Articos Platform Help
Articos (articos.com) is a synthetic-user research tool. You describe a target audience, and Articos
generates AI personas — each built on 30 Big Five personality facets plus cognitive-bias mapping —
then runs one of three modes and synthesizes a research report (motivations, objections, recommendations)
in ~30 minutes, with no recruiting: User Interviews (explore an audience/problem/concept),
Concept Testing (message/value-prop/positioning variants), and A/B Testing (a landing page or two
variants). Plus a "Talk to Research" chat and probing follow-ups; reports are shareable, white-label
on Pro.
Its niche: synthetic, not a real panel — the cheap/fast pre-flight counterpart to real-panel testers
(/sales-wynter B2B, /sales-pickfu consumer) and a peer of the synthetic-study tools (/sales-syntheticusers,
/sales-ditto, /sales-atypica). Two real differentiators: (1) enforced stance diversity — it
deliberately generates skeptics/detractors, not just fans, which mitigates (doesn't cure) the "personas
skew agreeable" bias the whole cluster suffers, and the objections are the highest-signal output; and (2) a
peer-reviewed 86% accuracy claim (46 studies / 9 domains, 86% recall vs expert research, marketed 7.5× over
a bare LLM) — better-sourced than peers' self-reports, but best-effort. Self-serve: free trial + 2
researches, then Starter/Pro or a one-time Research Pack.
The double caveat to say almost every time: (1) a synthetic result is an AI opinion, not real behavior —
even with 30 Big-Five facets and enforced skeptics it carries bias, can't reproduce observed behavior, and
Articos itself says ~70–80% of insights hold up; trust relative comparisons + the objections/rationale
over absolute reads, and validate the winner with real people. (2) Even real resonance is not demand —
take the willingness-to-pay / conversion go/no-go to a real behavior test via /sales-idea-validation.
Step 1 — Gather context
If references/learnings.md exists, read it first for accumulated platform knowledge.
Ask only what you can't infer:
- What do you want from Articos?
- A) Set up a study — pick the mode (User Interviews / Concept Testing / A/B Testing) and what
you're testing (audience/problem, message/value-prop, or a landing page/variants)
- B) Describe the audience — the buyer/user you want personas matched to
- C) Read results — the synthesized report (motivations, objections, recommendations), per-persona
answers, and the Talk-to-Research chat / probing follow-ups
- D) Budget — researches per plan, Starter/Pro vs the one-time Research Pack, the free trial
- E) Get data out — export/automation (there is no API/webhooks/MCP)
- F) Choose — Articos (synthetic) vs a real panel (/sales-wynter//sales-pickfu) or another
synthetic-study tool (/sales-syntheticusers,/sales-ditto) - Is a decision riding on this, or is it a fast pre-flight? This decides how hard to push the "synthetic
is directional; validate the winner with real people / real behavior" message.
Skip-ahead: if the user wants the validate-before-building method or a cross-tool comparison, that's a
/sales-idea-validation question — route in Step 2.
Step 2 — Route or answer directly
| If the user's question is about… | Route to |
|---|---|
| The validate-before-building method, or comparing research/validation tools across the market | /sales-idea-validation {question} |
| A REST API / webhook / MCP-native research pipeline (Articos has none — it's UI-only) | /sales-userintuition {question} |
| Running a real behavior demand test (smoke-test page, waitlist, pre-sale) after a synthetic study | /sales-idea-validation or /sales-funnel {question} |
| Real-panel B2B message/positioning testing (verified professionals in your ICP) | /sales-wynter {question} |
| Real-panel consumer creative/message split-testing (real people vote + explain) | /sales-pickfu {question} |
| A census-calibrated synthetic panel with a studies API + free tier | /sales-ditto {question} |
| The pure-play synthetic interview-study tool with a documented REST studies API | /sales-syntheticusers {question} |
When routing, give the exact command: "This is a {domain} question — run: /sales-idea-validation {original question}"
Otherwise, answer Articos-specific questions using Step 3.
Step 3 — Articos reference
Read references/platform-guide.md for the full reference — the three research modes + the
automation-surface table (everything is UI-only), the persona architecture (30 Big-Five facets, cognitive-bias
mapping, enforced stance diversity), the 86%-accuracy methodology and how to caveat it, best-effort pricing
(Starter/Pro/Research Pack + trial) and plan gates (probing follow-ups, Talk-to-Research queries, white-label),
the Study → Persona → Report data model, how to write a clean audience + variant set, and how to read the
synthesized report + objections (relative, not absolute).
There is no articos-api-reference.md — Articos has no public API/webhooks/MCP (best-effort; confirm
at articos.com). Don't invent endpoints.
Answer using only the relevant section — don't dump the full reference.
