Actor Pricing Simulator

Store Positioning

Store title: Actor Pricing Simulator

Short description: Estimate Apify actor PPE pricing, break-even points, margins, and profit risk from run-cost assumptions.

SEO title: Actor Pricing Simulator — API, schema, and developer QA

SEO description: Estimate Apify actor PPE pricing, break-even points, margins, and profit risk from run-cost assumptions. Use it to catch contract drift, schema mistakes, unsafe endpoint assumptions, and developer-tool quality issues before release.

Categories: DEVELOPER_TOOLS

Keywords: actor, pricing, simulator, apify actor, pricing audit, api testing, api/developer qa

Fixed-Inclusive PPE Pricing

This actor uses pay-per-event pricing. Event prices include Apify platform usage; users are not expected to pay a separate platform-usage pass-through charge for the configured pricing model.

• Tier: A1 — API/developer QA
• Primary event: operation-tested at $0.00650 base
• Default max charge: $10.00
• Store discounts: FREE/BRONZE base, SILVER discounted, GOLD deepest approved discount

Event set:

• actor-start: base $0.00500, GOLD $0.00400. Actor Pricing Simulator: charged when actor start is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
• operation-tested: base $0.00650, GOLD $0.00520. Actor Pricing Simulator: charged when operation tested is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
• contract-rule-checked: base $0.00390, GOLD $0.00312. Actor Pricing Simulator: charged when contract rule checked is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
• report-generated: base $0.05000, GOLD $0.04000. Actor Pricing Simulator: charged when report generated is completed. The price includes Apify platform usage; no separate usage pass-through is intended.

Public Task Concepts

• Build an Actor Pricing stakeholder brief from source rows
• Prioritize Actor Pricing findings with evidence and confidence
• Summarize Actor Pricing metrics into recommended actions
• Prepare an Actor Pricing source table with uncertainty notes
• Export Actor Pricing decision rows for review

Estimate Apify actor pay-per-event pricing, break-even points, expected margins, and profit risk before publishing or promoting an actor.

What This Actor Does

Actor Pricing Simulator models Apify marketplace fees, primary PPE events, fixed run-start/report events, platform usage cost, pass-through assumptions, and target margin. It returns one dataset row per scenario and optional key-value-store reports for quick pricing review.

It is designed for creator operations, portfolio audits, and pre-publish checks where a bad price can turn a working actor into a loss-making actor.

What This Actor Does Not Do

• It does not change live Apify pricing.
• It does not publish actors.
• It does not fetch private earnings, billing, or customer-plan data from Apify.
• It does not guarantee revenue, rankings, or profitability.
• It is not financial advice; it is a deterministic calculator based on the assumptions you provide.

Best Use Cases

• Check whether a browser, proxy, OCR, or file-conversion actor can absorb owner-paid platform usage.
• Find the break-even PPE event price for a scraper before it goes public.
• Compare usage-included pricing against platform usage pass-through.
• Triage a portfolio and identify actors likely to lose money.
• Prepare exact pricing notes before a Console/API pricing update.

Input Fields

• scenarios: Pricing scenarios to simulate. Each scenario can include actorSlug, eventName, eventPriceUsd, itemsPerRun, platformUsageCostPerRunUsd, fixed start/report event prices, pass-through mode, and target margin.
• apifyFeePct: Marketplace fee percentage deducted from event revenue. The default is 20.
• defaultTargetGrossMarginPct: Target margin used when a scenario does not provide one. The default is 60.
• includeSensitivity: Add price sensitivity points at 75%, 100%, 125%, and 150% of the provided event price.
• includeReport: Write PRICING_SIMULATIONS.json, PRICING_SUMMARY.json, and PRICING_REPORT.md to the key-value store.
• maxScenarios: Maximum scenarios to process. The default is 100; the hard cap is 1000.
• maxChargeUsd: Hard run-level PPE cap. Defaults to $10; the actor stops before paid work or withholds uncharged reports when the next event would exceed it.
• debug: Enable extra troubleshooting logs.

The default input includes one browser/proxy-heavy example and one cheap utility example so a zero-config run demonstrates meaningful output quickly.

