Social Intelligence

Reddit Mention Signals

Unfiltered company intelligence from 50,000+ subreddits. Detect buying intent, churn risk, pricing complaints, and competitor comparisons, each signal scored for urgency and backed by direct quotes.

Start Free View Full Signal Catalog

2M+

Companies Covered

Signal Subtypes

Monthly

Refresh Cadence

10,000+

Subreddits Monitored

Social Intelligence5 subtypes · Monthly refresh

What Are Reddit Mention Signals?

Reddit mention signals capture what customers, employees, and industry observers say about a company across 50,000+ subreddits, before that feedback reaches any formal channel. Autobound analyzes both posts and comment threads, matches mentions to 2M+ companies, aggregates related discussions into a single signal, and classifies each into subtypes like buying intent, churn risk, pain points, pricing concerns, competitor mentions, and support issues.

Each signal includes post count, total upvotes and comments, urgency, buying stage, direct quotes as evidence, links to source threads, and competitors mentioned. That structure turns raw threads into competitive intelligence: when a competitor's customers are venting about pricing or reliability, you know exactly which pain to reference and how urgent it is.

Example Signal Subtypes

buyingIntentchurnRiskpainPointpricingConcerncompetitorMentionsupportIssueproductFeedbackuseCase

Data Schema

Reddit Signal Data Schema

Reddit signals capture discussion volume, engagement metrics, sentiment direction, and extracted themes from relevant subreddit conversations.

reddit_mentions.schema.json

{
  "signal_id": "a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d",
  "signal_type": "reddit-mentions",
  "signal_subtype": "pricingConcern",
  "detected_at": "2026-06-10T15: 40: 33Z",
  "association": "company",
  "company": {
    "name": "Datadog",
    "domain": "datadoghq.com",  // match on domain
    "linkedin_url": "linkedin.com/company/datadog",  // or match on LinkedIn URL
    "industries": ["Software Development"],
    "employee_count_low": 5001,
    "employee_count_high": 10000,
    "description": "Cloud monitoring and observability platform..."
  },
  "contact": [],
  "data": {
    "summary": "Engineers across r/devops and r/aws report Datadog bills running 3-5x over budget at scale, with several teams actively evaluating Grafana Cloud and Honeycomb as lower-cost alternatives.",
    "sentiment": "negative",
    "salience_score": 0.92,
    "confidence_score": 0.95,
    "recency_score": 0.88,
    "moderation_score": 0.0,
    "urgency": "high",
    "buying_stage": "evaluating",
    "objection_type": "price",
    "audience_type": ["DevOps Engineers", "SRE Teams", "Engineering Managers"],
    "total_upvotes": 412,
    "total_comments": 187,
    "post_count": 5,
    "upvote_ratio": 0.91,
    "evidence": [
      "Our Datadog bill hit $38K last month for a 60-host cluster. That's more than our AWS spend.",
      "We moved logs to Grafana Cloud and kept Datadog for APM only. Cut the bill in half."
    ],
    "source_urls": [
      "https://www.reddit.com/r/devops/comments/1rk2m8x/datadog_pricing_at_scale/",
      "https://www.reddit.com/r/aws/comments/1rj9f2q/observability_costs_out_of_control/"
    ],
    "competitors_mentioned": ["Grafana Cloud", "Honeycomb", "ClickHouse"],
    "topics": ["Observability cost management", "Per-host pricing", "Competitor evaluation"],
    "topics_tags": ["Datadog", "observability", "pricing", "APM"],
    "subreddits": ["devops", "aws", "sysadmin"],
    "post_date": "2026-06-07T18: 12: 44Z",
    "post_author": "sre_throwaway42",
    "post_flair": ["Discussion"]
  }
}

GCS Bucket: gs://autobound-reddit-company-v1/
Formats: JSONL · Parquet
Refresh: Monthly

Full schema docs →Measured coverage →

Applications

What teams build with Reddit Mention Signals

04 documented applications

01
Competitive Displacement Campaigns
When Reddit discussions reveal customer frustration with a competitor, arm your sales team with specific pain points to reference in displacement outreach.
02
Product Market Fit Validation
Monitor Reddit discussions about your product category to understand what real users value, complain about, and wish existed. Use these insights to refine your positioning.
03
Buzz Surge Detection
Sudden spikes in Reddit mentions indicate something noteworthy is happening at a company. Whether it is a product launch, a controversy, or a viral moment, buzz surges create timely outreach opportunities.
04
Customer Success Intelligence
Track Reddit mentions of your own company and customers to detect emerging satisfaction issues before they escalate to formal complaints or churn signals.

