User Simulation Primer
01Data

What the models are built from

Data can record what people say, who they are, or what they do. Each provider uses a different combination.

Surveys and panels

What people say

Answers to known questions from known people. Limited to the questions that were asked.

Used by Aaru Artificial Societies Electric Twin Simile

Interviews

What people say

A long conversation with one person, in their own words. Deep for each person, slow and costly to collect at scale.

Used by Artificial Societies Listen Labs Semilattice Simile

Public text

What people say

Reviews, posts and forum threads, written without a researcher present. Large and in people’s own words, but limited to what people choose to post, and attributes have to be inferred. Kosinski et al., 2013

Used by Aaru Artificial Societies Semilattice

Census and official statistics

Who people are

The shape of a population by age, income, place and household. Says little about attitudes.

Used by Aaru Artificial Societies Synthetic Users

Behavioural records

What people do

Transactions, store visits, app use and clicks. Records what people do rather than what they say, and is usually licensed.

Used by Aaru Artificial Societies Simile

Experiment responses

What people do

How people responded in controlled studies, which records treatment effects as well as answers. Kolluri et al. (Simile), 2025

Used by Simile

A customer’s own data

Any of these

Research, support conversations or panels from the organisation asking the question. The exact audience, but often a small sample.

Used by Aaru Artificial Societies Electric Twin Listen Labs Semilattice Simile Ask Rally Synthetic Users

Only what a language model learnt in training

Nothing collected

Any audience can be described in a prompt, and the answers reflect the model’s stereotypes of that audience. Wang et al., 2025

Used by Ask Rally Evidenza