Reddit Brand Sentiment Analyzer | What People Really Think (2026)

Find out what Reddit actually thinks about any brand. Structured sentiment, real quotes with source links, competitor comparisons, and community discovery. From Fortune 500 to niche SaaS.

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Reddit Brand Sentiment Analyzer (zen-studio/reddit-brand-sentiment-analyzer) on Apify. Analyzes any brand's Reddit reputation. Returns: overall sentiment summary, top complaints, recommended alternatives with switching reasons, real quotes with Reddit URLs, discovered communities (subreddits). Input: brand (string, required), competitors (string array, optional), depth ("quick" $0.10 or "full" $0.25, default "full"). Output: JSON with sentiment/complaints/alternatives sections, allQuotes array, communities array, combined markdown report. Competitive mode adds competitors object with full analysis per competitor. Pricing: $0.10 quick / $0.25 full per brand (competitors charged separately). Apify token required. Get token: https://console.apify.com/account/integrations

Key Features

• Multi-angle analysis — sentiment, complaints, and alternatives in a single run. Each angle queries Reddit independently for complete coverage.
• Real quotes with sources — every insight backed by actual Reddit comments with direct URLs. Not generic sentiment scores.
• Competitive mode — add competitors for side-by-side comparison. See switching patterns and cross-references.
• Community discovery — find which subreddits discuss your brand and how large those communities are.
• Markdown output — combined report ready for LLM pipelines, N8N workflows, or feeding into GPT/Claude for further analysis.

How to Analyze Brand Sentiment on Reddit

Single brand

{
    "brand": "Notion"
}

Quick snapshot (faster, cheaper)

{
    "brand": "Datadog",
    "depth": "quick"
}

Competitive analysis

{
    "brand": "Notion",
    "competitors": ["Obsidian", "Coda"]
}

Input Parameters

Parameter	Type	Default	Description
brand	string	required	Brand, product, or company to analyze
competitors	string[]	—	Competitors for side-by-side comparison
depth	select	full	quick (1 angle, ~15s) or full (3 angles, ~30-60s)

What Data Can You Extract About a Brand?

Every report includes:

• Sentiment — AI-synthesized summary of how Reddit discusses the brand, with supporting quotes
• Complaints — most common frustrations and criticisms, sourced from real discussions
• Alternatives — what people recommend instead and why they switch
• Quotes — deduplicated across all angles, each with subreddit attribution and direct URL
• Communities — subreddits where the brand is discussed
• Source posts — cited Reddit threads with metadata
• Markdown report — combined narrative ready for LLM consumption

Output Example

{
    "brand": "Datadog",
    "canonicalName": "Datadog",
    "description": "Datadog is a cloud monitoring and analytics platform...",
    "category": "SaaS / DevOps & Monitoring",
    "timestamp": "2026-04-04T07:32:22.392818+00:00",
    "sentiment": {
        "summary": "People on Reddit have varied opinions about Datadog...",
        "quotes": [
            {
                "text": "Product is S tier but apparently the most expensive option in the observability space.",
                "subreddit": "techsales",
                "url": "https://www.reddit.com/r/techsales/comments/1muiyr1/comment/n9j9uq4/",
                "sourceType": "comment"
            }
        ],
        "sourceCount": 18
    },
    "complaints": {
        "summary": "Datadog's pricing model is the most common frustration...",
        "quotes": [
            {
                "text": "Datadog is bankruptcy as a service.",
                "subreddit": "devops",
                "url": "https://www.reddit.com/r/devops/comments/...",
                "sourceType": "comment"
            }
        ],
        "sourceCount": 18
    },
    "alternatives": {
        "summary": "High cost has led many users to seek alternatives...",
        "quotes": [
            {
                "text": "We just rolled out SigNoz at my startup to help centralize logging.",
                "subreddit": "devops",
                "url": "https://www.reddit.com/r/devops/comments/...",
                "sourceType": "comment"
            }
        ],
        "sourceCount": 16
    },
    "allQuotes": [
        // 34 deduplicated quotes across all angles
    ],
    "communities": [
        { "name": "r/devops" },
        { "name": "r/sysadmin" },
        { "name": "r/techsales" },
        { "name": "r/producthunters" }
    ],
    "sourcePosts": [
        // 27 unique Reddit threads cited
    ],
    "followUpQueries": [],
    "markdown": "# Brand Sentiment: Datadog\n\n## Overall Sentiment\n\n..."
}

In competitive mode, the output includes a competitors object with a full report per competitor:

{
    "brand": "Notion",
    "sentiment": { ... },
    "complaints": { ... },
    "alternatives": { ... },
    "competitors": {
        "Obsidian": {
            "brand": "Obsidian",
            "sentiment": { ... },
            "complaints": { ... },
            "alternatives": { ... },
            "allQuotes": [ ... ]
        }
    }
}

Advanced Usage

Competitive research pipeline

Run multiple competitors to map the competitive landscape. Each brand gets the same full analysis.

