, Christopher Krebs1, Michael Planty2, Lynn Langton2, Jessica Stroop2 

1. RTI International, 3040 Cornwallis Road, Research Triangle Park, NC 27709 

2. Bureau of Justice Statistics, 810 Seventh Street NW, Washington, DC 20531 

Abstract 

Although personalized invitations tend to increase response rates in web surveys, little is known about how 

personalization impacts data quality. To evaluate the impact of personalization on response rates and survey 

estimates of sensitive items, we conducted an experiment to compare the effects of personalized and generic 

greetings in a survey on an extremely sensitive topic: sexual assault victimization. Bivariate analyses were used to 

determine whether or not greeting personalization led to significant differences in response rates (by sex) and 

whether victimization estimates differed by greeting personalization. Bivariate analyses indicate that personalization 

increased response rates for all students and that female respondents to the personalized greeting reported 

significantly lower victimization rates than female respondents to the generic greeting. Further study is needed to 

assess whether differences in victimization are due to under-reporting by victims or true differences in the 

responding populations. 

Introduction

As part of the Campus Climate Survey Validation Study (CCSVS) (Krebs et al., 2016) which aimed to develop a 

valid and reliable methodology for campus climate surveys, we conducted an experiment intended to guide

recommendations regarding recruitment messages for future efforts. The experiment compared personalized and 

generic greetings in emails to students inviting them to participate in the survey. The ultimate goal of the experiment 

was to determine the impact of the conditions on survey response rates and sexual assault victimization rates. 

In general, there are two broad categories of greetings: (1) a generic greeting, and (2) a personalized greeting. A 

generic greeting uses a salutation that can be applied to all sample members (e.g., “Dear Student”). The generic 

greeting has the advantage of emphasizing respondents’ anonymity. This advantage may help respondents to feel 

comfortable answering questions about sensitive topics honestly. However, because the greeting is not tailored to the 

individual sample member, he or she may feel less invested in participating. Therefore, the generic greeting has the 

disadvantage of producing lower response rates. 

A personalized greeting uses the respondent’s name or other personal information (e.g., “Dear John”). This approach 

has been identified as an effective means to increasing response rates (e.g., Cook et al., 2000). This could be due to a 

number of reasons, such as the greeting’s potential to: (1) decrease the perceived distance between researcher and 

respondent, (2) signal that the respondent is unique and important to the study, and (3) indicate the authenticity of 

the survey and its sponsor (Dillman et al, 2014). 

In addition to impacting response rates, personalized greetings may also impact estimates in surveys of sensitive 

topics—it is not clear if sample members may hesitate to either respond or to respond honestly. In other words, a

personalized greeting may downwardly bias estimates. Existing literature on the impact of a personalized greeting 

on estimates is mixed. Some studies have found that the personalized greeting reduces self-disclosure on sensitive 

items (Joinson, Woodley, & Reips, 2004) or increases socially desirable responding (Heerwegh et al., 2005); 

however other studies have been unable to replicate these findings (e.g., Heerwegh, 2005; Heerwegh & Loosveldt, 

2006). Moreover, it is not clear if any differences found in the outcome of interest are actually due to the greeting or 

due to differences in the response rates caused by the different greetings. Randomization will control for any 

differences among initial sample members allowing for simple comparisons of the response rates. However, when 

comparing the outcome measure, the initial randomization will not control for any differences in the response 

propensities due to the different greeting types. Therefore, to accurately assess the impact of greeting on the 

outcome of interest, any differences in response need to be taken into account. 
Because the literature is unclear on the exact impact that a personalized greeting would have on response rates and 

reporting victimization compared to a generic greeting, two hypotheses were formed: 

1. That the personalized greeting would result in a higher response rate than the generic greeting, and 

2. Once controlling for differences in response, the victimization rates would not differ across respondents 

who received the personalized greeting and the generic greeting. 

Methods 

The CCSVS included nine U.S. institutions of higher learning. Data were collected via a web survey during the 

spring of 2015, with five of the nine institutions included in the greeting experiment. Because school context is 

likely to influence the effects of personalization, it is necessary to vary the conditions within each of the 

participating schools to rule out the possibility of school characteristics being responsible for any observed 

variability in the conditions. Therefore, rather than assigning all sampled students in a given school to receive one 

condition and then comparing this against the other condition at another school, the experimental conditions were 

varied within each participating school. The experiment was implemented to evaluate the impact of personalization 

on response rates and survey estimates. 

