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Quantitative Survey Research

Note: In the early stages, such as during discovery, when it is undetermined whether a trial will occur, a condensed report is available, providing predictive case value, liability, and responsibility. This is particularly useful prior to mediation. At a later date, prior to trial, we credit the initial investment and upgrade to include the complete range of key elements.

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Large-Sample Quantitative Survey Research

This approach involves gathering and analyzing large sets of numerical data to identify patterns, trends, and correlations. It provides a broad, statistically significant view of predictive behaviors and outcomes.

Our approach to case analysis, driven by quantitative methodology, is designed to enhance and complement traditional mock trial data. However, our method offers a significant advantage over mock trial exercises, which are limited in their ability to predict the outcome of a case. Mock trials typically use small sample sizes that provide limited insights and generalizability. While they may reveal patterns related to case sentiment and attitudes, their small scale prevents the drawing of strong conclusions. In contrast, Jury Analyst’s big data approach employs large, representative sample sizes, allowing us to confidently predict case sentiment and outcomes with a high level of accuracy. A sample of participants mirroring the potential juror pool will be pulled from the venue where the lawsuit is taking place. Each survey participant will be thoroughly vetted ahead of time to ensure they are real residents of the county and eligible for jury service.

The output from Jury Analyst’s large-scale survey research is a comprehensive, data-driven report designed to enhance trial preparation and strategy:

01 Recruiting a Sample Reflecting the Jury Pool Population

Recruiting a Sample Reflecting the Jury Pool Population

We aim to capture a cross-section of the jury pool that mirrors the demographic and psychographic diversity of the population. This is achieved through stratified random sampling, ensuring all relevant subgroups, such as those defined by age, gender, ethnicity, and education, are proportionally represented. This method reduces bias and enhances the external validity of our research, allowing the findings to be generalized to the broader population from which the jury will be drawn.

02 Drafting a Neutral Case Statement

Drafting a Neutral Case Statement

We provide a balanced overview of the case without introducing bias. The case statement is vetted by multiple stakeholders, including legal professionals not directly involved in the case, to ensure it is free from biased or leading language. The significance of a neutral case statement lies in its ability to ensure that any measured attitudes or predispositions are genuine and not influenced by the presentation of the case, thereby maximizing the validity of the data collected.

03 Ensuring Sufficient Sample Size

Ensuring Sufficient Sample Size

We ensure we have enough participants in our studies to confidently predict outcomes that truly represent the larger group. This involves using a method called statistical power analysis to determine the right number of participants. This method considers the effect size, which measures the strength of a relationship or difference in our data. It also looks at the significance level, commonly set at 0.05, meaning there's a 5% chance that our results are due to random factors, and the desired power, typically 80%, which reflects our confidence in detecting an effect if it truly exists. Having an adequate number of participants is essential because it reduces the risk of errors that could lead us to false conclusions, either by seeing effects that aren't there or by missing effects that are. This careful calculation ensures that our predictions about potential damages or juror characteristics are both robust and reliable.

04 Designing Reliable and Valid Questionnaires

Designing Reliable and Valid Questionnaires

When we create questionnaires, our goal is to make sure they accurately measure what we intend to measure. This means the questions should consistently give us reliable results and accurately assess what we’re interested in, such as juror attitudes. We use techniques like testing the same questions with the same people at different times, using similar questions in different ways, and checking how closely the questions relate to the subject we’re studying. Before using the questionnaire, we test it to make sure the questions are clear and effectively measure what we want. It’s crucial to design these questionnaires well because they ensure we get reliable data on juror opinions and behaviors, making our findings clear and useful for making smart decisions in jury selection and case strategy.

05 Avoiding Leading Questions

Avoiding Leading Questions

When drafting questionnaires, we are careful not to suggest answers or sentiments that could bias the results. This applies to both survey and focus group questions. When asking for jurors’ self-reported attitudes regarding a construct, it is important to avoid asking a question that suggests a particular answer/sentiment or contains information that the questionnaire could consciously or unconsciously want confirmed. In short, the researcher should not influence the results through the posing of a question. For example, when asking questions about people’s attitudes regarding negative experiences with doctors, a researcher will not want to suggest that it is commonplace for people to have negative experiences with doctors and thus elicit a response that would not have been primed otherwise.

Post-Research Debriefing

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Post-Research Debriefing

To ensure that the valuable insights and recommendations gleaned from our research are effectively integrated into your legal strategy, we offer comprehensive post-research debriefing sessions. These sessions are designed to facilitate a constructive dissemination of the research findings and are available both in-person and through virtual meetings, tailored to your team’s preferences and needs. Here’s how we expand and enhance the debriefing process:


  • In-Depth Analysis Presentation: We begin with a detailed presentation of the research findings, including data-driven insights into juror behavior, attitudes, and other relevant metrics. This presentation is tailored to highlight the most impactful information that can influence jury selection and case strategy.

  • Strategic Integration Discussion: Following the initial presentation, we engage in strategic discussions aimed at integrating these insights into your case preparation. This includes brainstorming sessions on how to apply the learnings to jury selection, witness preparation, and the overall narrative of the case.
  • Recommendations for Implementation: We provide specific, actionable recommendations based on our research findings. These recommendations are designed to enhance your team’s approach to the upcoming trial, focusing on both broad strategies and specific tactics.

  • Interactive Q&A Sessions: To ensure clarity and address any specific concerns your team may have, we include interactive Q&A sessions. These sessions offer opportunities for your team to probe deeper into the data, ask for clarifications, and explore additional scenarios that may not have been covered in the initial presentation.

  • Customized Action Plan Development: Together, we develop a customized action plan that outlines the steps necessary to effectively implement the research findings. This plan is collaboratively created to ensure that it aligns with your team’s goals and capabilities.

  • Follow-Up Support: Post-debriefing, we provide ongoing support to assist with the implementation of the strategies discussed. This support can include additional data analysis, further research inquiries, or follow-up meetings to adjust strategies as the case develops.

Our Progress

Milestones Achieved

608

Cases

47,620

Jurors Analyzed

279,681

Virtual Jurors

$9.3

Billion Recovered

We are the only....

Jury-eligible sample group provider in your geography.

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