Earnings Transcript

Trends extracted from a company's earnings transcript.

Overview

Earnings Transcripts capture what executives say on quarterly earnings calls—the most candid public statements about a company's priorities, challenges, and investments.

We ingest transcripts from 4,000+ public companies on a weekly basis. Our model scans the full transcript—CEO remarks, CFO commentary, and analyst Q&A—to extract signals across 40+ subtypes. A single transcript typically produces 5-15 signals, each with direct quotes and speaker attribution. We prioritize statements with dollar amounts, percentages, or explicit commitments over generic commentary.

Available Subtypes

Subtype EnumCategoryDescription
acquisitionActivitygrowthM&A activity-acquiring or being acquired
aiInvestmentbudgetAI/ML specific investment or priority
budgetbudgetGeneral budget discussion
budgetAndSpendingbudgetBudget and spending discussion
budgetGrowthbudgetBudget growth mentioned
budgetIncreasebudgetSpecific budget increase announced
capexDecreasebudgetCapital expenditure decrease announced
capexIncreasebudgetMajor capital expenditure increase announced
cloudInvestmentbudgetCloud infrastructure/migration investment
competitiveIntelligencecompetitiveCompetitive dynamics discussed
competitivePressurepainCompetitive threats or market share loss
competitorMentioncompetitiveCompetitor explicitly mentioned
costPressurepainCost/margin pressures discussed
customerExperienceFocusstrategicCustomer experience improvement priority
customerGrowthgrowthCustomer base expanding significantly
customerWingrowthSignificant customer win announced
dataInvestmentbudgetData infrastructure/analytics investment
digitalTransformationstrategicDigital transformation initiative
efficiencyFocusstrategicOperational efficiency as priority
growthSignalgrowthGeneral growth indicator
guidanceLowerstrategicFinancial guidance lowered
guidanceRaisestrategicFinancial guidance raised
headcountGrowthgrowthSignificant hiring or workforce expansion
investmentCommitmentbudgetSpecific investment commitment announced
layoffsorganizationalWorkforce reduction announced
leadershipChangeorganizationalNew C-level executive or leadership change
marketExpansiongrowthGeographic or market segment expansion
marketShareGaingrowthGaining market share
marketShareLosscompetitiveLosing market share
organizationalChangeorganizationalOrganizational structure changes
painPointpainGeneral pain point identified
productLaunchgrowthNew product or service announcement
regulatoryPressurepainRegulatory compliance challenges
restructuringorganizationalOrganizational restructuring
revenueAccelerationgrowthRevenue growth rate increasing
scalingChallengepainScaling or capacity constraints
securityInvestmentbudgetCybersecurity investment or priority
strategicInitiativestrategicStrategic initiative announced
strategicInitiativesstrategicMultiple strategic initiatives discussed
strategicPartnershipgrowthStrategic partnership announced
supplyChainPainpainSupply chain challenges mentioned
sustainabilityFocusstrategicESG or sustainability initiative
talentChallengepainHiring or talent retention challenges
techBudgetGrowthbudgetTechnology/IT budget explicitly growing
techDebtPainpainLegacy systems or technical debt mentioned
techInvestmentbudgetGeneral technology investment
vendorSelectionbudgetVendor evaluation or selection process mentioned

Signal Categories

Signals are organized into these categories:

CategoryDescription
budgetCompanies actively investing-indicates available budget
growthCompanies expanding-increased operational needs
painChallenges mentioned-opportunity to solve
strategicWhat executives explicitly prioritize
organizationalTiming opportunities from internal changes
competitiveMarket positioning insights