Measured, Not Estimated

What's actually inside Reddit Mention Signals

Volumes, subtypes, geography, and join-key fill rates audited directly from our production database, so you can verify coverage before you buy.

Measured coverageaudited from production · minimums, not ceilings

55,042

companies with fresh data / month

basis: published baseline

50,205

records created / month

basis: published baseline

Top subtypes

21 total

Use Case44K · 14%

Positive Review41K · 14%

Pain Point37K · 12%

Product Feedback33K · 11%

Buying Intent27K · 9.0%

Brand Reputation25K · 8.2%

Industry Trend22K · 7.2%

Competitor Mention17K · 5.5%

Geography

all 175 countries →

🇺🇸United States12K · 20%

🇬🇧United Kingdom2.5K · 4.2%

🇮🇳India1.8K · 3.0%

🇨🇦Canada1.8K · 3.0%

🇩🇪Germany1.3K · 2.1%

🇫🇷France1.2K · 2.0%

🇦🇺Australia889 · 1.5%

CA 5.1KNY 2.9KTX 1.9KFL 1.6KIL 1.0KMA 932

Top industries

all industries →

Retail1.7K · 2.8%

Software Development1.3K · 2.2%

Food and Beverage Services1.1K · 1.9%

Government Administration1.1K · 1.8%

Non-Profit Organizations970 · 1.6%

Hospitals and Health Care941 · 1.6%

Restaurants919 · 1.5%

Join keys

fill rate

Domain100%

LinkedIn URL65%

Company name100%

Records measured 301,231+Companies reached 59,744+Full schema & examples →

See the real records for yourself.

See full coverage & segmentation across all 35 signal types →

Worked Example

One signal, traced to outcome

One Reddit Mention Signals record followed from detection, through the action a rep took on it, to the measured result. Illustrative composite of observed customer workflows.

01 signal → 02 action → 03 outcome

Signal detected

Multiple Reddit threads in r/OnlineShopping report Fashion Nova orders showing 'shipped' but never arriving, accumulating 27 upvotes and 39 comments in a week.

Action taken

A logistics SaaS vendor targets Fashion Nova's VP of Operations:

“We noticed fulfillment accuracy is a hot topic for your brand. Here's how we helped a similar e-commerce company reduce lost packages by 85%.”

Outcome

Demo scheduled

Because the outreach addressed a real, publicly visible customer pain point with a quantified solution.

Run this against live data →

FAQ

Frequently Asked Questions

What are Reddit mention signals?

Reddit mention signals detect when companies are discussed across 10,000+ monitored subreddits. Autobound's AI extracts 5 signal subtypes, including buzz surges, competitor comparisons, product pain points, support issues, and hiring/layoff mentions, giving you unfiltered market intelligence about how companies and their products are perceived publicly.

How does Autobound detect Reddit mention signals?

Autobound monitors 10,000+ subreddits on a monthly refresh cadence, matching company names and products to discussion threads. AI models analyze post text, upvote velocity, comment sentiment, and thread context to classify signals by subtype and assign relevance scores. Each signal links directly to the source thread.

How should I use Reddit data in my outreach?

Never cite Reddit directly in outreach. Instead, use Reddit intelligence to inform your positioning. If Reddit users complain about a competitor's product limitations, build your messaging around those specific pain points. If a prospect's company is trending for a product issue, offer a solution to the underlying problem without referencing where you learned about it.

How It Works

From Raw Data to Your Stack

Autobound ingests from LinkedIn API, Glassdoor, GitHub, Reddit, G2, extracts structured signals with AI, and delivers them however your infrastructure needs.

Autobound Ingests

Raw data from LinkedIn API, Glassdoor, GitHub, Reddit, G2 is continuously collected and normalized across millions of sources.

AI Extracts & Scores

ML models extract 5 signal subtypes with relevance scoring, confidence levels, and entity resolution.

You Receive

Structured JSONL delivered via your preferred method, updated on a monthly cadence.

REST API

Real-time access with subtype filtering

300 req/min

GCS Push

Automated delivery to your bucket

JSONL + Parquet

Enrich API

On-demand LLM-ranked insights

AI relevance scoring

Flat File

Bulk exports for data warehouses

CSV, JSON, Parquet

3 vendors consolidated

“By consolidating three data vendors into Autobound's Enrich API, we added 100+ new signal types and saved 4 months of engineering time.”

AiSDR Team

Engineering, AiSDR

Ready to License Reddit Mention Signals?

Custom pricing based on signal types, delivery frequency, and volume. Full schema documentation and integration guides included.

Start Free View Schema Docs