A model of the visit.
Some people scan a screen and leave. Some read the proof. Some arrive from an ad already checking the promise. Those differences are the model, not a name swapped into a prompt.
before you spend real traffic
RunPivot Simulations: a new persona simulation named Pricing page CTA compares an original page with a mockup. The goal is to start a free trial. The simulation runs, then shows a predicted winner and each visitor type's preference. The result is a prediction, not a measured test.
How a run works.
Compare up to four candidates, set one goal, and read which version personas predict will get more visitors to act. The result is a prediction. A real experiment decides what ships.
1
What are you comparing?
Up to four candidates. Each one is a variant, a URL, or a mockup. Mark one as the control. An existing experiment is optional. Mockups can be up to 5 MB. Tall images are split into screens from top to bottom.
2
What should visitors do?
Set a goal, such as starting a free trial. A metric is optional. A run can take minutes to hours. You can leave the page while it finishes.
Pricing page CTA. The goal is to start a free trial. The paid-ad visitor acts on B. The researcher still wants A. That disagreement is the test.
Setup
1 · What are you comparing?
Pricing page CTA · No experiment attached
AOriginal
ControlVariant · The page you have
Bpricing-cta.png
CandidateMockup · Trial button on the first screen
Up to 4 candidates. Mockups up to 5 MB. Tall images are split into screens from top to bottom.
2 · What should visitors do?
Goal
Start a free trial
Metric, optional
None
Give each simulation a job.
Same form, one question. A hero, an offer, an ad, or a price. Run a simulation when you know what you want to learn, not when you have a pile of ideas.
Hero test
Does the first screen hold a cold click?
The homepage you have, next to a new first screen. See whether a paid click stays through the fold.
Offer check
Trial, demo, or waitlist: which ask survives?
Same page, different goal. See which ask each visitor type actually reaches.
Ad match
Does the page repeat what the ad promised?
A paid-ad visitor is checking that promise. If the hero says something else, they leave at the top.
Pricing pass
Who leaves when the number shows up?
Some visitors look for the price. Others never scroll that far. You see which type stops, and on which version.
Watch different visitors go through it.
Not one average person. A paid click, a skimmer, a researcher, someone coming back. They do not want the same page. Patience, reading depth, and intent change what each of them reaches.
See who stayed, who left, and why.
Every result is marked predicted, so it cannot be mistaken for the test. Skimmers never reached the button on A. Researchers still wanted A. That split is the experiment.
Results
Pricing page CTA
40 simulated visits · Goal: Start a free trial
Predicted winner: BPredicted, not measured
Candidate B · journeys
Desktop
Simulated trial starts
A · Original7/20
B · Variant 112/20
By visitor type
- Paid-ad visitorPrefers B · 4 of 5
B repeats the ad's promise, so it stayed past the hero.
Engaged: Hero headline · On A, 3 of 5 left at the hero
- Mobile skimmerPrefers B · 5 of 5
B's trial button is on the first screen. On A it's two scrolls down.
Engaged: Primary button · On A, stopped scrolling before the CTA
- Skeptical researcherPrefers A · 3 of 5
Wanted pricing and proof before a CTA. B asked too early.
Engaged: Pricing and logos · On B, left from the pricing table
- Returning visitorPrefers Tie · 5 of 5
Found the trial button on both. B was one click faster.
Engaged: Primary button · No drop-off on either
Hand the strongest idea to a real experiment.
Simulation isn't the result. It drafts the test, attaches the notes, and leaves the launch with you. The draft keeps the variants, the goal, and what each visitor did. You review it. Real visitors decide.
Simulation to experiment
Simulation
Pricing page CTA
- Predicted winnerB
- Best withAds, mobile
- Still unsureResearchers
Pricing page CTA
DraftA/B test · acme.com/
VariantsMetricsTargetingTraffic
- AOriginalControl50%
- BMockupTrial button on the first screen50%
Goal: Start a free trial · Metric: Trial signupsSimulation notes attached
Review & launchWhat comes back is a trace.
Which version each type preferred, why, and where they stopped. When they disagree, that is the brief for the experiment.
Where the research fits.
The useful finding in the public work is that a grounded agent beats a demographic sketch, and that simulation is an intervention you can replay, not a story about what is likely. That work is Stanford's generative-agent papers, and Simile, the company built from them.
We follow the distinction.
We do not claim their numbers. The 85% result is agreement with a person's own survey retest, on agents built from long interviews. A page rehearsal earns its own, against live experiments.
Common questions
Questions before you run one
How is a simulation different from an A/B test?
An A/B test measures what real visitors did. A simulation walks the page before that traffic is spent, and the result is marked predicted. Use it to choose what is worth testing. Use the experiment to decide what ships.
Is this a chatbot pretending to be a customer?
No. A language model can read the page. The visit comes from differences in how people browse: some scan and leave, some read the proof, some arrive from an ad already checking the promise. Those differences are the model, not a name swapped into a prompt.
What can I run a simulation on?
Up to four candidates. Each one is a variant, a URL, or a mockup, and one is the control. Set a goal, such as a trial or a demo. You do not need a live experiment first. Mockups can be up to 5 MB. Tall images are split into screens from top to bottom.
Do I need traffic to run a simulation?
No. Simulations do not use your real visitors. That is why they help when traffic is expensive, or when a site does not have enough of it for every idea.
Can I treat the result as a winner?
No. It shows who preferred which version, why, and where they stopped. It is predicted, not measured. When visitor types disagree, that split is the brief for a real experiment.
How does this relate to the Stanford and Simile research?
The public work shows that a grounded agent beats a demographic sketch, and that a simulation is something you can replay, not a story about what is likely. We follow that distinction. We do not claim their numbers. The 85% result is agreement with a person's own survey retest, on agents built from long interviews. A page rehearsal earns its own, against live experiments.
Ready to see the visit?
Start with the page you already have. Compare a few candidates, set one goal, and read who acted. Then launch the experiment yourself.