Step 4 — Actionable guidance
- Lead with the double caveat: synthetic = AI opinion, and resonance ≠ demand. Whatever the user asks,
make explicit that (1) Articos personas are synthetic — an AI opinion, so even a clean report is not
real behavior (the vendor itself says ~70–80% of insights hold up); and (2) even real resonance is
stated preference, not a purchase. Both caveats stack: trust the written objections/rationale and
relative comparisons, validate the winner with real people, and take the willingness-to-pay / conversion
go/no-go to a real behavior test via/sales-idea-validation. Credit the enforced stance diversity
(deliberately generating skeptics) as a genuine bias mitigation — but not a cure that makes synthetic output
real behavior, so still route the decision to real validation. - Frame the 86% accuracy claim honestly. It's peer-reviewed (46 studies / 9 domains, 86% recall vs
expert research, a marketed 7.5× lift over a bare LLM) — a stronger provenance than the cluster's
self-reported claims — but it's still a recall benchmark on past studies, not a guarantee for the user's
audience, and Articos itself caveats ~70–80% hold-up. Present it as best-effort, not proof. - Match the mode to the job, and describe the audience well. Recommend User Interviews for exploring an
audience/problem, Concept Testing for "does my message/value-prop land", and A/B Testing for picking
between landing-page variants — reserving Articos for the fast, cheap synthetic pre-flight (route real-panel
decisions to/sales-wynter//sales-pickfu, build-or-not to/sales-idea-validation). A vague audience
yields generic personas — describe the buyer specifically, and use probing follow-ups / Talk-to-Research
to interrogate the why. - Treat automation as UI-only, and don't invent endpoints. When any API/webhook/export/integration comes
up, state that Articos has no public REST API, webhooks, Zapier/Make, or MCP server (best-effort — confirm
at articos.com); data-out is manual export/sharing (report link, PDF). Don't design a REST/webhook pipeline
or guess endpoints; if a programmatic pipeline is a hard requirement, route to/sales-userintuition. - Size a run by researches, and call pricing best-effort. Cost is a subscription (Starter ~10/mo; Pro
unlimited + white-label) or a one-time Research Pack (credits, no expiry) — pick by how many studies you'll
run. Present every number as best-effort (point to articos.com/pricing) and note the free 7-day trial (2
researches, no card) for a first run. Running more personas/studies tightens the average — it doesn't turn an
AI opinion into demand.
If you discover a gotcha or tip not in references/learnings.md, append it there with today's date.
Gotchas
Best-effort from research (2026-07) — Articos's pricing (Starter/Pro rates, Research Pack, launch-promo
discounts), research quotas, persona architecture, accuracy methodology, and export options change; verify at
articos.com and articos.com/pricing.
- Synthetic ≠ real behavior (enforced skeptics mitigate, don't cure). Personas are an AI opinion; even
with 30 Big-Five facets and deliberately-generated skeptics they inherit bias amplification and can't
reproduce observed behavior — the skeptic design reduces agreeable bias but doesn't upgrade output to demand.
Articos itself says ~70–80% of insights hold up — trust relative comparisons + the objections, validate
the winner with real people. - Resonance ≠ demand. A strong report or a persona "I'd use this" is what lands with a reader-model, not
a purchase. Take the go/no-go to a real behavior test (smoke test, pre-sale) via/sales-idea-validation. - The 86% accuracy figure is a benchmark, not a guarantee. It's peer-reviewed (46 studies / 9 domains,
86% recall vs expert research, 7.5× over a bare LLM) — better-sourced than peers' self-reports — but it's a
recall stat on past studies, not proof it'll match your audience. Present as best-effort. - No public API/webhooks/MCP/Zapier — automation is manual export. Data-out is a report link / PDF export;
don't invent endpoints or design a webhook pipeline (that's a/sales-userintuitionjob). Best-effort —
confirm at articos.com. - Priced by researches, not personas. Starter is quota-capped (~10/mo), Pro is unlimited + white-label,
and a one-time Research Pack never expires — pick by re-run count. A bigger synthetic run tightens the
average, it doesn't make an AI opinion into demand. - It's synthetic user research, not usability or idea validation. For a built product/prototype use
/sales-uxia(synthetic) or/sales-uxtweak(real); for real-panel message testing use/sales-wynter
(B2B) //sales-pickfu(consumer); for build-or-not use/sales-idea-validation.
