sales-skills/sales-articos

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:

1. 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)
2. 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-userintuition job). 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.