Introduction

Every research study begins before the first question is asked. In consumr.ai, Research Setup is the stage where a defined audience becomes a research‑ready population. It connects the segment you created- who you want to study with the AI Twins and respondent cohorts that generate insights.

A segment provides the foundation: the demographic characteristics, behavioral context, and mindset that define the audience. Research Setup builds on that foundation by determining how that audience will be represented in research. Whether the study is qualitative or quantitative, the quality of the output depends on the quality of the audience being studied.

What Happens During Research Setup

Research Setup moves through three steps that prepare your audience for research.

1. Define Your Segment

You begin by creating or importing the audience you want to study. Segments can be defined in three ways:

1. Upload an existing segmentation document
2. Enter a written segment definition
3. Create a segment from connected first‑party audience data

The first two methods are covered in Predefined Segment Definition. The third method is covered in Creating Segment From 1st‑Party Audience.

This step establishes who the population is and what characteristics they represent.

2. Build the Research Population

Once segments are defined, they can be transformed into either qualitative or quantitative research populations:

• AI Twins - used for exploratory research where you want to understand motivations, reasoning, perceptions, and decision‑making.
• Respondents - used for quantitative studies where you need measurable results, comparisons, and statistically weighted findings.

3. Configure the Research Study

After the research population is created, it can be used in surveys, concept tests, focus groups, or other research workflows.

Segments Are the Starting Point

Research Setup begins with a simple question: Who are we trying to understand? The answer comes from the segment definition.

A segment determines the population represented in research, including demographic characteristics such as age range, gender, income range, and geographic location. It also includes the broader cohort context established during segment creation, including behavioral signals and mindset. Changing the segment changes the audience being measured.

Two segments within the same category can produce entirely different insights. A performance‑driven cohort will not respond the same way as a style‑driven cohort, even if both purchase within the same category. Research Setup ensures those differences are reflected in the research population.

From Segments to AI Twins and Respondents

Once a segment is defined, Research Setup determines how that audience will participate in research.

AI Twins

AI Twins represent the cohort in qualitative studies. They are designed for exploratory conversations that reveal motivations, barriers, and perceptions. A Segment Twin allows researchers to investigate the reasoning behind behavior through interactive dialogue.

Respondents

Respondents represent the cohort in quantitative studies. They are used for surveys, brand tracking, concept testing, and statistical comparisons. Respondents allow researchers to measure patterns across a defined population and generate meaningful quantitative results.