Example Input

{
  "scenarios": [
    {
      "actorSlug": "example-browser-scraper",
      "eventName": "item-scraped",
      "eventPriceUsd": 0.012,
      "itemsPerRun": 100,
      "platformUsageCostPerRunUsd": 0.65,
      "fixedStartEventPriceUsd": 0.025,
      "reportEventPriceUsd": 0.05,
      "passThroughUsageToUser": false,
      "targetGrossMarginPct": 60
    }
  ],
  "apifyFeePct": 20,
  "includeSensitivity": true,
  "includeReport": true,
  "maxScenarios": 10
}

Output Fields

Each dataset item represents one pricing scenario:

• scenarioId: Stable scenario hash.
• actorSlug and eventName: Actor/scenario label and primary PPE event.
• status: Scenario processing status. Current value is simulated.
• eventPriceUsd: Proposed primary event price.
• itemsPerRun: Assumed billable primary events per run.
• platformUsageCostPerRunUsd: Estimated platform/proxy/browser cost per run.
• passThroughUsageToUser: Whether platform usage is assumed paid by the user.
• grossRevenueUsd: Event revenue before Apify fee.
• netEventRevenueUsd: Event revenue after marketplace fee.
• ownerUsageCostUsd: Platform usage cost absorbed by the actor owner.
• netProfitUsd: Net event revenue minus owner usage cost.
• grossMarginPct: Net profit divided by net event revenue.
• breakEvenEventPriceUsd: Primary event price needed to break even.
• targetMarginEventPriceUsd: Primary event price needed for the target margin.
• riskLevel: low, medium, high, or loss.
• recommendation: Plain-language action based on the simulated risk.
• issues: Structured pricing issues such as underpriced events or high usage-cost share.
• sensitivity: Optional price sensitivity points.
• processedAt: ISO timestamp for the simulation.

The key-value store also contains:

• PRICING_SIMULATIONS.json: Full scenario array.
• PRICING_SUMMARY.json: Run-level counts and totals.
• PRICING_REPORT.md: Human-readable summary report.

Example Output

{
  "actorSlug": "example-browser-scraper",
  "eventName": "item-scraped",
  "status": "simulated",
  "eventPriceUsd": 0.012,
  "itemsPerRun": 100,
  "platformUsageCostPerRunUsd": 0.65,
  "passThroughUsageToUser": false,
  "grossRevenueUsd": 1.275,
  "netEventRevenueUsd": 1.02,
  "ownerUsageCostUsd": 0.65,
  "netProfitUsd": 0.37,
  "grossMarginPct": 36.27,
  "breakEvenEventPriceUsd": 0.007375,
  "targetMarginEventPriceUsd": 0.019563,
  "riskLevel": "medium",
  "recommendation": "Pricing is viable but below target margin. Consider testing $0.0196 per event."
}

Cost-Control Tips

• Start with 1-10 scenarios.
• Use measured run cost from small Apify runs when available.
• For browser, proxy, OCR, video, or large-crawl actors, test both owner-paid usage and pass-through scenarios.
• Treat default free-plan runs as a separate profitability question because event revenue and platform usage handling can differ by user plan.

Public Task Examples

This actor includes five prepared task concepts:

• Browser scraper PPE margin check.
• Utility actor break-even check.
• Pass-through comparison.
• Price increase target model.
• Portfolio pricing triage sample.

FAQ

Does this update my live Apify pricing?

No. It only calculates recommendations. Apply pricing changes separately through the Apify Console/API after reviewing the output.

What cost should I put in platformUsageCostPerRunUsd?

Use a measured small run when possible. If you only have estimates, enter a conservative high estimate and compare the sensitivity output.

Why does the actor include Apify fee?

Gross event revenue is not the same as owner revenue. The simulation defaults to a 20% marketplace fee, so net event revenue is 80% of configured event revenue before owner-paid platform usage.

Are diagnostics billed as dataset rows?

Troubleshooting

• Primary event price is missing or zero: Set eventPriceUsd for each scenario.
• Owner-paid usage cost exceeds net event revenue: Raise the event price, lower run cost, reduce run size, or enable usage pass-through.
• Results look too optimistic: Increase platformUsageCostPerRunUsd and use the measured cost from a realistic smoke run.
• Too many scenarios: Lower maxScenarios or split the portfolio into smaller runs.

Limitations

• This actor uses user-provided assumptions; it cannot see private Apify earnings or exact free-plan versus paid-plan user mix.
• It models linear primary-event volume and fixed run/report events, not every possible pricing structure.
• It does not account for refunds, coupons, exchange-rate effects, or conversion changes from price increases.

Source And Safety Notes

This actor does not scrape websites or process personal data. It only computes pricing math from the scenario values supplied by the user.

Changelog

• 1.0.0: Initial production build with break-even math, target-margin pricing, risk classification, sensitivity output, KVS summaries, PPE billing, examples, and fixture tests.