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 Enum | Category | Description |
|---|---|---|
acquisitionActivity | growth | M&A activity-acquiring or being acquired |
aiInvestment | budget | AI/ML specific investment or priority |
budget | budget | General budget discussion |
budgetAndSpending | budget | Budget and spending discussion |
budgetGrowth | budget | Budget growth mentioned |
budgetIncrease | budget | Specific budget increase announced |
capexDecrease | budget | Capital expenditure decrease announced |
capexIncrease | budget | Major capital expenditure increase announced |
cloudInvestment | budget | Cloud infrastructure/migration investment |
competitiveIntelligence | competitive | Competitive dynamics discussed |
competitivePressure | pain | Competitive threats or market share loss |
competitorMention | competitive | Competitor explicitly mentioned |
costPressure | pain | Cost/margin pressures discussed |
customerExperienceFocus | strategic | Customer experience improvement priority |
customerGrowth | growth | Customer base expanding significantly |
customerWin | growth | Significant customer win announced |
dataInvestment | budget | Data infrastructure/analytics investment |
digitalTransformation | strategic | Digital transformation initiative |
efficiencyFocus | strategic | Operational efficiency as priority |
growthSignal | growth | General growth indicator |
guidanceLower | strategic | Financial guidance lowered |
guidanceRaise | strategic | Financial guidance raised |
headcountGrowth | growth | Significant hiring or workforce expansion |
investmentCommitment | budget | Specific investment commitment announced |
layoffs | organizational | Workforce reduction announced |
leadershipChange | organizational | New C-level executive or leadership change |
marketExpansion | growth | Geographic or market segment expansion |
marketShareGain | growth | Gaining market share |
marketShareLoss | competitive | Losing market share |
organizationalChange | organizational | Organizational structure changes |
painPoint | pain | General pain point identified |
productLaunch | growth | New product or service announcement |
regulatoryPressure | pain | Regulatory compliance challenges |
restructuring | organizational | Organizational restructuring |
revenueAcceleration | growth | Revenue growth rate increasing |
scalingChallenge | pain | Scaling or capacity constraints |
securityInvestment | budget | Cybersecurity investment or priority |
strategicInitiative | strategic | Strategic initiative announced |
strategicInitiatives | strategic | Multiple strategic initiatives discussed |
strategicPartnership | growth | Strategic partnership announced |
supplyChainPain | pain | Supply chain challenges mentioned |
sustainabilityFocus | strategic | ESG or sustainability initiative |
talentChallenge | pain | Hiring or talent retention challenges |
techBudgetGrowth | budget | Technology/IT budget explicitly growing |
techDebtPain | pain | Legacy systems or technical debt mentioned |
techInvestment | budget | General technology investment |
vendorSelection | budget | Vendor evaluation or selection process mentioned |
Signal Categories
Signals are organized into these categories:
| Category | Description |
|---|---|
budget | Companies actively investing-indicates available budget |
growth | Companies expanding-increased operational needs |
pain | Challenges mentioned-opportunity to solve |
strategic | What executives explicitly prioritize |
organizational | Timing opportunities from internal changes |
competitive | Market 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
| Field | Type | Required | Description |
|---|---|---|---|
signal_id | string | ✓ | Unique identifier for this signal |
signal_type | string | ✓ | Always "earnings-transcript" |
signal_subtype | string | ✓ | Specific signal subtype (see subtypes list) |
signal_name | string | Human-readable signal headline with company name | |
detected_at | string (ISO 8601) | ✓ | Timestamp when the signal was extracted |
association | string | ✓ | Always "company" |
batch_id | string | Processing batch identifier |
Company Object
| Field | Type | Required | Description |
|---|---|---|---|
company.name | string | ✓ | Company name |
company.domain | string | ✓ | Company website domain |
company.linkedin_url | string (URL) | LinkedIn company page URL | |
company.financial_symbol | string | Stock ticker symbol (note - different field name from SEC filings) | |
company.industries | array[string] | Industry classifications | |
company.sector | string | Business sector |
Data Object
| Field | Type | Required | Description |
|---|---|---|---|
data.fiscal_period | string | Fiscal quarter (Q1, Q2, Q3, Q4) | |
data.fiscal_year | integer | Fiscal year | |
data.earnings_date | string (ISO 8601) | Date of earnings call | |
data.signal_category | string | Category grouping (budget, growth, pain, etc.) (budget, competitive, growth, guidance, organizational, pain, partnership, priority) | |
data.sales_relevance | string | Sales opportunity context | |
data.relevance | float (0.0-1.0) | Business relevance score | |
data.confidence | string | Confidence level in the signal accuracy (high, medium, low) | |
data.sentiment | string | Sentiment of the signal (positive, negative, neutral) | |
data.headline | string | Concise insight summary | |
data.detail | string | Detailed explanation | |
data.evidence | array[string] | Direct quotes from transcript | |
data.evidence_speakers | array[object] | Speaker attribution for each quote | |
data.competitors_mentioned | array[string] | Competitors mentioned | |
data.vendors_mentioned | array[string] | Vendors mentioned | |
data.technologies_mentioned | array[string] | Technologies/products mentioned | |
data.regions | array[string] | Geographic regions mentioned | |
data.metric_dollar_millions | float | Dollar amount in millions | |
data.metric_pct | float | Percentage as decimal (e.g., 0.15 = 15%) | |
data.metric_headcount | integer (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
relevanceandconfidenceboth above 0.9 for high-precision use cases - Build picklists from
signal_subtypevalues - Use
data.earnings_dateto calculate freshness:detected_at - earnings_date - Use
evidence_speakersfor 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
Updated 2 days ago
