Replication
Methods and validation
How to Tell If a Causal Vendor's Probability Model Is AuditableA data science leader vetting a causal behavioral platform for a paid pilot needs one question answered before budget moves: can this vendor show the exact path from its modeling…
Case studies
Bechtel Carbon Tax Policy Study: Simulated vs. Published ResultsPolicy and public-affairs teams weighing a costly, slow fielded study on a carbon tax package need to know whether a simulated discrete-choice experiment gets close enough to…
Comparisons
Simulated vs Recruited Research: Choose the Evidence Your Decision NeedsChoose the method by the consequence of being wrong. Use a simulated experiment to compare actions and narrow a directional question.
Case studies
Twelve Published Studies Subconscious Uses to Check Simulated Experiments Against Real Human BehaviorA research leader deciding whether to trust a simulated experiment for a live product, pricing, or policy call needs one thing first: proof that the simulation reproduces what…
Use cases
What Is AI Market Research? Definition, Methods, and Where It Still Needs a Human CheckAI market research uses artificial intelligence to conduct, accelerate, or interpret market research: AI-generated synthetic respondents, automated analysis of qualitative data…
Company and trust
How much validation does a research decision need?A buyer weighing causal experimentation against incumbent market research asks two questions: does this method answer "why," and how much validation does this decision need before…
Case studies
Does a Simulated Yogurt-Choice Study Match Human Behavior? The Ares ReplicationA simulated conjoint study on functional yogurt reproduced the attribute ordering found in a published human study, matching 87% of the measured human ceiling (0.832 of 0.959; see…
Methods and validation
Bayesian Spatial Modeling for Evaluating Hockey Goaltending PerformanceA goalie's save percentage answers a narrow question: what share of shots did they stop?
Case studies
Checking a simulated immigration-attitudes study against Hainmueller & Hopkins 2015A research or policy team weighing whether to trust a simulated discrete-choice result on a politically sensitive topic needs a prior human benchmark, not a general accuracy…
Case studies
Do Simulated Patient Preferences Match a Published DCE? The Adam ReplicationA health-services researcher or HEOR/medical affairs team deciding whether to trust a synthetic discrete choice experiment on patient treatment preferences needs a check against…
Use cases
Validating Agentic Research Output: A Five-Layer Eval FrameworkEvery automated research pipeline runs into the same question: how do you know the output is real before you act on it?
Methods and validation
Aaru and EY: What a 90% Correlation Claim Actually CoversA synthetic-research vendor publishes a correlation number against a Big Four partner, and the number circulates as proof the category works.
Case studies
Does a Synthetic Panel Replicate Wind-Developer Policy Preferences? The Luthi ReplicationA synthetic replication of a 2011 fielded discrete-choice study on wind-energy policy preferences produced a rank correlation of r_s = .7884 (p = .0004) against the original…
Comparisons
PyMC-Marketing vs. Google Meridian: What to Check Before a Benchmark Moves Your BudgetA marketing analytics team choosing between PyMC-Marketing and Google's Meridian will find a published benchmark claiming one library is faster and more accurate than the other.
Use cases
Before You Trust a Simulated Buyer Study, Ask What Validates ItA simulated buyer study earns trust when it runs as a controlled, causal experiment against a defined population and its findings are checked against real human participants using…
Comparisons
Synthetic Responses vs. Causal Experiments: Choosing a Market Research ToolChoose a market research tool by the evidence it produces for the decision at hand.
Methods and validation
What to Demand Before You Trust a Synthetic-Respondent Vendor's Accuracy ClaimA vendor's self-reported accuracy number is a marketing claim until you can reproduce it.
Case studies
Checking a Synthetic Experiment Result Before You Act on ItThe decision: trust the number, or check it first
Use cases
Self-Improving AI Agents: When Is an 'It Got Better' Claim Real?A coding agent's instructions get rewritten by an optimizer, a benchmark score goes up, and someone proposes shipping the change.
Case studies
Does a Causal Experiment Match a Fielded Conjoint Study? The Claret Fish-Preference ReplicationA causal experiment on Spanish consumers' fish preferences reached 87% of the measured human ceiling (0.832 of 0.959; mean 0.73 across the 43 studies passing design filters)…
Comparisons
Simulated Markets vs Real Participants: How Much Evidence Does the Decision Need?A simulated-market experiment can carry an exploratory decision when its calibration is relevant and the cost of a wrong call is limited. It should not carry every decision alone.
Case studies
Does a Synthetic Panel Rank Subcompact Car Features the Way Thai Buyers Did? The Wu ReplicationAn automotive product or insights leader deciding which vehicle features to prioritize before committing R&D and marketing spend to a new subcompact model needs a way to check a…
Case studies
What a Weak Replication Correlation Actually Tells a Product TeamA weak replication correlation, like the .5213 result below significance found here, tells a product team the simulation partially tracked human preference and points to…
Case studies
Does a simulated vaccine-preference study match a published one? A Kreps et al. replication checkA head of insights weighing a simulated discrete choice experiment against a full human-recruited study needs one answer: does the simulated ranking of preferences track how real…
Methods and validation
Predicting Swinging Strikes with Bayesian Additive Regression TreesBayesian additive regression trees predict swinging strikes by summing many shallow trees fit through MCMC sampling over pitch-tracking features like velocity and spin rate…
Methods and validation
What a World Cup Forecasting Model Teaches About Trusting a Model at AllA model can hit its headline accuracy target and still be wrong on the exact numbers a decision depends on.
Case studies
When to Rerun a Causal Experiment Before You Act on ItA research or insights lead who already ran a causal experiment eventually asks the same question: is the finding still good, or does the budget and strategy riding on it need a…
Methods and validation
Can LLM-Generated Open-Ended Survey Responses Match Real Issue Distributions?A consumer insights leader deciding whether to trust LLM-generated open-ended answers before fielding qualitative research needs one question answered: do those answers reflect…
Methods and validation
When Is a Simulated Behavior Model Trustworthy Enough to Act On?A causal effect estimated from a simulated buyer population is not automatically trustworthy. It becomes trustworthy after someone checks it against real behavior.
Methods and validation
How to compare simulated and human experimental resultsCompare simulated and human experiments only when they measure the same alternatives, population, and outcome.
Case studies
Checking a simulated vaccine-allocation study against Duch et al. 2021A consumer-insights team weighing a simulated discrete-choice result against a real human study needs a published study to check the simulation against.
Case studies
Replicating a published rural job-preference study with a causal discrete choice experimentThe decision: trust a new method, or field a traditional study first
Methods and validation
Why Causal Effects Come With a Spread, Not a Single NumberA vendor hands you a causal effect with a confidence interval attached.
Case studies
Does a Simulated Population Reproduce a Published Refugee-Preference Study? The Adida ReplicationA policy researcher, DEI research lead, or research methodologist weighing a simulated discrete-choice experiment for a sensitive, non-commercial topic needs more than a…