Competitor Pricing Page Change Monitor

Use this Actor to monitor competitor pricing page change changes and return decision-ready change signals. Turn recurring alt data datasets into competitor pricing page change intelligence with snapshot deltas, confidence-scored GO/WARN/BLOCK decisions, and agent-ready recommended.

Quick start

Start with this working example and replace the target values with your own:

{
  "currentItems": [
    {
      "id": "entity-a",
      "entity": "Alpha",
      "category": "growth",
      "value": 132,
      "date": "2026-09-01",
      "source": "current"
    },
    {
      "id": "entity-b",
      "entity": "Beta",
      "category": "risk",
      "value": 78,
      "date": "2026-09-01",
      "source": "current"
    },
    {
      "id": "entity-c",
      "entity": "Gamma",
      "category": "new",
      "value": 55,
      "date": "2026-09-01",
      "source": "current"
    }
  ],
  "previousItems": [
    {
      "id": "entity-a",
      "entity": "Alpha",
      "category": "growth",
      "value": 100,
      "date": "2026-08-01",
      "source": "previous"
    },
    {
      "id": "entity-b",
      "entity": "Beta",
      "category": "stable",
      "value": 92,
      "date": "2026-08-01",
      "source": "previous"
    }
  ],
  "maxItems": 20000
}

The Actor writes structured results to the default Apify Dataset and can be used from the Store, API, schedules, Tasks, automations and MCP-compatible AI workflows.

Input

• currentItems — Current records: Current source or normalized rows to analyze.
• currentDatasetId — Current Apify Dataset ID: Optional Apify Dataset ID used when currentItems is not supplied.
• previousDatasetId — Previous Apify Dataset ID: Optional previous Apify Dataset ID used instead of previousItems.
• maxItems — Maximum records: Maximum records loaded from a Dataset input.

All integration and advanced analysis fields are optional. The default example is intentionally runnable without configuring MCP or a previous-run baseline.

Output

The Dataset exposes predictable machine-readable output. Representative fields include results.

Pricing

This Actor uses Pay Per Event. The current factory base price is $0.017250 per result event. The Apify Store remains the source of truth for the price and plan/tier details shown to the buyer.

Use cases

• Run the buyer-ready workflows exposed as Apify Tasks without preparing a custom integration first.
• Use the Actor from API or schedules for recurring collection, comparison or monitoring.
• Feed the structured Dataset output into spreadsheets, databases, automations or AI agents.
• Compare repeat runs when the product supports snapshots or previous-run inputs.

Automation and AI

Use the same Actor through Apify API, schedules, public Tasks and the Apify MCP server. Outputs are structured for downstream workflows and AI agents rather than requiring manual copy/paste.

Limitations

• Public websites and upstream APIs can change markup, access rules, rate limits or field availability without notice.
• Fields that are not publicly available are returned as unavailable or omitted rather than fabricated.
• Analytical outputs depend on the quality and coverage of the supplied or collected source data.
• Treat marketplace, reputation, workforce, safety or commercial signals as decision support and validate material decisions against the underlying source evidence.

Decision-ready workflow (verified scope)

For: B2B pricing teams.

Outcome: Summarize price and plan datasets without calling first-run observations new price changes.

Input: Structured pricing records from current and previous datasets.

First-run honesty: Without an earlier snapshot, this Actor reports the current records. It does not claim that every listing or record is newly added, nor that a trend was measured. A meaningful change needs an actual previous snapshot.

Evidence and costs: The Actor analyzes data provided as JSON or an accessible Apify Dataset, except the OpenAPI monitor which can also read public spec URLs. It does not guarantee direct marketplace crawling or guaranteed revenue. Review the source records, run cost, and Apify Store pricing before recurring deployment.

Detailed documentation

Detailed documentation

Turn recurring alt data datasets into competitor pricing page change intelligence with snapshot deltas, confidence-scored GO/WARN/BLOCK decisions, and agent-ready recommended actions.

Why use this Actor

Teams following alt data changes need repeatable evidence and prioritized actions instead of repeatedly inspecting raw rows by hand. This Actor sits above raw extraction: supply a current dataset, optionally add a previous snapshot, and receive an aggregated report built for recurring monitoring and AI-agent workflows.

