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Deliver proprietary market signals through API

Integrate TickerTrends signal workflows directly into your dashboards, models, alerts, and research systems without forcing your team into another tool.

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Signal payloads

Consumer demand, B2B demand, company mapping, competitor movement, and KPI context.

Alerts and changes

Deliver acceleration, persistence, divergence, and coverage updates into internal tools.

Custom workflows

Build around your universe, taxonomy, watchlists, reporting cadence, and model inputs.

TickerTrends API Offerings

TickerTrends is focused on pre-purchase intelligence, measuring demand signals and event-driven changes before they are reflected in reported financials or transaction data. Our API products help teams quantify how consumer, enterprise, social, and business events may translate into company-level financial impact.

TickerTrends Trackers Feed

Standardized time-series trackers across consumer usage, consumer interest, social interest, ecommerce demand, developer activity, and other demand signals.

  • Historical time series
  • Comparable across companies

Data Source KPI Feed

Underlying source-level KPIs, tickerized and structured for deeper analysis and custom research workflows.

  • Source-specific metrics
  • Useful for custom modeling

KPI Forecast Feed

TickerTrends KPI forecast outputs with revision history for revenue, KPIs, and other tracked business metrics.

  • Latest forecast values
  • Revision direction and velocity

Social Discussion Feed

Structured discussion data tracking what products, brands, and companies are gaining or losing attention across virtually all major social channels, with regional coverage across countries.

  • Volume and growth
  • Topic, narrative, and regional tracking

Catalyst Feed

Detect emerging products, platform shifts, launches, partnerships, campaigns, and events that may become company-level catalysts across sectors.

  • Consumer, B2B, TMT, etc.
  • Event and launch monitoring
Coming this month

TickerTrends MCP

Connect TickerTrends data directly into AI-enabled research workflows through a structured MCP layer for fast retrieval and analysis.

  • Natural-language data access
  • Designed for AI tooling

Event Impact Model

Input any event and receive a structured output defining expected impact on a target reported company metric.

  • Event-to-metric mapping
  • Impact before financials / transactions

Forecasting Model API

Flexible model layer for converting structured demand data into KPI forecasts.

  • Flexible input structures
  • Forecast output + context
S3 deliverySnowflake deliveryMCP deliveryPricing: admin@tickertrends.io
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Built for Research dashboards · Watchlists and alerts · Backtesting · Internal data pipelines

Try it live below

API delivery for the signals your team already uses

Start with covered signal payloads, then extend into custom company, product, competitor, and KPI models. The API is built for teams that need repeatable delivery into existing research and operating systems.

Example demand signal payload

Weekly intent signal for a tracked product term.

+28.4% 90D

Example response

Payloads can include raw values, signal scores, acceleration, persistence, peer comparison, and timestamps.

{
  "status": "success",
  "signal": {
    "entity": "Hoka",
    "type": "consumer_demand",
    "period": "weekly",
    "intent_volume": 142830,
    "acceleration_90d": 0.284,
    "persistence_score": 82,
    "peer_divergence": 0.17,
    "kpi_readthrough": ["traffic", "unit_demand"]
  }
}
  • Standard endpoints for covered trackers
  • Custom payloads for your research tools
  • Exports for research, alerts, and model inputs

Build signal delivery into your existing workflow

The API service is designed for teams that already know where the answer needs to land: a model, a dashboard, a data warehouse, a weekly report, or an alert workflow.

Request
Response
import requests

base_url = "https://api.tickertrends.io/signals"
entity = "HOKA"
api_key = "your_api_key"

url = f"{base_url}?entity={entity}&signal_type=consumer_demand"
headers = {"Authorization": f"Bearer {api_key}"}

response = requests.get(url, headers=headers)

if response.status_code == 200:
    data = response.json()
    print("Data received:", data)
else:
    print(f"Failed to retrieve data. Status code: {response.status_code}")
    print("Error message:", response.text)

Common API workflows

Push demand and KPI signals into internal dashboards
Route acceleration alerts to research or operating teams
Export company and competitor mappings for your coverage universe
Use signal fields as inputs for forecasting and screening models

Need custom API access?

Tell us what universe, signal fields, cadence, and delivery format your team needs.

Contact us