Archived snapshot of / as of 2026-09-18 (8041f67b) — current version →

AI market research · simulated respondents

Ask 500 customers. Before lunch.

Simulated respondents answer your market question in minutes — Confidence Guard™ tells you when to ask real people.

The agent scopes it in a few questions, then runs the study. No account needed to try.

No panel contract. No minimum order. No sales call. Results arrive live as they come in.

simulation · run 1 · n = 500 · done
Switzerland18–65+n = 50010–30 min
Yes, I'd pay it0%
Only with a loyalty discount0%
No, too expensive0%
Plausibility 8.0/10

Confidence Guard™: High plausibility. What that means →

Awarded 2026Best of Swiss Web 2026 – Marketing, SilverBest of Swiss Web 2026 – Productivity, BronzeBest of Swiss Web 2026 – Innovation, BronzeBest of Swiss Web — Marketing (Silver), Productivity (Bronze), Innovation (Bronze)

How it works

Three moves. The third is the one nobody else offers.

FIRST

Ask like a human, not a researcher

Type the question the way you'd ask a customer. We turn it into a proper survey instrument — answer options, order effects, the boring craft that decides whether a number means anything.

THEN

Simulate on survey data, not web text

Respondents are generated from real survey answers we collected ourselves — not from a model's idea of what your customers sound like. Stratified by age, gender and region, weighted against official population statistics. The same ground truth as a human sample. Results arrive live over 10 to 30 minutes.

WHEN IT MATTERS

Anchor it with real people

One click sends the identical questionnaire to real respondents, recruited on social media with our patent-pending stratified sampling. The simulation becomes the hypothesis; the humans settle it. Usually back within a few days.

Why it holds up

Any model will answer you. Ours will also tell you when to stop trusting it.

Asking ChatGPT what your customers think is free and instant. It is also unfalsifiable: nothing sits behind the number, and no one can tell you the answer was wrong until the market does. That's the whole difference here. It starts where a chatbot stops — and closes the gap to professional market research.

Asking a general chatbot

  • ×Trained on the internet, weighted toward the loudest markets — rarely the one you sell in
  • ×Same confident tone whether it knows or is guessing
  • ×No sub-groups you can defend to a board
  • ×No route to a real answer when the stakes rise

Asking boomerang.ai

  • Calibrated on human samples we run ourselves, continuously, and measured against them
  • Every result carries a confidence score and the reason behind it
  • Region, age and gender splits, with base sizes shown
  • Optional: escalate to real respondents in one click — same questionnaire, no re-setup

What people actually ask

The decisions that were too small for a research budget.

Most companies don't skip research because they don't care. They skip it because a CHF 25,000 study can't be justified for a CHF 25,000 decision.

Six real questions and what happened to each — all of them on boomerang.ai: simulated where the plausibility held, anchored with real respondents where it didn't.

Pricing

"If we move the subscription from CHF 39 to CHF 45, who leaves?"

Simulated · 4 price points · plausibility 8.1

Naming

"Which of these three names sounds trustworthy to a Swiss German ear?"

Simulated · then anchored, n = 400

Positioning

"Does 'sustainably sourced' still move anyone, or is it noise now?"

Simulated · split by age · plausibility 7.4

Creative

"Which of these two ad concepts gets remembered tomorrow?"

Simulated first · then anchored with real people — recall needs humans

Product

"Would customers actually use a self-checkout here, or say they would?"

Plausibility 5.2 · anchored with real people

Expansion

"Does this work the same in Romandie as in Zürich?"

Simulated · regional split · plausibility 6.9

Confidence Guard™

A number you can't check isn't research. It's a horoscope.

Every answer arrives with a plausibility score from 0 to 10, assigned by an independent checking model that rates the result for consistency with the question, the audience and the answer logic — it measures how far to trust the simulation, not whether the world agrees. Each score comes with a plain-language verdict on what it means for your decision. It's the part we'd want if we were buying this.

8.0 – 10

Decide on it. Dense human calibration behind this question type. Simulation has tracked reality closely here.

6.0 – 7.9

Direction, not decimals. Trust the ranking, don't quote the percentage in a board deck. Anchor before you commit budget.

below 6.0

Go to humans. We'll say so plainly, and put the escalation button right under the result. Selling you a weak number would cost us more than the credit.

Pricing sensitivity, retail CH8.1
Brand associations, insurance7.6
Ad recall, 48h unaided4.8

plausibility score  · last human anchor
Recalibrated with every human sample we field.

How good is good?

We publish our own error rate.

Every vendor claims their AI is accurate. It only becomes checkable when someone shows the number — including the months it went down. The plausibility score itself (0–10) comes from an independent judge model that rates how credible each simulated result is for your question and audience — it measures confidence in the simulation, not facts about the world.

45678Dec 25Jan 26Feb 26Mar 26Apr 26May 26Jun 26Jul 26Aug 265.66.94
Average plausibility across all simulations per month — everyday use, not lab conditions: arbitrary topics, started by users themselves.

6.94

Average plausibility in August 2026, against 5.6 in December 2025.

82.6%

Overlap between our simulated answer distributions and the real human ones — five Swiss surveys held out of training, scored on the model in production.

Why the curve climbs: every human sample feeds back into the model. Tomorrow's accuracy depends on today's fieldwork — which is why we run both.

Pricing

Start free. Pay when a decision is worth it.

Simulations are cheap because they're computed. Human samples cost what fieldwork costs — we don't hide either number.

All prices excl. VAT.

Starter

For finding out whether the answers are any good.

CHF 0

2 studies per month

  • up to 300 respondents per study
  • Plausibility score on every result
  • Overall results (topline)
  • 1 study in pre-test at a time
  • Help centre
Start free
Startups & SMEs

Plus

For teams putting real money behind the answer.

CHF 79 / month

or CHF 790 a year — full allowance up front

  • 5 studies per month
  • up to 1,000 respondents per study
  • Region, age and gender splits
  • A/B tests, long surveys, raw data and PDF export
  • Up to 3 studies in pre-test at once
  • Email support
  • Add real people any time: 5–10 credits per respondent (1 credit = CHF 1)
Start 14 days free — no card
Worked example

Simulated answers come with your plan. Real people are bought in credits — one credit is CHF 1, and one completed interview costs 5–10 of them. A typical study, at the sample size we recommend, with the arithmetic done:

The study
Audience
Swiss general population
Sample
300 respondents
Questions
3
Field time
3–7 days
Worked example

CHF 1'500–3'000

5–10 credits per completed interview, for 300 respondents · excl. VAT

A worked example, not a quote. Your price is firm for the stated assumptions: audience, n, length, incidence. If length or incidence move by more than ±25 %, we bill the actual effort — and tell you first. The free pre-test shows both before any cost arises. Narrower audiences and longer questionnaires sit at the top of the range; other markets can cost less. Prices in CHF, 1:1 in EUR and USD.

An institute, agency or insights team? At Boomerang Ideas you self-serve too, with onboarding help and a phone hotline on top of email support.

One last thing

Ask the question you've been arguing about.

First one's free, and the answers start arriving while you read this page.