{
    "brand": "Slack",
    "competitors": ["Microsoft Teams", "Discord"],
    "depth": "full"
}

The alternatives angle for each brand naturally cross-references the others. If people switch from Slack to Discord, that shows up in Slack's alternatives section.

Scheduled brand monitoring

Schedule this actor to run weekly or monthly. Each run produces a timestamped report. Compare reports over time to track sentiment shifts after product launches, pricing changes, or PR incidents.

{
    "brand": "Robinhood",
    "depth": "quick"
}

Use quick mode for scheduled runs to keep costs down ($0.10 vs $0.25 per brand).

Feed into LLM pipelines

The markdown field is a complete narrative report ready for GPT, Claude, or any LLM. Use it as context for generating executive summaries, blog posts, or investor briefings.

from apify_client import ApifyClient

client = ApifyClient("your_token")
run = client.actor("zen-studio/reddit-brand-sentiment-analyzer").call(
    run_input={"brand": "Linear", "depth": "full"}
)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    # Feed markdown into your LLM
    llm_context = item["markdown"]
    # Or use structured data
    top_complaints = item["complaints"]["quotes"][:5]

Customer discovery for founders

Find out what people complain about in your space. The complaints and alternatives angles reveal pain points and unmet needs.

{
    "brand": "Monday.com",
    "competitors": ["Asana", "ClickUp"],
    "depth": "full"
}

Pricing — Pay Per Event (PPE)

Depth	Per brand	What you get
Quick snapshot	$0.10	1 angle (sentiment only), ~15 seconds
Full report	$0.25	3 angles (sentiment + complaints + alternatives), ~30-60 seconds

Each brand counts as one event. Competitors are charged separately at the same rate.

Scenario	Cost
Single brand, quick	$0.10
Single brand, full	$0.25
Brand + 2 competitors, full	$0.75
Brand + 4 competitors, quick	$0.50

What Brands Work?

Tested across 14 brands in different categories. Works for any brand, product, or company discussed on Reddit.

Category	Example	Quotes found
SaaS	Notion, Linear, Monday.com	28-79
Consumer	Tesla, SHEIN, Temu	36-45
Fintech	Robinhood	42
B2B	Datadog	37
DTC	Huel, Oatly	40
Dev Tools	Raycast, Cursor	36-39
VPN	NordVPN	35
Niche SaaS	GorillaDesk (pest control)	32
Medical	Cala (wearable)	32

Niche brands with limited Reddit presence still produce useful reports. GorillaDesk returned 32 quotes from r/PestControlIndustry.

How It Works

1. Identify — resolves brand name to its canonical form, detects generic names (e.g. "Linear", "Monday") to avoid confusion with common words
2. Analyze — fires 3 parallel queries to Reddit's AI synthesis engine, each targeting a different angle (sentiment, complaints, alternatives)
3. Merge — deduplicates quotes and communities across angles, builds a unified report with combined markdown

Full mode takes 30-60 seconds. Quick mode takes 15-20 seconds.

FAQ

What brands work? Any brand, product, or company discussed on Reddit. Works across all categories: SaaS, consumer products, fintech, health, automotive, dev tools.

What if a brand has a generic name like "Linear" or "Monday"? The actor automatically detects generic names and adds context to prevent confusion. "Linear" returns results about the project management tool, not linear algebra.

How fresh is the data? Every run queries Reddit live. There is no cache. Results reflect current discussions.

What's the difference between quick and full mode? Quick runs 1 angle (sentiment only), full runs 3 (sentiment + complaints + alternatives). Both cost the same per brand, but quick is faster.

How does competitive mode work? Add competitor names to the competitors field. Each competitor gets the same full analysis. The alternatives angle for each brand naturally references the others, revealing switching patterns.

Can I schedule recurring runs? Yes. Use Apify's built-in scheduler to run weekly or monthly. Compare timestamped reports to track sentiment shifts over time.

What if there are no Reddit discussions about my brand? You'll get a report with empty or minimal data. The actor only returns what Reddit actually contains.

How are quotes selected? Quotes are extracted from Reddit's AI-synthesized answers, which pull from thousands of discussions. Each quote includes the source subreddit and a direct URL to the original comment.

Can I use this for content marketing? Yes. The quotes and pain points make excellent source material for blog posts, social media, and thought leadership content. Every quote has attribution.

Support

• Bugs: Issues tab
• Features: Issues tab

Legal Compliance

Extracts publicly available data from Reddit. Users must comply with Reddit's terms of service and applicable data protection regulations (GDPR, CCPA).

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Structured brand intelligence from Reddit. Real quotes, real communities, real sentiment.