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.

We process episodes across a large catalog of business and industry shows, transcribe them, and extract structured signals attributed to the specific person speaking. Each appearance is classified into one of 50 subtypes (funding, hiring, executive opinions, strategy shifts, pain points, and more), with the supporting quotes, the entities they referenced, and scores for relevance and confidence.

The result: you know exactly what a buyer believes, what they're investing in, and which competitors they're weighing—giving you 30-60 minutes of their own words to reference in outreach.

Available Subtypes

Subtype Enum	Category	Description
`acquisitionAnnounced`	strategic	Company announces intent or agreement to acquire another company
`acquisitionCompleted`	strategic	Company completes an acquisition
`aiInvestment`	technology	Company investing in AI capabilities, models, or tooling
`automationInvestment`	technology	Company 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

Signal Categories

Each signal carries a data.signal_category assigned by the extraction model. Categories are thematic groupings, not a closed enum; the most common are:

Category	Description
`financial`	Funding, capex, cost, margin, debt, and other money movements
`revenue`	Wins, losses, and shifts in revenue trajectory
`strategic`	M&A, partnerships, divestitures, and strategy shifts
`operations`	Capacity, supply chain, logistics, expansion, and quality
`workforce`	Hiring, layoffs, and labor supply
`leadership`	Executive and board changes, executive opinions
`technology`	Product launches, tech adoption, migrations, and IT investment
`market`	Market moves, industry predictions, and sustainability
`risk`	Security, litigation, compliance, churn, and disclosed concerns
`competitive`	Competitor mentions, pricing pressure, and market-share moves

Schema

{
  "signal_id": "d2f5a8b1-4c6e-5a90-b3c7-8e1f2a3b4c5d",
  "signal_type": "podcast-contact",
  "signal_subtype": "executiveOpinion",
  "detected_at": "2026-07-18T00:00:00Z",
  "association": "contact",
  "episode_id": "acqrd-2026-07-18-the-data-stack-show-ep-98",
  "parent_signal_id": null,
  "company": {
    "name": "Snowflake",
    "domain": "snowflake.com",
    "description": "Cloud data platform for storage, analytics, and data sharing.",
    "employee_count_low": 5001,
    "employee_count_high": 10000,
    "industries": [
      "Software Development",
      "Data Infrastructure And Analytics"
    ],
    "linkedin_url": "linkedin.com/company/snowflake-computing"
  },
  "contact": {
    "name": "Marcus Reyes",
    "first_name": "Marcus",
    "last_name": "Reyes",
    "job_title": "VP of Data Platform",
    "email": null,
    "linkedin_url": "linkedin.com/in/marcus-reyes"
  },
  "data": {
    "podcast_name": "The Data Stack Show",
    "episode_title": "Why the warehouse is becoming the application layer",
    "episode_url": "https://example.com/podcasts/data-stack-show/98",
    "headline": "Snowflake's VP of Data Platform says teams should stop copying data out of the warehouse",
    "detail": "As a guest, Marcus argued that reverse-ETL and app-in-warehouse patterns will replace most data copying within two years, and described an internal push to run ML workloads directly on the platform.",
    "evidence": [
      {
        "speaker_name": "Marcus Reyes",
        "speaker_title": "VP of Data Platform",
        "speaker_company": "Snowflake",
        "role": "guest",
        "quotes": [
          "If you're still shipping copies of your data to five different tools, you're going to lose the next two years to plumbing.",
          "We're moving the compute to the data, not the other way around."
        ]
      }
    ],
    "entities_referenced": [
      {
        "name": "Databricks",
        "domain": "databricks.com",
        "relationship": "competitor",
        "context": "Referenced when comparing lakehouse architectures",
        "headline": "Contrasted Snowflake's approach with Databricks",
        "detail": "Marcus compared platform strategies without naming a winner."
      }
    ],
    "source": {
      "episode_date": "2026-07-18T00:00:00Z",
      "podcast_popularity": 0.64
    },
    "entity_type": "individual",
    "entity_role": "guest",
    "signal_category": "technology",
    "relevance": 0.87,
    "confidence": "high",
    "sentiment": "neutral",
    "is_ad": false,
    "metric_dollar_millions": null,
    "metric_pct": null
  }
}

