Reddit Mentions (Company)

Overview

Reddit Mentions (Company) turn candid Reddit threads into structured sales signals. When a business complains about a renewal, evaluates a replacement, or reports an outage, you get a signal with the company resolved to its domain and the exact quotes that prove it.

We monitor 500+ hand-vetted business communities and 150+ standing searches. Every community passed a live AI screen before inclusion (1,300+ candidates tested, 59% rejected). Each signal carries one of 15 subtypes, verbatim evidence, and two honesty labels: stage says how strong the evidence is; prominence says whether the thread was about this or mentioned it in passing.

Delivery is weekly. A signal ships once - the ID is stable, and a record re-ships only when its evidence gets stronger.

Available Subtypes

The signal_subtype field takes one of 15 values. Expand for the full list with each subtype's stage and category vocabularies.

All 15 subtypes - roles, stages, and categories

Subtype	Role	Stage values	Category values	Description
`customerFeedback`	vendor	`none` `considering` `switching` `switched`	`pricing` `reliability` `security` `support` `integration` `implementation` `features` `usability` `general`	Any customer voice about a vendor's product - praise, pain, pricing anger, intent to leave, or a completed switch. The broadest subtype. Watch `stage` for churn: `switching`/`switched` means the account moved
`buyingIntent`	vendor or buyer	`researching` `evaluating` `deciding`	free text - the software category (`"CRM"`, `"observability"`)	An active evaluation or purchase. Buyer-side records need a company named specifically enough to resolve, so most records are vendor-side
`techAdoption`	buyer	`switched`	free text - the tool category adopted	A named company reports using or rolling out named tools
`serviceOutage`	subject	event ladder¹	`outage` `degradation` `data_loss`	The product is down or degraded NOW. Post-hoc reliability complaints are `customerFeedback`/`reliability`
`pricingChange`	subject	event ladder¹	`price` `license` `packaging` `terms`	The vendor changed price, licensing, packaging, or terms - the fact of the change; the angry reaction is `customerFeedback`
`productChange`	subject	event ladder¹	`discontinued` `feature_removed` `breaking_change` `redesign` `policy_change`	Sunset/EOL, removed feature, breaking release, redesign, or policy change
`accountRestriction`	subject	event ladder¹	`suspension` `closure` `funds_hold` `quota_denied` `access_denied` `listing_removed` `reviews_removed` `ad_disapproved`	A platform suspended, closed, held funds from, or denied access to a customer
`financialDistress`	subject	event ladder¹	`unpaid_vendors` `missed_payroll` `runway` `fire_sale` `shutdown_talk` `other`	Unpaid vendors, missed payroll, runway rumors, insolvency. Often ships `speculative` - community predictions, labeled as predictions
`cybersecurityIncident`	subject	event ladder¹	`breach` `ransomware` `vulnerability_disclosed` `active_exploitation` `supply_chain`	A breach, or a critical vulnerability in the company's own product. The entity is always the victim or the vulnerable-product maker
`layoffs`	subject	event ladder¹	`layoffs` `hiring_freeze` `attrition`	Layoffs/RIF, hiring freeze, or mass attrition
`leadershipChange`	subject	event ladder¹	-	A named executive joins or leaves. Carries `data.details` `{person_name, title, direction}`. Resolved people also ship as `reddit-contact` records
`acquisitionAnnounced`	subject	event ladder¹	`acquirer` `target` `merger` (this company's side)	An acquisition or merger; the counterparty appears in `data.other_companies`
`fundingEvent`	subject	event ladder¹	`seed` `series_a` `series_b` `later_stage` `debt` `grant` `unspecified`	A funding round raised by this company
`hiringSignal`	subject	event ladder¹	-	The company hires at scale. One person's job offer does not qualify
`productLaunch`	subject	event ladder¹	-	The company launches a product

¹ Event ladder - every event subtype uses the same stage scale, weakest to strongest evidence: speculative (the author predicts it; never stated as fact) → rumored (someone claims it is happening, unverified) → reported (secondhand claim it occurred) → confirmed (first-hand account or official notice/link). Filter stage != "speculative" for facts only; keep predictions as early intent.