A total of 20,302 sample members across five schools were randomly assigned to receive either a personalized 

greeting (“Dear [Fill: First Name]”) or a generic greeting (“Dear [Fill: School Name] Student”) in their survey 

invitation and reminders. Within each participating school, the sample was stratified by sex of the student, based on 

student rosters provided by each school. In order to ensure an equal number of males and females be assigned to 

each treatment group, the randomization was conducted within stratum. As shown in Table 1, the experiment was 

powered to detect small differences in both response (3.03% or less) and victimization (2.18% or less) rates. 

Table 1. Minimum detectable differences in response and sexual assault rates for the greeting 

experiment, by sex 

Females Males 

N 

Minimum Detectable 

Difference N 

Minimum Detectable 

Difference 

Response Rates 11,823 2.54 % 8,479 3.03 % 

Sexual Assault Rates 6,971 2.18 3,828 1.50 

Note: Detectable difference calculations assume a two-sided Pearson’s chi-squared test with alpha = 0.05 and 

80% power. Observed sample sizes, response rates, and victimization rates were used in the calculations, and 

detectable differences shown are in the direction of the observed difference. 

Following data collection, bivariate tests were conducted by sex to determine whether or not observed differences in 

response rates and sexual assault victimization rates were statistically significant. All estimates took into account the 

stratified random sampling design and were calculated using unweighted data. Tests were conducted using 

unweighted data because these experiments were testing differences among respondents rather than trying to make 

inferences about the entire student population. Because the experiment was randomized and every sampled student 

had an equal chance of being assigned to either the personalized or generic greeting conditions, observed significant 

differences in response rates can be attributed directly to the assigned greeting. However, if response rates differ 

across greeting conditions, respondent populations could differ (i.e., different greetings could encourage more or 

less participation by particular subgroups of the population). For this reason, observed differences in victimization 

outcomes could be due to either (1) different respondent characteristics (e.g., if the personalized greeting brought 

more freshmen into the sample and freshmen are more likely to be victimized, then victimization rates in the 

personalized greeting condition would be higher than the generic greeting condition), or (2) differences in reporting 

patterns due to concerns about confidentiality (e.g., if the responding populations are similar and actually have the 

same victimization status, but the personalized greeting suppresses reporting among victims). Because of the 

confounding between response and victimization patterns, bivariate analyses do not give a complete understanding 

of the effects of a personalized greeting on victimization, and further assessments are needed. 

Results 
Of the sampled students, 6,971 females and 3,828 males participated in the survey, for unweighted response rates of 

59% for females and 45% for males (AAPOR RR3; AAPOR, 2015). The personalized greeting led to significantly 

higher survey response rates for both males and females (Table 2). For both sexes, survey response rates were about 

3.5 percentage points higher for students who were randomized to receive the personalized greeting than the generic 

greeting. Based on the bivariate test, victimization rates were significantly lower, though only slightly, for females 

who received the personalized greeting. There was no significant difference for males. 

Table 2. Comparison of response rates and sexual assault rates, by greeting assignment and sex, 

2014–2015 academic year 

Generica Personalized 

Number Percent SE Number Percent SE

Response 

Males 1,819 43.3 % 0.3 % 2,009 46.9 %* 0.3 % 

Females 3,382 57.2 0.1 3,589 60.7 * 0.1 

Victimization 

Males 65 3.6 0.1 68 3.4 0.1 

Females 443 13.1 0.1 441 12.3 * 0.1 

Note: SE = standard error. 

a

 Reference group. 

* Personalized rate is significantly different than generic rate at the alpha = 0.05 level. 

Discussion 

The personalized greeting increased response rates as anticipated, but estimated victimization rates were lower for 

the personalized than the generic greeting conditions. As previously discussed, this could be due to either 

differences in the responding populations or that personalization may have reduced the likelihood that females who 

had experienced sexual assault victimization would participate in the survey or would report their victimization 

experiences openly if they did participate. 

We present here bivariate analyses only, and because of the significant difference in the response rates, it is likely 

that properties of the randomization (i.e., equal numbers of students across person characteristics) do not hold for the 

victimization comparison. Therefore, to control for potential differences between respondents in the two experiment 

groups, a multivariate model should be conducted. Preliminary findings from a model-based assessment that 

controlled for the characteristics of responding students found that there was no significant difference in 

victimization rates when taking into account characteristics of the responding students (Krebs et al., 2016). While 

more detailed study is needed, this would suggest that the bivariate differences in victimization rates are due to the 

characteristics of responding students rather than suppressed reporting of victimization due to the personalized 

greeting. 

Disclaimer: This document was prepared using Federal funds provided by the U.S. Department of Justice under 

Cooperative Agreement number 2011-NV-CX-K068. Any opinions and conclusions expressed herein are those of the 

author(s) and do not necessarily represent the views of the Bureau of Justice Statistics and the U.S. Department of 

Justice.

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