Reporting Window Finder

🧭 What can Reporting Window Finder do?

Give it a domain, ticker, ISIN, LEI or CIK and it tells you when that public company reports, and when to reach out around it. One flat row per company, built to drop into a Clay column.

Most tools tell you a company is public. This one tells you the fiscal year end, the reporting cadence, the next reporting date, how many days away it is, and the open and close of an outreach window you define yourself.

📦 What you get	⚙️ Features and integrations
🏢 49 identity fields in resolve, 52 in qualify, 51 in universe 📅 80 fields in timing mode 🎯 outreach_window_open and outreach_window_close, your lead and lag 🧾 null never missing, every field always present	🔑 Five identifier types: domain, ticker, ISIN, LEI, CIK 🇺🇸 Timing from SEC filing history, US companies 🧊 24 hour identity cache, timing never cached ⬇️ Export to JSON, CSV, Excel, HTML or XML

Bought by outbound teams timing their sequences around earnings, by investor relations and finance researchers, and by anyone who needs a reporting calendar keyed to identifiers they already have.

🇺🇸 Timing rows cover US companies only. Identity, venue and classification resolve worldwide, across 10,646 publishable companies. The reporting dates come from US SEC filing history and exist for US companies alone. If you send a European or UK company to timing mode, you get its identity and a stated reason, never a guessed date.

💡 Why use this actor?

If you want	Read these fields
The next reporting date	next_event_date, next_event_type, next_event_period
To time outreach around it	outreach_window_open, outreach_window_close, window_status, days_to_event
To know how much to trust the date	confidence_band, confidence_effective, next_event_source_rung
The reporting rhythm	derived_cadence, cadence_confidence, cadence_observation_count
The fiscal calendar	fiscal_year_end_mmdd, fiscal_year_end_month, is_non_calendar_fiscal_year
Company identity	legal_name, primary_ticker, isin, lei, cik, domain
Venue and classification	primary_exchange_code, country_code, sector, security_type
To tell empty from broken	match_method, timing_unavailable_reason, domain_absent_reason

📏 A predicted date is labeled as one

next_event_is_estimate and next_event_is_announced sit on every timing row. A date derived from filing history is an estimate, and the actor says so on the row rather than in the documentation. confidence_band and confidence_effective tell you how much history sat behind it.

The bands sit at 0.80 and 0.50. At or above 0.80 is strong, 0.50 to 0.80 is moderate, below 0.50 is weak. Confidence is computed on the weakest link in the chain: a date is only as good as the cadence it was derived from, so confidence_effective is the minimum of the event and cadence confidences, never an average. Because of that minimum, the 0.75 to 0.80 band is empty by construction. A gap in the distribution is arithmetic, not missing data.

📋 What data does it extract?

Field counts are per mode, read from live runs and the row builders: resolve 49, qualify 52 with its three verdict fields, universe 51, timing 80, and season 22, which are aggregate rows rather than company rows. Within a mode every field is always present, row_status, error_reason and billable_events_json included (added 2026-10-05). A field with nothing behind it is null, never absent, so a Clay column never shifts.

Identity and venue: company_id, legal_name, normalized_name, primary_ticker, isin, lei, cik, domain, primary_exchange_code, country_code, currency, market_segment, listing_count, all_exchange_codes, is_cross_listed, sector, security_type, is_operating_company, is_foreign_private_issuer, is_us_registrant, is_blank_check, is_depositary_receipt, public_float_usd, public_float_band, shares_outstanding.

Timing: fiscal_year_end_mmdd, derived_cadence, next_event_date, next_event_type, next_event_period, next_event_is_estimate, next_event_is_announced, days_to_event, outreach_window_open, outreach_window_close, window_status, constrained_period_open, constrained_period_close, is_in_constrained_period, confidence_band, timing_unavailable_reason.

Also on the rows, by mode:

Field	Meaning
matched_value	Matched Value
identity_basis	Identity Basis
domain_confidence	Domain Confidence
domain_source	Domain Source
fields_limited_by_surface	Fields Limited By Surface
classification_scheme	Classification Scheme
public_float_as_of	Public Float As Of
returned_count	Returned Count
source_tag	Source Tag
notice	Notice
truncated	Truncated
period_start	Period Start
period_end	Period End
group_by	Group By
split_by	Split By
group_key	Group
event_count	Events
company_count	Companies
estimated_share	Estimated Share
mean_confidence	Mean Confidence
fiscal_year_end_source	Fiscal Year End Source
next_event_confidence	Next Event Confidence
next_event_source_name	Next Event Source Name
next_event_is_statutory_deadline	Next Event Is Statutory Deadline
window_lead_days_used	Window Lead Days Used
window_lag_days_used	Window Lag Days Used
skipped_nearer_event	Skipped Nearer
nearer_event_date	Nearer Event Date
timing_disclaimer	Timing Disclaimer
is_listed	Listed
listed_status_basis	Basis
listed_status_checked_at	Listed Status Checked At
row_status	ok when the row was produced normally, partial when some of it could not be read, error when the row could not be produced. Always present.
error_reason	Why the row is partial or an error, in plain words. Null on an ok row. Always present, never a missing key.
billable_events_json	The pay per event charges this row caused, as a JSON array of {"event","count"}, for example [{"event":"company-checked","count":1}]. "[]" when the row was free. Lets you reconcile a run from the dataset alone. The once per run apify-actor-start charge is not on any row.

