Podcast Appearances (Contact)

Overview

Podcast Appearances (Contact) capture the moments a prospect goes on the record—what an executive actually said on a podcast, in their own words, attributed to the specific person speaking.

We process episodes across a large catalog of business and industry shows, transcribe them, and extract structured signals tied to the individual contact. Each signal carries the supporting quotes and our confidence in when it took place.

There are two flavors of contact signal, distinguished by signal_subtype:

Appearance signals — signal_subtype: "podcastAppearance". A profile of the contact's appearance: the host, the topics covered, the occasion, their key talking points (each with a supporting quote), and a snapshot of what their company does.
Themed-claim signals — any of the themed subtypes below (e.g. aiInvestment, fundingEvent, techAdoption). A single discrete claim attributed to the contact, with the quotes, speaker relationship, and event timing that back it. This is the same shape used by Podcast Mentions (Company).

The data object differs between the two—see Data Object below.

Available Subtypes

signal_subtype is either podcastAppearance or one of the themed values below. The Category column is an organizational grouping for readability only—it is not a field in the payload.

Subtype Enum	Category	Description
`podcastAppearance`	appearance	A general appearance/interview by the contact (appearance shape)
`acquisitionAnnounced`	strategic	Company announces intent or agreement to acquire another company
`acquisitionCompleted`	strategic	Company completes an acquisition
`aiInvestment`	technology	Investing in AI capabilities, models, or tooling
`automationInvestment`	technology	Investing in process or workflow automation
`boardChange`	leadership	Change to the company's board of directors
`capacityConstraint`	operations	Production or service capacity limits
`capexIncrease`	financial	Increase in capital expenditure
`cashFlowConcern`	risk	Cash-flow pressure or liquidity concern
`channelShift`	strategic	Shift in go-to-market or distribution channels
`cloudInvestment`	technology	Investment in cloud infrastructure or migration
`competitorNamed`	competitive	A competitor is explicitly named or compared
`complianceBurden`	risk	Regulatory or compliance burden discussed
`costReduction`	financial	Cost-cutting or efficiency initiative
`customerChurn`	risk	Customer churn or account losses discussed
`cybersecurityInvestment`	technology	Investment in security tooling or programs
`dataInvestment`	technology	Investment in data infrastructure or analytics
`digitalTransformation`	technology	Broad digital-transformation initiative
`executiveOpinion`	leadership	An executive shares a notable opinion or point of view
`expansion`	operations	General business expansion
`fundingEvent`	financial	Funding round or capital raise
`growthSignal`	revenue	General growth indicator
`hiringSignal`	workforce	Hiring or headcount growth
`industryPrediction`	market	Prediction about industry direction or the future
`inflationImpact`	risk	Impact of inflation on the business
`internationalGrowth`	operations	Expansion into international markets
`inventoryIssue`	operations	Inventory problem (excess or shortage)
`laborShortage`	workforce	Labor or talent shortage
`layoffs`	workforce	Workforce reductions
`leadershipChange`	leadership	Leadership change other than CEO or CTO
`legacyModernization`	technology	Modernizing legacy systems
`litigationMaterial`	risk	Material litigation or legal action
`majorContractLoss`	revenue	Loss of a major contract
`majorContractWin`	revenue	Win of a major contract
`manufacturingIssue`	operations	Manufacturing or production issue disclosed
`marketExpansion`	market	Expansion into new markets or segments
`painPointDisclosed`	risk	A business pain point or challenge disclosed
`partnership`	strategic	Partnership or alliance announced
`platformStrategy`	technology	Platform or ecosystem strategy
`pricingPressure`	competitive	Pricing pressure discussed
`productLaunch`	technology	New product or service launched
`recurringRevenueShift`	revenue	Shift toward a recurring-revenue model
`restructuring`	strategic	Organizational restructuring
`revenueAcceleration`	revenue	Revenue growth accelerating
`softwareImplementation`	technology	Implementing new software or systems
`strategyShift`	strategic	Notable change in company strategy
`supplierConcentration`	risk	Dependence on a small number of suppliers
`supplyChainDisruption`	operations	Supply-chain disruption
`sustainabilityInvestment`	market	Investment in sustainability or ESG
`techAdoption`	technology	Adoption of a new technology
`techMigration`	technology	Migration between technologies or platforms

Schema — Appearance signal (`podcastAppearance`)

