Reddit Mentions
Monitor Reddit discussions to surface emerging product pain points, competitive comparisons, and category trends affecting your prospects.
Reddit Mentions surface authentic, unfiltered discussions about companies — what real users are saying when they're not talking to vendors.
We analyze 50k+ subreddits and search across 4M+ companies to surface mentions in threads and comments. For recent discussions, we analyze both the original post and the comment thread to produce one or more signals — multiple comments on the same topic can contribute to a single aggregated signal. Each mention is categorized into one of 14 subtypes (buying intent, churn risk, pain points, security concerns, and more) and scored for confidence, recency, and urgency.
Reddit is uniquely valuable because users speak without corporate filters. When someone posts "we're evaluating alternatives to [competitor] because their pricing model broke at scale" — that's a buying signal you won't find on LinkedIn or Twitter.
See real delivered data → Sample Files
Subtypes
Subtypes are the specific business events or intents we categorize each signal into — they tell you what kind of discussion was detected.
Available Subtypes (14)
| Subtype Enum | Category | Description |
|---|---|---|
buyingIntent | intent | Active discussions about evaluating or purchasing solutions |
churnRisk | risk | Users expressing dissatisfaction or intent to switch providers |
competitorMention | competitive | Active threads comparing the company to competitors |
implementationHelp | feedback | Users seeking guidance on setup or integration |
industryTrend | market | Emerging category or market trends being discussed |
integrationNeed | feedback | Users discussing integration requirements or challenges |
negativeReview | feedback | Users criticizing or warning against the product |
painPoint | feedback | Users discussing problems or frustrations with a product |
positiveReview | feedback | Users praising or recommending the product |
pricingConcern | feedback | Discussions about pricing issues, value, or cost complaints |
productFeedback | feedback | Feature requests, bugs, or improvement suggestions |
securityConcern | risk | Discussions about security, privacy, or data concerns |
supportIssue | feedback | Customer support quality or responsiveness problems |
useCase | feedback | Users sharing how they use the product or seeking advice |
Categories
Categories are a popular filtering criterion — they group related subtypes into broader themes for routing, dashboards, and segment-building.
Signal Categories
| Category | Description |
|---|---|
intent | Active buying or evaluation signals |
risk | Churn risk, security concerns, dissatisfaction |
competitive | Direct competitor comparisons and displacement signals |
feedback | Product feedback, pain points, feature requests |
market | Industry trends and emerging category discussions |
Example Signal
What a single entry looks like in a delivered signal file:
{
"signal_id": "f4a83b21-9d7c-4e68-a5f1-72c6d8e41b09",
"batch_id": "2026-03-15-00-00-00",
"signal_type": "reddit",
"signal_subtype": "churnRisk",
"signal_category": "risk",
"detected_at": "2026-03-14T07:31:55.892Z",
"association": "company",
"company": {
"name": "Zendesk",
"domain": "zendesk.com", // match on domain
"linkedin_url": "linkedin.com/company/zendesk", // or match on LinkedIn URL
"industries": ["Software Development"],
"employee_count_low": 5001,
"employee_count_high": 10000,
"description": "Customer service and engagement platform..."
},
"contact": [],
"data": {
"summary": "Multiple Reddit users report Zendesk pricing increases and discuss migration to Intercom and Freshdesk as alternatives...",
"post_text": "After 4 years on Zendesk, they just quoted us a 60% renewal increase with zero new features. Already demoing Intercom and Freshdesk this week...",
"post_author": "anonymous",
"post_date": "2026-03-12",
"post_count": 4,
"subreddits": ["r/SaaS", "r/CustomerSuccess", "r/startups"],
"source_urls": [
"https://reddit.com/r/SaaS/comments/abc123/zendesk_pricing_increase",
"https://reddit.com/r/CustomerSuccess/comments/def456/alternatives_to_zendesk"
],
"evidence": [
"After 4 years on Zendesk, they just quoted us a 60% renewal increase with zero new features",
"We switched to Intercom last quarter and cut our support costs by 40%",
"Freshdesk's free tier handles 80% of what we used Zendesk for",
"Their enterprise tier is now more expensive than Salesforce Service Cloud"
],
"topics": ["pricing increases", "vendor evaluation", "cost optimization"],
"topics_tags": ["pricing", "churn", "competitive-displacement"],
"competitors_mentioned": ["Intercom", "Freshdesk", "Salesforce Service Cloud"],
"sentiment": "negative",
"buying_stage": "active_evaluation",
"urgency": "high",
"audience_type": ["customer", "decision_maker"],
"confidence_score": 0.89,
"recency_score": 0.94,
"salience_score": 0.87,
"moderation_score": 0.95,
"total_upvotes": 247,
"total_comments": 89,
"upvote_ratio": 0.94,
"post_flair": ["Discussion"],
"objection_type": "pricing"
}
}Field Reference
Standard envelope and entity fields are shared across all signals — see Schema and Resolution. The fields below are specific to this signal:
Signal-Specific Fields
The data object contains everything unique to this signal type — the intelligence extracted from Reddit discussions.