Schema

Verbatim production record, annotated:

{
  "signal_id": "913d28a9-8194-5e66-a6fc-f750a3d09442",  // deterministic: same signal = same ID, every delivery
  "batch_id": "2026-09-20-16-25-11", // when we generated it (UTC, audit truth)
  "signal_type": "reddit-company",
  "signal_subtype": "customerFeedback",
  "signal_name": "Reddit Mention",
  "detected_at": "2026-09-20T19:04:57.108Z", // delivery-timeline date (week-ending for weekly files)
  "association": "company",
  "company": { // use domain or LinkedIn url to match. Shown for both contact & company signals.
    "name": "Grammarly",
    "domain": "grammarly.com", // resolved live; null = we abstained rather than guessed
    "linkedin_url": "https://www.linkedin.com/company/grammarly",
    "industries": ["Software Development"],
    "employee_count_low": 1001,
    "employee_count_high": 5000,
    "description": "Grammarly is an AI writing assistant used by teams and enterprises."
  },
  "contact": null, // always null on company records
  "data": {
    "signal_category": "feedback", // coarse group: feedback | intent | adoption | event
    "summary": "A company reports that after deciding not to renew its subscription, Grammarly sent unsolicited emails and in-app popups to all licensed users, prompting the company's leadership to immediately remove the software and expedite a switch to Microsoft Copilot.",
    "entity_role": "vendor", // vendor | buyer | subject
    "stage": "switched", // subtype-scoped; here: the customer already moved
    "category": "general", // subtype-scoped; null where the subtype has none
    "sentiment": "negative", // toward the company
    "prominence": "core", // core = the thread is about this; aside = passing mention
    "timing": "completed", // ongoing_state | in_progress | completed | planned
    "event_date": "2026-09", // best-estimate month; null = no date derivable (never invented)
    "event_date_text": null, // the raw phrase from the thread, when one exists
    "people": [], // real named people only - never Reddit usernames
    "topics": ["cancellation", "customer retention", "vendor management", "sales tactics"],
    "products_mentioned": [],
    "evidence": [ // verbatim quotes; prefix = where each came from
      "[post] We let them know we weren't going to renew and they sent these unsolicited emails and popups in their app to all of the users who had licenses.",
      "[post] They didn't give us a heads up - just started carpet bombing everyone. They even listed the direct email for the guy on my team who handles licensing."
    ],
    "other_companies": [ // everyone else in the conversation, with their role
      { "name": "Microsoft", "role": "switching_to", "domain": "microsoft.com" }
    ],
    "source_url": "https://www.reddit.com/r/sysadmin/comments/1wjdpgx/psa_grammarly_will_send_unhinged_messages_to_all/",
    "post_id": "1wjdpgx",
    "post_title": "PSA: Grammarly will send unhinged messages to all your users if you try to cancel",
    "post_text": "…full thread body, up to 5,000 chars - the same context the extractor read…",
    "post_kind": "multi_media", // text | image | link | multi_media | hosted:video
    "link_url": null,
    "image_url": null,
    "image_read_by_model": false, // true when the extractor read the image pixels
    "subreddit": "sysadmin",
    "subreddit_url": "https://www.reddit.com/r/sysadmin/",
    "post_date": "2026-09-18T02:26:01.000Z", // when the thread was posted (the real conversation time)
    "post_flair": ["General Discussion"],
    "post_author": "brothertax", // handle only - we never resolve Reddit users
    "post_author_url": "https://www.reddit.com/user/brothertax/",
    "post_author_id": "t2_4g10w",
    "total_upvotes": 4207,
    "total_comments": 348,
    "upvote_ratio": 0.98,
    "awards": 0,
    "virality": "very_high", // engagement percentile vs the week's corpus
    "mention_count": 1, // distinct threads naming this company this run
    "mention_surge": false, // true at mention_count >= 3
    "related_post_urls": [],
    "comments": [ // up to 20 top comments, for verification context
      {
        "author": "bunnythistle",
        "author_url": "https://www.reddit.com/user/bunnythistle/",
        "score": 2064,
        "depth": 0,
        "posted_at": "2026-09-18T02:33:58.000Z",
        "url": "https://www.reddit.com/r/sysadmin/comments/1wjdpgx/comment/pahvl9b/",
        "excerpt": "That sounds like a great way to get their domain on our email block list. …"
      }
    ],
    "comments_total": 348,
    "comments_included": 20,
    "nsfw": false, // Reddit's own over-18 flag
    "content_warning": null // "profanity_in_quotes" = check before quoting in outreach
  },
  "_qa": { // quality metadata - machine-measured, filterable
    "validation_issues": [],
    "resolution": "resolved",
    "margin": null,
    "triage_interest": 0.9
  }
}