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	✓	Specific signal subtype (see allowed values above)
`detected_at`	string (ISO 8601)	✓	Episode publication date
`association`	string	✓	Entity association type - always "contact"
`episode_id`	string	✓	Source podcast episode identifier (dedup key)
`parent_signal_id`	string (UUID)		Parent signal when this was expanded from a referenced entity; otherwise null

Company Object

Field	Type	Required	Description
`company.name`	string	✓	Company discussed or appearing
`company.domain`	string	✓*	Company domain (primary match key)
`company.linkedin_url`	string (URL)	✓*	Company LinkedIn URL (alternate match key)
`company.description`	string		Company description
`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

^{*A company signal requires at least one of domain or linkedin_url.}

Contact Object

Field	Type	Required	Description
`contact.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 at time of appearance
`contact.email`	string	✓*	Work email (match key)
`contact.linkedin_url`	string (URL)	✓*	Contact LinkedIn URL (match key)

^{*A contact signal requires at least one of email or linkedin_url.}

Data Object

Field	Type	Required	Description
`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.headline`	string	✓	One-line takeaway (≤120 chars)
`data.detail`	string	✓	Fuller description of what was said and why it matters
`data.evidence`	array[object]	✓	Supporting quotes with speaker attribution (see Evidence Object)
`data.entities_referenced`	array[object]		Other companies/entities named in the discussion (see Entity Object)
`data.source`	object		Episode metadata (see Source Object)
`data.entity_type`	string		Type of entity the signal is about (`company`, `government`, `organization`, `individual`)
`data.entity_role`	string		Role in the episode (`guest`, `mentioned`)
`data.signal_category`	string		Model-assigned theme for the signal (see Signal Categories)
`data.relevance`	float		Relevance / actionability score (0.0-1.0)
`data.confidence`	string		Extraction confidence (`high`, `medium`, `low`)
`data.sentiment`	string		Sentiment of the mention (`positive`, `neutral`, `negative`)
`data.is_ad`	boolean		Whether the mention came from an ad/sponsor read
`data.metric_dollar_millions`	float		Dollar figure referenced, in millions USD (when stated)
`data.metric_pct`	float		Percentage figure referenced (when stated)

Evidence Object

Field	Type	Description
`evidence[].speaker_name`	string	Name of the person quoted
`evidence[].speaker_title`	string	Speaker's job title
`evidence[].speaker_company`	string	Speaker's company
`evidence[].role`	string	Speaker role (`guest`, `host`, `analyst`, `correspondent`)
`evidence[].quotes`	array[string]	Verbatim quotes supporting the signal

Entity Object (`entities_referenced[]`)

Field	Type	Description
`entities_referenced[].name`	string	Name of the referenced entity
`entities_referenced[].domain`	string	Domain of the referenced entity (nullable)
`entities_referenced[].relationship`	string	Relationship to the subject (`vendor`, `new_vendor`, `former_vendor`, `displaced_vendor`, `replacement_vendor`, `customer`, `former_customer`, `competitor`, `partner`, `acquisition_target`, `acquirer`, `vendor_evaluated`, `investor`, `other`)
`entities_referenced[].context`	string	Why the entity was mentioned
`entities_referenced[].headline`	string	One-line takeaway about the referenced entity
`entities_referenced[].detail`	string	Fuller description of the reference

Source Object

Field	Type	Description
`source.episode_date`	string (ISO 8601)	Publication date of the episode
`source.podcast_popularity`	float	Relative popularity of the show (0.0-1.0)

Coverage

Refresh: Monthly
Association: Contact-level
Subtypes: 50

Next: Data Activation Guide — Playbooks for turning podcast signals into personalized outreach and competitive intelligence.