Brand Mention Monitor — Brandwatch Alternative

Monitor public brand mentions across Google News, Hacker News, Reddit RSS, and selected feeds. Export matched queries, source URLs, sentiment cues, urgency flags, and collection times for a review queue. For brand researchers, each dataset row is one retained public mention with its query, source, and collection context.

Workflow: put the results to work

Add the brand name, useful aliases, and explicit competitors, then select relevant public sources. Review urgent mentions with their source context. Sentiment labels are deterministic triage cues; they support a reading queue rather than replace human interpretation.

Best fit and focused standalone workflow

Choose this Actor when the job is a source-linked snapshot of public conversations around one brand, product, organization, or competitor set. Use it for teams that value machine-readable rows, explicit collection boundaries, and a lightweight way to compare current public coverage.

For a separate AI-answer visibility workflow, then use AI Search Brand Monitor to compare how brands appear in AI-generated answers. Brand Mention Monitor starts with public-source mentions; the next step can be a scheduled review, a team dashboard, or a downstream enrichment flow.

From monitoring request to reviewable dataset

A growth or communications team starts with a brand name, an optional competitor set, and a seven-day freshness window. The Actor then queries the selected public sources, filters custom feeds to matching terms, normalizes public-source fields, and deduplicates overlapping URLs. Next, the team compares sentiment and urgency flags, exports the mentions view, and schedules the same bounded input for regular review.

Quick start

Use a clear public brand name, select the source mix, and set the whole-run result cap. Aliases widen primary-brand matching, while competitors create separately labeled comparison rows.

{
  "brandName": "Apify",
  "brandAliases": ["Apify Store"],
  "competitors": ["Bright Data"],
  "sources": ["googleNews", "hackerNews", "reddit"],
  "lookbackDays": 7,
  "maxResults": 20,
  "excludeKeywords": ["sponsored"],
  "responseFormat": "concise"
}

Add direct public RSS, Atom, or JSON Feed URLs through feedUrls when a known publication or community feed belongs in the same review. The Actor keeps the source endpoint and source item URL on every retained record.

Data you receive

One default-dataset row represents one validated, deduplicated public mention for the configured brand or competitor. OUTPUT is the concise terminal outcome, while RUN_SUMMARY provides source-level counters and warnings for operational readback.

Field	Meaning
subject and brandName	Identify the primary brand or a configured competitor.
source, sourceUrl, and sourceDomain	Preserve the selected public source and a direct item URL.
publishedAt and retrievedAt	Separate the source-supplied publication time from Actor collection time.
sentiment, sentimentScore, and urgency	Provide transparent keyword-based review signals.
sourceQuery, feedUrl, and matchedTerms	Show why the row entered this bounded monitoring run.

{
  "recordType": "mention",
  "id": "7ef830cece2f24aa20b91b5f",
  "subject": "brand",
  "brandName": "Apify",
  "matchedTerms": ["Apify"],
  "source": "Hacker News",
  "title": "Example source-provided title mentioning Apify",
  "text": "A bounded source-provided excerpt for review.",
  "sourceUrl": "https://news.ycombinator.com/item?id=123456",
  "sourceDomain": "news.ycombinator.com",
  "author": "example-author",
  "publishedAt": null,
  "retrievedAt": "ISO-8601 collection timestamp",
  "sentiment": "neutral",
  "sentimentScore": 0,
  "urgency": "low",
  "sourceQuery": "Apify",
  "feedUrl": null,
  "responseFormat": "concise",
  "language": "en-US"
}

Run through the API

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~brandwatch-alternative/runs?token=$APIFY_TOKEN" \
  -H "content-type: application/json" \
  -d '{"brandName":"Apify","sources":["googleNews","hackerNews"],"lookbackDays":7,"maxResults":20}'

Read the run's default dataset after it completes, then check OUTPUT and RUN_SUMMARY before treating the result as a complete monitoring snapshot.

For AI agents and MCP workflows

Monitor public mentions of Apify and Bright Data from the last seven days, return up to 20 rows, then read the terminal outcome and cite the source URL and collection time for each finding.

An AI agent can pass the same bounded input through Apify, inspect outcome, and route rows by subject, sentiment, urgency, and provenance. A reliable workflow validates the dataset readback before summarizing coverage and keeps source availability warnings alongside any decision.

Brandwatch comparison

Decision area	Brand Mention Monitor	Brandwatch
Scope	Bounded public-source monitoring workflow for one configured review job.	Broad consumer-intelligence and social-listening suite for enterprise research workflows.
Inputs	Brand names, aliases, competitors, public-source selection, and direct public feeds.	Suite workspace, queries, and product configuration for broader research operations.
Billing and cost control	Pay per event plus platform usage, with maxResults as a per-run collection cap.	Evaluate current suite pricing and plan coverage directly for the required team workflow.
Outputs	Source-linked dataset rows plus OUTPUT and RUN_SUMMARY readback artifacts.	Suite analysis, dashboards, collaboration, and broader research features.
Integrations and automation	API-ready input, dataset exports, scheduling, and agent-oriented provenance fields.	Evaluate the current documented integrations and automation path for the selected suite plan.

This independent Actor is not affiliated, associated, or endorsed by Brandwatch. Brandwatch can be a strong fit for organizations seeking its broader suite capabilities; this Actor is designed for a specific, source-linked monitoring job.

Builder's note and practical guidance

I built this Actor for the moment between a broad monitoring question and a reviewable, source-linked list of current public mentions. I designed the data contract around provenance first: a source URL, source query, publication time, collection time, and explicit terminal outcome provide a useful starting point for human review or downstream automation. For the clearest signal, use precise public brand names, a modest freshness window, and a result cap that matches the review capacity of the next workflow step. Literal exclusions apply to titles, source text, and selected source queries, which keeps query-led reviews consistent.

Responsible use

Use this workflow for public sources you are authorized to access, with collection practices that follow applicable laws and site terms. Public-source availability changes over time, so keep the source URL and collection time with any report or decision based on these records.

Pricing and run costs

This Actor uses Pay per event plus Apify platform usage. The Pricing tab lists the current event rates and billing terms.

Event	Billing unit	When it applies
apify-actor-start	Actor Start	Charged when the Actor starts running. Number of events charged depends on Actor memory (one event per GB, minimum one event).
mention-observed	Public mention	One validated, deduplicated public mention is persisted with source provenance and deterministic sentiment fields.

Run cost combines the charged events and Apify platform usage. Review the run charge limit and requested result count before starting.

Connect an AI agent

Use the Apify MCP configurator to choose an available client connection. Inspect this Actor’s current input schema and required credentials before running it.