Field Reference

Core Fields

Field	Type	Required	Description
`signal_id`	string (UUID)	✓	Deterministic ID derived from `(post, company, subtype)`. The same signal carries the same ID in every delivery. Re-runs and backfills are upsert-safe: treat `signal_id` as your primary key
`batch_id`	string	✓	Generation batch timestamp, `YYYY-MM-DD-HH-MM-SS` UTC. This is when Autobound produced the record - the audit trail. It can differ from `detected_at` on backfilled weeks
`signal_type`	string	✓	Always `"reddit-company"`
`signal_subtype`	string	✓	One of the 15 subtypes above. Drives which `stage` and `category` values are possible
`signal_name`	string	✓	Always `"Reddit Mention"`
`detected_at`	string (ISO 8601)	✓	The date this signal belongs to on YOUR timeline. For weekly files it is the week-ending date. It is not the thread date - use `data.post_date` for that
`association`	string	✓	Always `"company"`
`company`	object	✓	The company this signal is about (below)
`contact`	null	✓	Always `null` on company records; person records ship as `reddit-contact`

Company Object

Field	Type	Required	Description
`name`	string	✓	The company name after resolution. Falls back to the name exactly as the thread used it when resolution abstained
`domain`	string \| null	✓	Primary domain from Autobound's live resolution engine (web search + AI verification of each candidate). `null` means the resolver abstained rather than guessed - about 1 in 10 records; the signal still ships name-only. Use `domain` as your join key to CRM/enrichment when present

Data Object

Field	Type	Description
`signal_category`	string	Coarse grouping for quick routing: `feedback`, `intent`, `adoption`, or `event`. Redundant with subtype but cheaper to filter on
`summary`	string	One sentence, company first, with the concrete specifics (numbers, dates, names) pulled into words. Predictions read as predictions; passing mentions read as asides - the summary never upgrades weak evidence
`entity_role`	string	The company's side of the story. `vendor` = its product is being discussed; `buyer` = it is doing the evaluating/adopting; `subject` = the event happened to it
`stage`	string \| null	How far along, or how solid. Funnel subtypes use funnel values (`considering` → `switched`); event subtypes use the evidence ladder (`speculative` → `confirmed`). See the subtype accordion for each vocabulary. This is your main precision filter
`category`	string \| null	The subtype's finer classification (e.g. `pricing` vs `reliability` inside `customerFeedback`). `null` on subtypes that define no categories
`sentiment`	string	`positive`, `neutral`, `negative`, or `mixed` - the thread's tone toward THIS company, not the thread's overall mood
`prominence`	string	`core` = the thread is about this signal, or the author reports it first-hand. `aside` = a passing mention: a commenter's recommendation, an old event recalled, background context. Roughly a third of signals are asides - they are real information, labeled so you can weight them
`timing`	string \| null	When the described thing happens relative to the post: `ongoing_state` (a standing situation), `in_progress` (happening now), `completed` (already happened - even years ago), `planned` (announced for the future). Omitted when none fits
`event_date`	string \| null	Best-estimate month, `YYYY-MM` or `YYYY`. Relative phrases ("yesterday", "last week") are anchored to the post date. `null` when no date is derivable - we never invent one. Pair with `timing`: `completed` + an old `event_date` = history, not news
`event_date_text`	string \| null	The raw temporal phrase from the thread ("effective October 1"). Present on most dated signals; useful for display
`people`	array	Real named humans relevant to this signal: `{ name, title, employer, role }` with role `actor` (the person the signal is about) or `mentioned`. Reddit usernames never appear here
`details`	object	Only on `leadershipChange`: `{ person_name, title, direction: "joins" \| "leaves" }`
`topics`	array	Up to 5 short lowercase tags (`pricing`, `migration`, `ai`) for faceting
`products_mentioned`	array	The company's own product lines named in the thread (`"M365"`, `"Lambda"`)
`evidence`	array	1–3 verbatim quotes supporting the signal, each prefixed with its source: `[post]`, `[comment u/<name>]`, or `[image]`. This is the checkability guarantee - every claim is one click from its evidence via `source_url`
`other_companies`	array	Every other company in the conversation with its relationship to this one: `competitor`, `alternative`, `incumbent`, `switching_to`, `adopted`, `replaced`, `acquirer`, `target`, `partner` - each with its resolved `domain` when available. A churn signal's `switching_to` entry tells you who won the deal
`source_url`	string	Canonical thread permalink. Append `.json` for Reddit's public JSON of the full thread
`post_id`, `post_title`, `post_text`	string	Thread identity, title, and body (up to 5,000 chars - the same text our extractor read, shipped for verification)
`post_kind`	string	What kind of post: `text`, `image`, `link`, `multi_media`, `hosted:video`. Image posts may carry the content in pixels - see `image_read_by_model`
`link_url`, `image_url`	string \| null	The external link or image for non-text posts
`image_read_by_model`	boolean	`true` when the extractor read the attached image (screenshots of outage banners, pricing emails, etc.)
`subreddit`, `subreddit_url`	string	The source community
`post_date`	string (ISO 8601)	When the thread was posted - the conversation's real timestamp. Use this for recency, not `detected_at`
`post_flair`	array	The thread's flair labels, when set
`post_author`, `post_author_url`, `post_author_id`	string	The poster's handle, profile URL, and stable `t2_` ID. Provenance only - we never resolve Reddit users to real identities
`total_upvotes`, `total_comments`, `upvote_ratio`, `awards`	number	Thread engagement at collection time. High engagement = the market is watching this conversation
`virality`	string	Engagement percentile bucket relative to that week's whole corpus (`low` → `very_high`) - "viral" always means viral for that week
`mention_count`	number	How many distinct threads named this company in the same run
`mention_surge`	boolean	`true` at `mention_count` ≥ 3 - the company is a topic across communities (common during outages and pricing changes)
`related_post_urls`	array	Up to 10 other threads mentioning the same company that run
`comments`	array	Up to 20 top comments (author, score, depth, timestamp, permalink, 400-char excerpt) - the discussion context, shipped so you can verify tone and claims without leaving the record
`comments_total`, `comments_included`	number	The thread's full comment count vs how many ship here
`nsfw`	boolean	Reddit's own over-18 flag for the thread. Effectively always `false` in our vetted business communities
`content_warning`	string \| null	`"profanity_in_quotes"` when the summary or evidence text contains profanity. Check this before piping quotes verbatim into outreach copy