| data_source | live when the row was read from the data source during your run, snapshot when the data source was down and the row came from the daily snapshot. Snapshot rows are not charged. | | snapshot_row_count | On a snapshot row, how many companies the snapshot holds. Null on a live row. |

Provenance on every row: data_source, data_as_of, snapshot_built_at, snapshot_row_count, contract_version, provenance_source, provenance_confidence, attribution, license, source_surface.

🛠️ How to find a company's next reporting date

1. Pick a mode. resolve for identity, timing for reporting dates and windows, universe to list companies matching a filter, season for aggregate reporting volume by week or month, qualify to test companies against filters.
2. Give it identifiers: company_domains, tickers, isins, leis, ciks or company_names. Mix types freely in one run, up to 1,000 per run.
3. For timing, set window_lead_days and window_lag_days. They default to 70 and 42, which opens the window ten weeks before the reporting date and closes it six weeks after.
4. Run it. Every input gets exactly one row back, in the same shape, whether it matched or not.

💵 How much does it cost?

Pay per event. You are charged for rows returned, not for rows you filtered out.

Event	Price
Company resolved (company-resolved), resolve, qualify and universe rows	$0.006 per row
Timing row returned (timing-row-returned), timing rows	$0.012 per row
Reporting season aggregate (season-aggregate), season rows	$0.05 per row
Actor start (apify-actor-start), set by Apify	$0.00005 per run, per GB of memory

Volume discounts of 5, 10 and 15 percent apply on the Apify Bronze, Silver and Gold plans.

A row that resolves nothing is still billed. An identifier that matches no public company comes back with match_method set to no_match and every other field null. That is a real answer, the actor made a real request to produce it, and a documented null is worth more than a silent gap. If you do not want to pay for misses, filter your input before you send it.

Timing rows are billed per row and exist for US companies only. A non US company sent to timing mode returns its identity and a timing_unavailable_reason, and is billed as a timing row because the work was done.

Not charged: rows dropped by a filter you set, every row served from the snapshot and every row nothing could answer (see "When the data source is down" below), and every row in a run that fails input validation. A rejected input emits no rows and charges no row event. The platform's own apify-actor-start event still applies, at one per run, because it is levied before the actor validates anything.

The truncation notice is a row you are not charged for. When universe or season matches more than your limit, one extra row comes back carrying total_matched and no company, so the shortfall is visible rather than silent. It is not billed: a limit of 5 against a larger match returns 6 rows and charges 5.

Free plan: No free plan monthly cap. Free Apify plan users run it at the same per row prices, limited only by their plan's monthly credit.

Stopping at your maximum charge: when a run reaches the maximum cost per run you set in Apify, it returns no further row, adds one free notice row saying so, and keeps every row already charged. To spend less, lower limit or max_days_to_event, or narrow the filters.

⌨️ Input

Every field on the Input tab, in the order the form shows them. Only mode and at least one identifier (or a filter, in universe and season) are needed.

