Pricing

from $8.50 / 1,000 delivered signal metrics reports

Competitive Intelligence Metrics Calculator

Aggregate buyer-supplied signal rows into one deterministic metrics report. Get complete closed-enum counts, source totals, integer confidence basis points, review warnings, evidence gaps, and a human action without fetching external sources.

Pricing

from $8.50 / 1,000 delivered signal metrics reports

Rating

0.0

(0)

Developer

Tim Zinin

Actor stats

Bookmarked

Total users

Monthly active users

11 days ago

Last modified

Categories

MCP servers

Automation

Marketing

You can access the Competitive Intelligence Metrics Calculator programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "schemaVersion": "1.1",
10    "rows": [
11        {
12            "signalId": "nike-launch-001",
13            "eventType": "product_launch",
14            "severity": "high",
15            "sourceName": "Brand newsroom",
16            "confidenceBps": 9200,
17            "status": "active",
18        },
19        {
20            "signalId": "nike-price-001",
21            "eventType": "price_change",
22            "severity": "medium",
23            "sourceName": "Retail monitor",
24            "confidenceBps": 7600,
25            "status": "resolved",
26        },
27        {
28            "signalId": "nike-review-001",
29            "eventType": "review",
30            "severity": "low",
31            "sourceName": "Retail monitor",
32            "confidenceBps": 4800,
33            "status": "active",
34        },
35    ],
36}
37
38# Run the Actor and wait for it to finish
39run = client.actor("zinin/us-brand-signal-metrics-aggregator").call(run_input=run_input)
40
41# Fetch and print Actor results from the run's dataset (if there are any)
42print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
43for item in client.dataset(run.default_dataset_id).iterate_items():
44    print(item)
45
46# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Signal Metrics Aggregator — Counts & Warnings API in Python

The Apify API client for Python is the official library that allows you to use Competitive Intelligence Metrics Calculator API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Competitive Intelligence Metrics Calculator API in JavaScript

Competitive Intelligence Metrics Calculator API through CLI

Competitive Intelligence Metrics Calculator OpenAPI definition

Competitive Intelligence Metrics Calculator API

Competitive Intelligence Summary by Brand

zinin/us-brand-signal-brand-summary

Summarize buyer-supplied signal rows by brand in one deterministic report. Preserve event, severity, status, and recorded-source counts with stable digests, evidence gaps, and a human review action. No source fetching or external verification.

Tim Zinin

Daily Competitive Intelligence Brief Builder

zinin/us-brand-signal-brief-composer

Turn 1–50 buyer-supplied signal rows into one deterministic severity brief. Get complete CRITICAL/HIGH/MEDIUM/LOW sections, ordered projections, stable digests, explicit evidence gaps, and a human review action without source fetching or external verification.

Tim Zinin

Competitive Intelligence Dataset Splitter

zinin/us-brand-signal-batch-splitter

Group buyer-supplied signal rows by brand, event type, severity, or analysis status. Get one deterministic grouping report with complete counts, stable digests, evidence gaps, and a human review action. It does not create separate Datasets.

Tim Zinin

Competitive Evidence Snapshot Change Detector

zinin/us-brand-evidence-snapshot-diff

Compare two buyer-supplied evidence snapshots in one deterministic report. Separate added, removed, changed, and unchanged records with stable digests, evidence gaps, human review actions, and current-run billing truth. No source fetching.

Tim Zinin

Auditable Competitive Evidence Timeline Builder

zinin/us-brand-evidence-chronology-builder

Turn 1–30 buyer-supplied brand evidence rows into one deterministic, digest-verifiable chronology with stable ordering, timestamp warnings, source links, gaps, and a manual-review action. Offline: no source fetch or identity, truth, rights, or legal verification. One paid report per run.

Tim Zinin

Competitive Intelligence Action Queue Builder

zinin/us-brand-action-queue

Turn buyer-authorized signal rows into one deterministic, prioritized human-review queue. Retain conflicts, rule traces, evidence gaps, owner routing, stable digests, and current-run billing truth. No source fetching or autonomous action.

Tim Zinin

Competitive Signal Business Rules Router

zinin/us-brand-signal-rule-router

Turn buyer-supplied normalized signals and ordered rules into one deterministic routing plan. Preserve matched routes, unmatched signals, warnings, stable digests, evidence gaps, human review action, and current-run billing truth without contacting destinations.

Tim Zinin

Confidence Threshold Filter for Brand Signals

zinin/us-brand-signal-confidence-gate

Apply explicit buyer-owned accept and review thresholds to normalized signal scores. Get one deterministic report with accepted, review, and rejected queues, stable digests, evidence gaps, human review action, and current-run billing truth.

Tim Zinin

Brand Signal Co-Occurrence Analysis Tool

zinin/us-brand-signal-cooccurrence-analyzer

Count which opaque signals appear together across buyer-supplied groups. Get one deterministic report with support, Jaccard overlap, stable digests, evidence gaps, and a review action. No source fetching, identity inference, or causality claim.

Tim Zinin

Source Citation Table Generator for Evidence

zinin/us-brand-evidence-citation-table

Turn 1–100 buyer-supplied brand evidence rows into one deterministic citation-table report with preserved fields and HTTPS URLs, bounded Markdown, source and host counts, verification gaps, and SHA-256 digests. Sources are never fetched or verified; run start is separate.

Tim Zinin