Schema

{
  "signal_id": "34c1d2c0bd4d9d70",
  "signal_type": "earnings-transcript",
  "signal_subtype": "investmentCommitment",
  "signal_name": "DICK'S Sporting Goods allocating $500M-$750M for Foot Locker turnaround, including tech asset review.",
  "detected_at": "2026-01-10T14:30:00Z",
  "association": "company",
  "batch_id": "batch-701b83d1",
  "company": {
    "name": "DICK'S Sporting Goods, Inc.",
    "domain": "dickssportinggoods.com",
    "linkedin_url": "linkedin.com/company/dicks-sporting-goods",
    "financial_symbol": "DKS",
    "industries": [
      "Specialty Retail"
    ],
    "sector": "Consumer Cyclical"
  },
  "data": {
    "fiscal_period": "Q3",
    "fiscal_year": 2025,
    "earnings_date": "2026-01-08T08:00:00Z",
    "signal_category": "budget",
    "sales_relevance": "Long-term commitment = sustained vendor opportunities",
    "relevance": 1.0,
    "confidence": "high",
    "sentiment": "positive",
    "headline": "Allocating $500M-$750M for Foot Locker turnaround, including tech asset review.",
    "detail": "A massive budget has been allocated for the Foot Locker integration, explicitly including a review of existing technology assets and legacy contracts. This creates a time-sensitive opportunity for new vendors.",
    "evidence": [
      "We expect these actions, along with other merger and integration costs to result in a future pretax charge of between $500 million and $750 million.",
      "We are looking deeper into the assets that we have in place, some of the technology assets, some of the legacy contracts that we will evaluate."
    ],
    "evidence_speakers": [
      {
        "speaker_name": "Navdeep Gupta",
        "speaker_title": "Chief Financial Officer"
      }
    ],
    "competitors_mentioned": [],
    "vendors_mentioned": [],
    "technologies_mentioned": [],
    "regions": [],
    "metric_dollar_millions": 750,
    "metric_pct": null,
    "metric_headcount": null
  }
}

Field Reference

Core Fields

FieldTypeRequiredDescription
signal_idstringUnique identifier for this signal
signal_typestringAlways "earnings-transcript"
signal_subtypestringSpecific signal subtype (see subtypes list)
signal_namestringHuman-readable signal headline with company name
detected_atstring (ISO 8601)Timestamp when the signal was extracted
associationstringAlways "company"
batch_idstringProcessing batch identifier

Company Object

FieldTypeRequiredDescription
company.namestringCompany name
company.domainstringCompany website domain
company.linkedin_urlstring (URL)LinkedIn company page URL
company.financial_symbolstringStock ticker symbol (note - different field name from SEC filings)
company.industriesarray[string]Industry classifications
company.sectorstringBusiness sector

Data Object

FieldTypeRequiredDescription
data.fiscal_periodstringFiscal quarter (Q1, Q2, Q3, Q4)
data.fiscal_yearintegerFiscal year
data.earnings_datestring (ISO 8601)Date of earnings call
data.signal_categorystringCategory grouping (budget, growth, pain, etc.) (budget, competitive, growth, guidance, organizational, pain, partnership, priority)
data.sales_relevancestringSales opportunity context
data.relevancefloat (0.0-1.0)Business relevance score
data.confidencestringConfidence level in the signal accuracy (high, medium, low)
data.sentimentstringSentiment of the signal (positive, negative, neutral)
data.headlinestringConcise insight summary
data.detailstringDetailed explanation
data.evidencearray[string]Direct quotes from transcript
data.evidence_speakersarray[object]Speaker attribution for each quote
data.competitors_mentionedarray[string]Competitors mentioned
data.vendors_mentionedarray[string]Vendors mentioned
data.technologies_mentionedarray[string]Technologies/products mentioned
data.regionsarray[string]Geographic regions mentioned
data.metric_dollar_millionsfloatDollar amount in millions
data.metric_pctfloatPercentage as decimal (e.g., 0.15 = 15%)
data.metric_headcountinteger (nullable)Headcount number

Data Activation

Timing

detected_at is when Autobound processed the transcript. Use data.earnings_date for when the call actually occurred - this is the authoritative event timestamp. Transcripts typically become available 1-7 days after the call.

Uniqueness

One signal per subtype per company per earnings call. A single call can produce 5-15 signals across different subtypes (budget, growth, pain, etc.).

Delivery

Each delivery arrives in a timestamped folder. Signals in that folder cover the window between this delivery and the previous one. Treat all signals in a new folder as recent and actionable—no need to diff against prior deliveries.

Best Practices

  • Filter on relevance and confidence both above 0.9 for high-precision use cases
  • Build picklists from signal_subtype values
  • Use data.earnings_date to calculate freshness: detected_at - earnings_date
  • Use evidence_speakers for routing signals by executive role (CFO statements to finance teams, etc.)

API Usage

Generate Content API

{
  "enabledInsights": [
    "capexIncrease",
    "aiInvestment",
    "strategicInitiative"
  ],
  "disabledInsights": []
}

Generate Insights API

{
  "insightSubtype": "capexIncrease"
}

Example Output

"Noticed in DICK'S Sporting Goods' Q3 earnings call that you're allocating $500-750M for the Foot Locker integration, including a tech asset review. That's a significant investment and a tight timeline—would love to share how we're helping similar retailers streamline their M&A integrations."

Coverage

  • Refresh: Quarterly
  • Coverage: 4,000+ public companies
  • Best for: Enterprise sales, Executive outreach, Strategic account planning