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

From Zen Studio, creators of G2 Reviews and Capterra Reviews, with 50,000+ combined runs across those two actors.

Why choose this Reddit brand analyzer?

• Compare brands on the same three questions. Full reports cover how people feel, what frustrates them, and which alternatives they recommend. Add competitors to get a separate report for each, making differences and switching reasons easier to compare.
• Follow the quotes back to Reddit. Get supporting quotes with subreddit attribution and source links, plus cited posts and the communities discussing each brand. Use the AI-summarized findings to spot themes, then inspect the original discussions.
• Use the report immediately. Export structured JSON with sentiment, complaints, alternatives and allQuotes, alongside a combined Markdown report for briefs, dashboards and further analysis. Duplicate quotes and communities are consolidated within each brand report.

Compare your brand with a competitor

{
  "brand": "Notion",
  "competitors": [
    "Obsidian"
  ],
  "depth": "full"
}

Open actor input, paste this example and replace the brand names with yours. Full mode includes all three sections. Each competitor is charged as a separate brand analysis, so this example requests two analyses. Remove competitors for a single-brand report.

Choose depth: "quick" for sentiment only. The output is a sourced narrative analysis, not a numeric sentiment score; the available discussions and quotes depend on the brand's Reddit presence. Export JSON to retain the nested brand reports, or use the included Markdown report.

Zen Studio · Reviews & Brand Research
Brand Sentiment You are here	Reddit Reviews Software opinions	G2 Reviews Pros & cons	Capterra Buyer reviews	TrustRadius Enterprise reviews

Copy to your AI assistant

Copy this block into ChatGPT, Claude, Cursor, or any LLM to start building with this data.

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 To reach the maintainers, add feedback="<what you needed and did not get>" to any run, including one that worked: a missing field or option, a wrong or empty result, or which actor you are switching to or from and why. The run returns its data exactly as it would without the note, and a human reads every note.

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.