{
  "signal_id": "bd785b70-2db0-5a31-a1ff-75f16809fef9",
  "signal_type": "podcast-contact",
  "signal_subtype": "podcastAppearance",
  "signal_name": "Kevin Bognar (Chief Revenue Officer @ Stripe) on The Emblazers Show",
  "detected_at": "2026-08-24T10:25:27.000Z",
  "association": "contact",
  "company": {
    "name": "Stripe",
    "domain": "stripe.com",
    "linkedin_url": "linkedin.com/company/stripe",
    "industries": ["Software Development"],
    "employee_count_low": 10000,
    "employee_count_high": 10000,
    "revenue": "1 Billion and Over",
    "description": "Stripe is a financial infrastructure platform for businesses."
  },
  "contact": {
    "name": "Kevin Bognar",
    "full_name": "Kevin Bognar",
    "first_name": "Kevin",
    "last_name": "Bognar",
    "job_title": "Head of Commercial & SMB Sales - Americas",
    "title": "Head of Commercial & SMB Sales - Americas",
    "email": "[email protected]",
    "linkedin_url": "https://www.linkedin.com/in/kevinjbognar",
    "seniority": "Director",
    "department": "Operations",
    "city": null,
    "state": null,
    "country": null
  },
  "data": {
    "headline": "Kevin Bognar (Chief Revenue Officer @ Stripe) on The Emblazers Show",
    "host": "Tim Riesterer",
    "occasion": "Discussing Stripe's use of AI in their sales process",
    "topics": [
      "AI in sales",
      "Sales leadership",
      "Go-to-market strategy",
      "Sales culture"
    ],
    "talking_points": [
      {
        "point": "AI is crucial for improving sales efficiency and prospecting.",
        "quote": "I would be remiss if I didn't answer that question immediately with how do we use AI to be more efficient ourselves?"
      },
      {
        "point": "Using AI to find ICP twins dramatically shortens sales cycles.",
        "quote": "our average time to close of those create and close opportunities in SMB was 13 days. Now, if the opportunity was created in the prior quarter, it was 76 days."
      },
      {
        "point": "Effective sales leadership requires simplification, predictability, and collaboration.",
        "quote": "as a seller for a long time myself. I just really hated complex, overly engineered things that I was being asked to do. So as a leader, I try to clear the deck of all of that noise so that we can give back more time to be with users"
      }
    ],
    "company_snapshot": {
      "org_facts": ["120-person sales organization"],
      "what_they_do": "Grow the GDP of the internet by making it easier for organizations to do commerce and take payments.",
      "technologies_used": ["Gong", "Salesforce", "JIRA"],
      "customers_mentioned": ["Anthropic"],
      "competitors_mentioned": []
    },
    "evidence": null,
    "is_ad": false,
    "podcast_name": "The Emblazers Show",
    "episode_title": "How to Lead with Authenticity in an AI-Powered Sales Culture",
    "episode_url": "https://theemblazersshow.podbean.com/e/how-to-lead-with-authenticity-in-an-ai-powered-sales-culture/",
    "episode_id": "55660086617",
    "published_at": "2026-06-02",
    "recorded_at_estimate": "2026-05",
    "date_confidence": "inferred",
    "transcript_source": "transcript"
  }
}

Schema — Themed-claim signal (e.g. `partnership`)

{
  "signal_id": "f03d5c52-d91a-5ce3-a926-602c5b91ea6c",
  "signal_type": "podcast-contact",
  "signal_subtype": "partnership",
  "signal_name": "Stripe · partnership · ongoing_state (2026-05)",
  "detected_at": "2026-08-24T10:25:27.000Z",
  "association": "contact",
  "company": {
    "name": "Stripe",
    "domain": "stripe.com",
    "linkedin_url": "linkedin.com/company/stripe",
    "industries": ["Software Development"],
    "employee_count_low": 10000,
    "employee_count_high": 10000,
    "revenue": "1 Billion and Over",
    "description": "Stripe is a financial infrastructure platform for businesses."
  },
  "contact": {
    "name": "Kevin Bognar",
    "full_name": "Kevin Bognar",
    "first_name": "Kevin",
    "last_name": "Bognar",
    "job_title": "Head of Commercial & SMB Sales - Americas",
    "title": "Head of Commercial & SMB Sales - Americas",
    "email": "[email protected]",
    "linkedin_url": "https://www.linkedin.com/in/kevinjbognar",
    "seniority": "Director",
    "department": "Operations",
    "city": null,
    "state": null,
    "country": null
  },
  "data": {
    "headline": "Stripe · partnership · ongoing_state (2026-05)",
    "speaker": "Kevin Bognar",
    "speaker_relation": "own_company",
    "quotes": [
      "Anthropik's a great customer and partner, and I tend to agree with them."
    ],
    "evidence": "Anthropik's a great customer and partner, and I tend to agree with them.",
    "timing": "ongoing_state",
    "event_date": "2026-05",
    "is_ad": false,
    "podcast_name": "The Emblazers Show",
    "episode_title": "How to Lead with Authenticity in an AI-Powered Sales Culture",
    "episode_url": "https://theemblazersshow.podbean.com/e/how-to-lead-with-authenticity-in-an-ai-powered-sales-culture/",
    "episode_id": "55660086617",
    "published_at": "2026-06-02",
    "recorded_at_estimate": "2026-05",
    "date_confidence": "inferred",
    "transcript_source": "transcript"
  }
}