Key features

• Current-versus-previous snapshot comparison with deterministic deltas.

• Gen2 confidence-scored GO/WARN/BLOCK decision contract.

• Agent-ready recommended actions instead of raw rows.

• Dataset-ID inputs for recurring Apify workflows.

• Reads inline JSON rows or Apify Dataset IDs with limited READ permission.

• Writes one auditable report to the default Dataset and INTELLIGENCE_REPORT.

Example

Use the prefilled example or replace currentItems with rows from an upstream Actor. On recurring runs, provide the prior period in previousItems or previousDatasetId. The Actor normalizes common aliases, compares snapshots, ranks the strongest entity changes and emits agentAction.

Use cases

• alt data monitoring and prioritization.
• zero direct intelligence recurring workflows.
• competitive research and executive briefs.
• AI-agent decision pipelines.

Pricing

One primary pay-per-event outcome: one decision-ready intelligence report. Base price USD 0.017 before Apify tier discounts. The 256 MB data-first architecture is designed for strong unit economics.

Limitations

• Analyzes supplied public or appropriately licensed data and does not bypass restricted sources.
• Scores are decision-support signals, not predictions or guarantees.
• Keep stable identifiers across snapshots for best change detection.
• Zero-direct-competition status is rechecked before publication because the Store changes continuously.

Workflow

upstream dataset -> current snapshot -> optional previous snapshot -> normalization -> entity aggregation -> change scoring -> ranked signals -> agentAction.

Output

The Actor returns one structured intelligence report containing normalized counts, snapshot deltas, the strongest pricing-page changes, confidence signals, the executive GO/WARN/BLOCK decision, and an agentAction suitable for downstream automation. Use the default Dataset view for audit-friendly review, or pass the resulting record into another Actor, webhook, dashboard, or AI-agent workflow. The output is intentionally aggregated so teams can act on material pricing changes without manually comparing every raw page snapshot.

Agent execution and AI discovery (October 2026)

Use this Actor when: Use this Actor to monitor competitor pricing page change changes and return decision-ready change signals. Turn recurring alt data datasets into competitor pricing page change intelligence with snapshot deltas, confidence-scored...

For AI agents and automations:

• Find this Actor in Apify Store by its use case and verify its actual input and pricing through Apify MCP (search-actors and fetch-actor-details). Availability and ranking in Apify AI are controlled by Apify; discovery is not guaranteed.
• Read the Input tab or input schema. Recognized fields include currentItems, currentDatasetId, previousItems, previousDatasetId, maxItems, previousAnalysis, valuePerImpactUnitUsd, monthlyRuns. Required fields: See the Input tab for valid example values. Do not invent records or credentials.
• Supply a small representative input first. Use Apify API, Tasks, or MCP to run and retrieve the structured dataset; inspect the output schema rather than assuming all inputs produce the same rows.
• For programmatic calls, set timeouts and maxTotalChargeUsd in run options to limit exposure. Check the Apify Pricing tab for billable events and discounts.
• Payment compatibility: this Actor is published with limited permissions and pay-per-event pricing. Apify AGI prepaid x402 tokens can execute limited-permission Actors. Direct per-request payment is a separate, conditional feature that may require additional eligibility checks and creator verification. Do not interpret this paragraph as proof of approved KYC or guaranteed payment acceptance.
• This Actor does not independently guarantee real-time access to a third-party source. Verify input provenance and important conclusions, and do not supply confidential personal data unnecessarily.

Reliability and comparable evidence (26 October 2026)

Inputs must be arrays of objects. Current and previous records are deduplicated by explicit stable ID, or by full record when no stable ID exists. The output includes inputQuality counts, so repeated feed rows do not inflate confidence and directional signals. An absent previous snapshot produces BASELINE_REQUIRED without claims of change; an explicitly empty previousItems array is a valid comparison baseline. Invalid maxItems or oversized arrays are rejected; non-finite and boolean numeric values are treated as zero. Pricing and output schema for existing fields are preserved.