Field	Type	Default	What it does
mode	string	"resolve"	resolve returns identity and venue. qualify adds a listed status verdict. timing returns fiscal year end, reporting cadence, the next obligated event and your outreach window. universe builds a company list from filters. season returns reporting load per week or month.
company_domain	string	none	A single bare domain, e.g. stripe.com. The Clay column shape. Used by resolve, qualify and timing.
company_domains	array	none	Many domains at once. Used by resolve, qualify and timing.
tickers	array	none	Exchange tickers, e.g. NWLG. Matched against the primary ticker and every venue listing.
isins	array	none	12 character ISINs.
leis	array	none	20 character Legal Entity Identifiers.
ciks	array	none	SEC Central Index Keys, with or without leading zeros.
company_names	array	none	Legal or trading names. Matched on a normalized name. Former names are not available: the alias table carries tickers and ISINs only.
operating_companies_only	string	"false"	Drop funds, trusts and other non operating entities. Sent as a string for Clay compatibility.
exclude_blank_checks	string	"false"	Drop pre deal SPACs. Separate from the operating company filter: a blank check shell is flagged as an operating company and passes every ordinary firmographic filter.
listed_only	string	"false"	qualify mode. Keep only rows proven to be publicly listed.
suppress_listed	string	"false"	qualify mode. Remove companies proven to be publicly listed, for anyone selling only into private companies. It removes what we can prove is listed; it does not warrant that the remainder is private.
assume_unmatched_is_private	string	"false"	qualify mode. By default an unmatched company returns is_listed null, because a non match may mean the company is private OR that we do not hold its domain. Set true to opt into reading a non match as private, which sets is_listed false.
foreign_private_issuer	string	"any"	Filter on foreign private issuer status.
us_registrant_only	string	"false"	Keep only companies carrying an SEC CIK.
exchange_codes	array	none	ISO 10383 MICs. 18 venues are covered.
country_codes	array	none	ISO 3166-1 alpha-2, e.g. US, GB, FR.
regions	array	none	Shorthand for a set of venues and countries: us, uk, eu. Widens an explicit exchange or country filter rather than replacing it.
sectors	array	none	SEC SIC descriptions, e.g. Pharmaceutical Preparations. Populated on roughly 65 percent of the publishable universe.
security_types	array	none	ordinary_shares, depositary_receipt, preferred_shares.
public_float_bands	array	none	micro, small, mid, large, mega, unknown. Size runs on public float because market capitalization is not populated anywhere in this dataset.
fiscal_year_end_months	array	none	Integers 1 to 12. Fiscal year end is effectively a United States field in this dataset.
exclude_december_fiscal_year_end	string	"false"	Keep only companies whose fiscal year ends in a month other than December, the accounts whose budget cycle is out of phase with a calendar quarter.
cadences	array	none	quarterly, semiannual, annual, unknown.
min_cadence_confidence	string	"0"	0 to 1. Rows whose cadence confidence falls below this return a null timing block with a stated reason rather than a guess. Quarterly cadence averages 0.94, annual 0.40, semiannual 0.21.
event_types	array	none	full_year_results, half_year_results, quarterly_results, trading_update, annual_report_publication, sustainability_report_publication, agm, proxy_filing, capital_markets_day.
window_lead_days	string	"70"	How many days before the event the outreach window opens. Default 70.
window_lag_days	string	"42"	How many days before the event the outreach window closes. Default 42. Must be less than the lead.
window_statuses	array	none	Keep only rows in these window states: open, not_yet, closed_passed, no_event.
max_days_to_event	string	none	Drop rows whose next event is further away than this. A cost control.
include_constrained_period	string	"true"	Emit the period in which a listed company is constrained in what it can announce, derived from the same window numbers. Useful for campaign and announcement timing.
season_group_by	string	"week"	season mode. Bucket size.
season_split_by	string	"none"	season mode. Optional second dimension.
season_from	string	none	season mode. ISO date. Defaults to today.
season_to	string	none	season mode. ISO date. Defaults to 180 days from today.
min_provenance_confidence	string	"any"	Set to high to exclude rows whose source terms were never read.
exclude_name_only_matches	string	"false"	Drop rows whose identity link rests on a name and country agreeing rather than on an identifier. Use this wherever a wrong identity link matters.
exclude_share_alike	string	"false"	Drop rows derived from CC BY-SA sources, whose share alike condition may not suit a closed product.
limit	string	"1000"	Maximum rows for universe and season. Truncation is always reported, never silent.

Example input, timing mode for two US companies:

{
  "mode": "timing",
  "tickers": ["TXG", "ADBE"],
  "window_lead_days": "70",
  "window_lag_days": "42"
}

📤 Output

One flat row per input, one JSON object per row, all fields always present.

{
  "matched_on": "ticker",
  "matched_value": "TXG",
  "legal_name": "10x Genomics, Inc.",
  "primary_ticker": "TXG",
  "cik": "0001770787",
  "primary_exchange_code": "XNAS",
  "country_code": "US",
  "derived_cadence": "quarterly",
  "next_event_type": "quarterly_results",
  "next_event_date": "2026-11-03",
  "next_event_is_estimate": true,
  "days_to_event": 77,
  "outreach_window_open": "2026-08-25",
  "outreach_window_close": "2026-09-22",
  "window_status": "not_yet",
  "confidence_band": "strong",
  "data_as_of": "2026-08-17",
  "row_status": "ok",
  "error_reason": null,
  "billable_events_json": "[{\"event\":\"timing-row-returned\",\"count\":1}]"
}

💡 Tips

Read window_status before next_event_date. It is open, not_yet, closed_passed or no_event against today, and it is the field you filter a Clay table on. no_event is the state a company lands in when there is no reporting event to build a window from, which is every non US company.