| Field | Type | Description |
|---|---|---|
summary | string | One-line headline describing the Reddit discussion (e.g., "Multiple users report Zendesk pricing increases, evaluating alternatives"). Designed for notifications. Typically 10–20 words, always includes the company and core theme |
post_text | string | Representative text from the Reddit discussion — typically the most relevant post or comment that triggered this signal. Useful for understanding the user's exact words and sentiment |
post_author | string | Reddit username of the primary poster. Usually "anonymous" since Reddit users rarely reveal identity. Useful for tracking repeat posters across threads |
post_date | string (date) | Date of the most recent relevant post or comment. Useful for recency filtering |
post_count | integer | Number of distinct posts/comments that contributed to this aggregated signal. Higher counts indicate a broader pattern rather than a single complaint |
subreddits | array[string] | Subreddits where the discussion appeared. Useful for understanding audience context (e.g., r/SaaS vs r/sysadmin implies different buyer personas) |
source_urls | array[string] | Direct links to the Reddit threads. Useful for verification and reading full context |
evidence | array[string] | Direct quotes from Reddit users that support this signal. These are the actual voices of users and prospects — unfiltered, unedited. Powerful for building outreach that references real market sentiment |
topics | array[string] | High-level topics discussed in the thread. Useful for filtering and routing |
topics_tags | array[string] | Machine-generated tags for categorization. Useful for building automated routing rules |
competitors_mentioned | array[string] | Competitors named in the discussion. Unlike other signals, these are flat strings (not objects). Useful for competitive intelligence and displacement campaigns |
sentiment | string | Overall sentiment of the discussion: positive, negative, neutral, mixed. Negative sentiment about a company often correlates with churn risk |
buying_stage | string | Inferred buying stage: awareness, consideration, active_evaluation, decision, post_purchase. Useful for prioritizing outreach timing |
urgency | string | How time-sensitive the signal is: low, medium, high, critical. High urgency + active evaluation = a deal happening now |
audience_type | array[string] | Type of users in the discussion: customer, prospect, decision_maker, technical_user, end_user. Useful for understanding who's talking |
confidence_score | float (0.0–1.0) | How confident we are that this signal accurately reflects the stated sentiment/intent. Higher = more reliable |
recency_score | float (0.0–1.0) | How recent the discussion is relative to the detection window. Higher = more current |
salience_score | float (0.0–1.0) | How relevant and important this discussion is. Combines post engagement, specificity of complaints, and presence of actionable intent |
moderation_score | float (0.0–1.0) | Content quality score. Lower scores may indicate spam, off-topic, or low-quality content. Useful for filtering |
total_upvotes | integer | Combined upvotes across all posts/comments in this signal. Useful as a proxy for community agreement |
total_comments | integer | Total comment count across threads. High comment counts indicate active, ongoing discussion |
upvote_ratio | float (0.0–1.0) | Ratio of upvotes to total votes. High ratio (>0.9) indicates strong community agreement with the sentiment |
post_flair | array[string] | Reddit post flairs (community-assigned labels). Useful for understanding post categorization |
objection_type | string | Primary objection or concern type: pricing, features, support, reliability, security, performance. Useful for routing to the right sales play |
signal_category | string | Category grouping (see Signal Categories above). Useful for routing signals to the right team |
Timing & Delivery
detected_atis when we processed the Reddit discussion. Usepost_datefor the original thread date.- One signal per subtype per company per discussion cluster. Multiple posts about the same topic from the same timeframe are aggregated into a single signal with a higher
post_count. - Each delivery arrives in a timestamped folder. Treat all signals in a new folder as recent — no need to diff against prior deliveries.
Coverage
- Refresh: Monthly
- Coverage: 50k+ subreddits, 4M+ companies monitored
- Best for: Competitive intelligence, churn prediction, identifying buying intent from real user voices, understanding objections before sales calls
See usage tips and filtering examples → Reddit Usage Tips
Updated 9 days ago