Field Reference

Core Fields

Field	Type	Required	Description
`signal_id`	string (UUID)	✓	Unique identifier for this signal
`signal_type`	string	✓	Always `"podcast-contact"`
`signal_subtype`	string	✓	`podcastAppearance` or a themed value (see allowed values above)
`signal_name`	string	✓	Human-readable label for the signal (mirrors `data.headline`)
`detected_at`	string (ISO 8601)	✓	When Autobound detected/ingested the signal (not the episode date—see `data.published_at`)
`association`	string	✓	Entity association type—always `"contact"`
`company`	object	✓	The contact's company (see Company Object)
`contact`	object	✓	The individual the signal is about (see Contact Object)

episode_id is nested under data, not at the top level. There is no parent_signal_id field.

Company Object

Field	Type	Required	Description
`company.name`	string	✓	The contact's company
`company.domain`	string	✓*	Company domain (primary match key)
`company.linkedin_url`	string (URL)	✓*	Company LinkedIn URL (alternate match key)
`company.industries`	array[string]		Industry classifications
`company.employee_count_low`	integer		Lower bound of employee-count range
`company.employee_count_high`	integer		Upper bound of employee-count range
`company.revenue`	string		Revenue band when available via enrichment (e.g. `"1 Billion and Over"`); nullable
`company.description`	string		Company description (nullable)

^{*Requires at least one of domain or linkedin_url.}

Contact Object

Field	Type	Required	Description
`contact.name`	string	✓	Full name of the contact (alias of `full_name`)
`contact.full_name`	string	✓	Full name of the contact
`contact.first_name`	string		First name
`contact.last_name`	string		Last name
`contact.job_title`	string		Job title (alias of `title`)
`contact.title`	string		Job title
`contact.email`	string	✓*	Work email (match key)
`contact.linkedin_url`	string (URL)	✓*	Contact LinkedIn URL (match key)
`contact.seniority`	string		Seniority band via enrichment (`Staff`, `Manager`, `Director`, `Vp`, `Cxo`); nullable
`contact.department`	string		Department via enrichment; nullable
`contact.city`	string		City; nullable
`contact.state`	string		State/region; nullable
`contact.country`	string		Country; nullable

^{*Requires at least one of email or linkedin_url.}

Data Object

Fields shared by both signal flavors:

Field	Type	Required	Description
`data.headline`	string	✓	One-line summary of the signal (mirrors `signal_name`)
`data.is_ad`	boolean	✓	Whether the segment came from an ad / sponsor read
`data.podcast_name`	string	✓	Name of the podcast show
`data.episode_title`	string	✓	Title of the episode
`data.episode_url`	string (URL)		Link to the episode
`data.episode_id`	string	✓	Source podcast episode identifier (dedup key)
`data.published_at`	string (date)	✓	Episode publication date (`YYYY-MM-DD`)
`data.recorded_at_estimate`	string		Best estimate of when the episode was recorded
`data.date_confidence`	string		Confidence in the date fields: `exact` or `inferred`
`data.transcript_source`	string		Origin of the analyzed text (e.g. `transcript`)
`data.evidence`	string		Primary supporting quote; typically `null` for appearance signals

Fields present only on appearance signals (podcastAppearance):

Field	Type	Description
`data.host`	string	Podcast host name
`data.occasion`	string	The occasion / context of the appearance
`data.topics`	array[string]	High-level topics discussed in the episode
`data.talking_points`	array[object]	Key points the contact made (see below)
`data.talking_points[].point`	string	Paraphrased key point
`data.talking_points[].quote`	string	Supporting verbatim quote
`data.company_snapshot`	object	Context about the contact's company gleaned from the episode
`data.company_snapshot.org_facts`	array[string]	Notable facts stated about the company
`data.company_snapshot.what_they_do`	string	What the company does, in the speaker's words (nullable)
`data.company_snapshot.technologies_used`	array[string]	Technologies mentioned as in use
`data.company_snapshot.customers_mentioned`	array[string]	Customers named on the episode
`data.company_snapshot.competitors_mentioned`	array[string]	Competitors named on the episode

Fields present only on themed-claim signals (e.g. aiInvestment):

Field	Type	Description
`data.speaker`	string	Name of the person who made the statement
`data.speaker_relation`	string	Speaker's relationship to the company—e.g. `own_company` or `third_party`
`data.quotes`	array[string]	Verbatim transcript quotes supporting the signal
`data.timing`	string	When the described event occurs relative to the episode—e.g. `ongoing_state`, `in_progress`, `completed`, `planned`
`data.event_date`	string	Best-estimate month of the event (`YYYY-MM`)
`data.event_date_text`	string	Raw temporal phrase from the transcript (e.g. `"these days"`), when present

Coverage

Refresh: Monthly
Association: Contact-level
Subtypes: podcastAppearance + 50 themed values