Quality Metadata (`_qa`)

Machine-measured quality facts. Filter on these instead of trusting a single score.

Field	Type	Description
`validation_issues`	array	Non-blocking QA notes recorded at extraction time (empty on clean records)
`resolution`	string	Company resolution outcome: `resolved`/`candidate` (domain returned and accepted), `unresolved`/`abstained` (no confident match - domain is `null`), `not_attempted`
`margin`	number \| null	The resolver's decision margin, when it reports one
`triage_interest`	number	0–1 actionability score from triage. Higher = more concrete and seller-actionable. A cheap precision dial: `>= 0.7` keeps the sharpest third
`vet`	object \| null	Present on risky signals (events, asides): an independent automated second review. Contains per-check booleans (entity in source, subtype fit, stage fit, prominence fit, summary faithful), a `verdict` of `ok` or `flag`, and a short `reason`. `flag` means our reviewer disagrees with something - shipped anyway, labeled, so you can decide

Coverage

Communities: 500+ hand-vetted business subreddits across IT & infrastructure, security, data/AI, software engineering, e-commerce & retail, marketing, sales & CS, finance & accounting, HR & legal, healthcare, construction & trades, manufacturing, energy, logistics - plus dedicated regional coverage (UK & Ireland, DACH, France & Benelux, Nordics, Iberia & LATAM, India, Australia & NZ, Canada, SEA & Japan/Korea, MEA). Per-community yield is re-measured every run; communities that stop producing get pruned.
Standing searches: 150+ probe-verified queries catch signals outside the curated communities.
Cadence: weekly (week ending Sunday), with historical weeks backfilled. Deduplication is guaranteed: a signal ships once, under a stable ID, and re-ships only when its evidence strengthens (a rumor upgrading to confirmed).
Quality machinery: automated review of every risky signal at production time, tripwire gates on every run, and independent AI audits that grade weekly batches field-by-field before delivery.

Legacy docs: the previous Reddit page described the earlier company-seeded Reddit product and is retained (hidden) for reference.