Related skills
/sales-idea-validation— The tool-agnostic validate-before-building method + the full research/validator tool landscape (use to decide build-or-not; a synthetic "yes" is an AI opinion, not demand). Install:npx skills add sales-skills/sales --skill sales-idea-validation -a claude-code/sales-syntheticusers— Synthetic Users, the pure-play synthetic interview-study peer with a documented public REST studies API — the pick when you need to run synthetic studies programmatically. Install:npx skills add sales-skills/sales --skill sales-syntheticusers -a claude-code/sales-ditto— Ditto, the census-calibrated synthetic-panel peer with a studies API + free-tier key and Claude Code skills — pick it for census filtering or an API pipeline. Install:npx skills add sales-skills/sales --skill sales-ditto -a claude-code/sales-societies— Artificial Societies, the network simulator Articos positions against (predicts how a post/message spreads, not isolated reactions) — the self-serve synthetic alternative shoppers compare Articos to. Install:npx skills add sales-skills/sales --skill sales-societies -a claude-code/sales-wynter— Wynter, the real-panel B2B message-testing counterpart (80k+ LinkedIn-verified professionals in your ICP). Pick Wynter for real B2B positioning signal; Articos for a synthetic pre-flight. Install:npx skills add sales-skills/sales --skill sales-wynter -a claude-code/sales-pickfu— PickFu, the real-panel consumer counterpart (15M+ real people vote and explain, with a real REST API/MCP/CLI). Pick PickFu for a real-panel decision; Articos for a fast/cheap synthetic pre-flight. Install:npx skills add sales-skills/sales --skill sales-pickfu -a claude-code/sales-userintuition— The REST-API/webhook/MCP research peer — the pick when you need a programmatic pipeline Articos's UI-only surface can't offer. Install:npx skills add sales-skills/sales --skill sales-userintuition -a claude-code/sales-do— Not sure which skill to use? The router matches any sales objective to the right skill. Install:npx skills add sales-skills/sales --skill sales-do -a claude-code
Examples
Example 1: "Articos personas loved my concept and gave strong scores — should I build?"
User says: "I ran a concept test in Articos and the personas were really positive about my SaaS idea, and even the skeptics came around. Green light to build?"
Skill does: Names the double caveat — the personas are synthetic (an AI opinion), not real behavior
(vendor says ~70–80% of insights hold up) and even real resonance is not demand — credits the enforced-skeptic
design as mitigation not a cure, reframes the output as relative signal + objections not a verdict, and routes
the user to validate with real people (/sales-wynter / /sales-pickfu) + a real behavior test via /sales-idea-validation.
Result: The user keeps the objections + winning direction and earns the go/no-go from real behavior, not a synthetic report.
Example 2: "How do I pull Articos results into our data warehouse automatically?" (developer/automation)
User says: "I want a webhook to fire when an Articos study finishes and POST the report into BigQuery. What's the endpoint and how do I authenticate?"
Skill does: States plainly that Articos has no public REST API, webhooks, Zapier/Make, or MCP server
(best-effort — confirm at articos.com), so there's no endpoint or key to build against, and does not
invent one — the only data-out is manual export / a shared report link. Routes an automated
completion-to-warehouse pipeline to /sales-userintuition (API + webhooks + MCP).
Result: The user stops hunting for an API that doesn't exist and either exports manually or moves the pipeline to an API-native tool.
Example 3: "Articos or Artificial Societies for a fast pre-launch read?"
User says: "I want a cheap synthetic read on my launch message before I publish. Articos or Societies?"
Skill does: Frames the trade-off — Articos runs studies (interviews / concept / A/B) on bias-diverse
personas → a report with objections; Artificial Societies (/sales-societies) models a network predicting
how a post spreads — a different question. Picks Articos for "what do people think / what objections surface",
Societies for "how far will this post travel"; both are synthetic (AI opinions), so validate the winner with
a real panel and take demand to a real behavior test.
Result: The user picks the synthetic tool that matches the actual question and keeps demand as a separate, real test.
Troubleshooting
"Can I trust the Articos report — how accurate is it?"
Symptom: The user wants to know whether the synthesized report reflects how real people will react.
Cause: Personas are synthetic — LLM models built on 30 Big-Five facets + cognitive-bias mapping with enforced skeptics. The 86% accuracy is a peer-reviewed recall benchmark (46 studies / 9 domains, 7.5× over a bare LLM), stronger than peers' self-reports, but it's a stat on past studies; Articos itself says ~70–80% of insights hold up.
Solution: Read the report as a relative signal + the written objections (the enforced skeptics are the most useful part), not a calibrated verdict. Validate the winner with real people (/sales-wynter / /sales-pickfu) and take the go/no-go to a real behavior test (/sales-idea-validation).
"Where's the Articos API / webhook to export results?"
Symptom: You're looking for an API key and a webhook to fire when a study completes.
Cause: Articos is UI-only — no public REST API, webhooks, Zapier/Make, or MCP server (best-effort; confirm at articos.com). Data-out is manual export / a shared report link.
Solution: Export or share the report from the dashboard. For a programmatic warehouse/CRM pipeline, use an API-native tool — route to /sales-userintuition. Don't build against guessed endpoints.
"Which Articos plan do I need, and is there a way to try it first?"
Symptom: The user wants to budget and de-risk a first run.
Cause: Articos bills by researches — Starter is quota-capped (~10/mo), Pro is unlimited + white-label, and a one-time Research Pack (credits, no expiry) suits occasional use — plus launch-promo discounts that change (best-effort).
Solution: Start with the free 7-day trial (2 researches, no card) to see real output, then pick by re-run count: the one-time pack for a few studies, Starter for steady monthly use, Pro for high volume or white-label. Confirm current rates at articos.com/pricing. More researches tighten the average but don't make a synthetic result into demand.
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