Set the window to your sales cycle. window_lead_days and window_lag_days are yours. A long enterprise cycle wants a wider lead than the default 70 days.

Use universe mode to build the list, then timing to time it. universe returns every company matching a filter, paging through the whole match rather than stopping at the first page.

When the data source is down

The actor reads one live data source, and every request to it is capped by the run's own timeout minus a 90 second reserve. If that source refuses the request, does not answer in time, or fails, the run switches to a snapshot of the same data and still succeeds:

• The snapshot is a copy of the same public data the live source serves, rebuilt once a day. Every row served from it says data_source: "snapshot" and carries snapshot_built_at (when the copy was made) and snapshot_row_count (how many companies it holds), so you can tell a live read from a snapshot read in any column.
• Snapshot rows are not charged. Rows read live before the source went down keep their charge.
• The snapshot answers identity, qualification, universe and season the way the live source did on its build date. Two things are narrower: it does not match secondary ISINs or tickers that are only aliases, and it holds up to 8 upcoming reporting events per company.
• The status message says the run used the snapshot and how many rows came from it.

If the snapshot cannot be read either:

• Each company you sent gets one row with matched_on and matched_value set to your identifier, row_status: "error", and an error_reason that starts with blocked: (the source refused), timed_out: (it did not answer in time), or error: (it failed). In universe and season mode there is one such row for the run.
• None of these rows is charged, and the status message says how many there are.
• No company data is invented. Run it again later.

A blocked: row never means the company was not found. A real "not found" is a no_match row with company fields null, and that one is a result.

⚠️ Known limits

Timing is US only. Reporting events come from SEC filing history. Non US companies resolve fully for identity, venue and classification and return a stated timing_unavailable_reason in timing mode. No date is invented for them.

Unknown cadence is refused, not guessed. 922 companies in the universe have no derivable reporting cadence, because their filing history is too short or too irregular to support one. The actor returns derived_cadence null with a reason instead of inventing a date. A wrong date that looks right is worse than no date.

864 companies have no publishable representation and cannot be returned at all. They exist in the market and not in the redistributable surface this actor reads.

Dates are predicted, not announced. next_event_is_estimate is true for a predicted date and next_event_is_announced is true only when the event is a confirmed one. Treat an estimate as an estimate.

Identity is cached for 24 hours, timing never is. days_to_event, window_status and is_in_constrained_period change every day by construction, so a cached window would be a wrong window. There is no flag to turn timing caching on.

Attribution ships only where the result set requires it. The attribution and license fields carry the acknowledgment a row's source requires, and the run level attribution list holds only the strings the rows you actually received need. A result set with no rows from a given source does not claim that source's acknowledgment.

❓ FAQ

Which identifier should I send? Whichever you already have. Ticker and CIK are the most precise, domain is the most common in a GTM table, and name matching is the loosest. matched_on tells you which one produced the row.

Can I send 5,000 companies? Send up to 1,000 identifiers per run. universe mode pages through matches larger than that and returns the whole set.

What is the constrained period? The stretch before a reporting date when a company's investor relations team is least available. constrained_period_open, constrained_period_close and is_in_constrained_period mark it so you can avoid it or target it deliberately.

Why did a company I know is public come back no_match? Either the identifier does not appear on the publishable surface, or the company is one of the 864 with no publishable representation. match_method and domain_absent_reason say which.

How fresh is the data? data_source, data_as_of and snapshot_built_at ship on every row. Read them rather than assuming. A snapshot row is at most about a day old.

🧩 Want other GTM data?

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💬 LinkedIn Post Tracker	📢 Meta Ad Library Monitor
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✖️ X Brand Presence Mapper	▶️ YouTube Channel Stats Extractor

Every actor in the suite takes a domain or a company and returns one flat row, so they stack in the same Clay table without reshaping anything.

🛠️ Need something custom built for you or your team? Tell us what you are trying to find and we will build it. Talk to Mamba Labs.

🆘 Support

A company timed wrongly, or an identifier that should have matched? Open an issue on the Issues tab with the input and the rows, and we will look at it.

ℹ️ Sourcing and legal. Company identity, venue and classification come from openly published reference sources, and reporting events from US SEC filing history. Every row carries its provenance_source, provenance_confidence and, where the source requires one, its attribution string and license. The actor emits company identity, venue, classification and reporting dates. It holds no personal data and returns none. You are responsible for how you use the output.

Built by Mamba Labs.