Detection timeframes

Every signal is evaluated over a specific time window. Some fire the instant a field changes between two crawls. Others only fire once a pattern holds across weeks or months. Knowing the window tells you how fresh a signal is and how much weight to give it, a single-snapshot change is immediate but noisy, while a 90-day pattern is slower but far more reliable. CUFinder evaluates signals across five practical windows.

Week (7 days)

Short-fuse patterns that need to be caught fast, like a cluster of crisis posts.

1 month (30 days)

Rolling-activity windows: posting cadence, engagement shifts, and the nightly momentum score.

3 months (60 to 90 days)

Quarter-scale patterns: vacancies, consolidations, churn spikes, and most composite events.

6 months (180 days)

The longest patterns, like the pre-IPO buildout that unfolds over two quarters.

Two more windows sit outside the week-to-six-month scale: an instant snapshot diff (the change is detected the moment two crawls differ) and a 12-month lookback used by the first-in-function and first-in-geography signals.

Snapshot (instant)

These fire the moment a tracked field differs between two consecutive crawls. There is no waiting window, the change is the signal. They are the most immediate but also the most sensitive, so filter them by magnitude. This is the largest group. 71 signals use this window:

Signal	Category	What it means
`employee_growth`	Growth	A company’s employee count increased by at least one between snapshots.
`employee_size_band_upgrade`	Growth	A company moved up a full Professional Network employee size band.
`followers_growth`	Growth	The company’s Professional Network follower count increased.
`jobs_open_increase`	Growth	The number of open job postings increased.
`remote_jobs_share_change`	Growth	The share of remote or hybrid postings shifted significantly.
`employee_decrease`	Decline	A company’s employee count dropped by at least one.
`employee_size_band_downgrade`	Decline	A company fell down a Professional Network employee size band.
`hiring_freeze_signal`	Decline	Open roles collapsed while headcount stayed flat or fell.
`followers_decrease`	Decline	The company’s follower count dropped.
`jobs_open_decrease`	Decline	The number of open job postings fell.
`jobs_dropped_to_zero`	Decline	A company that had open roles now has none.
`name_change`	Identity	The company name string changed.
`name_change_drastic`	Identity	A name change with almost no overlap to the old name.
`dba_added`	Identity	The name now references a former name (dba/fka).
`tagline_change`	Identity	The company tagline text changed.
`tagline_added`	Identity	A previously empty tagline is now populated.
`tagline_removed`	Identity	A populated tagline was cleared out.
`description_change_minor`	Identity	The company description was lightly edited.
`description_change_major`	Identity	The company description was substantially rewritten.
`description_keyword_added`	Identity	A tracked strategic keyword appeared in the description.
`description_keyword_removed`	Identity	A tracked strategic keyword disappeared from the description.
`industry_change`	Categorization	The company’s primary industry classification changed.
`industry_added`	Categorization	A new industry was added to the company’s list.
`industry_removed`	Categorization	An industry was dropped from the company’s list.
`specialty_added`	Categorization	A new specialty was added.
`specialty_removed`	Categorization	A specialty was dropped from the list.
`specialties_count_increase`	Categorization	The total number of specialties grew notably.
`specialties_count_decrease`	Categorization	The total number of specialties shrank notably.
`hq_change`	Location	The headquarters city or country changed.
`hq_country_change`	Location	The headquarters country specifically changed.
`location_added`	Location	A new office location appeared.
`location_removed`	Location	An office location disappeared.
`country_expansion`	Location	A company opened its first location in a new country.
`multi_office_milestone`	Location	The company’s office count crossed a milestone threshold.
`office_consolidation`	Location	Multiple office closures in a short window.
`company_type_change`	Structure	The company’s entity type changed.
`nonprofit_to_for_profit`	Structure	The company changed between nonprofit and for-profit status.
`subsidiary_status_change`	Structure	The company became or stopped being a subsidiary.
`founded_year_added`	Structure	A previously missing founded year was populated.
`founded_year_change`	Structure	The founded year value changed.
`parent_company_change`	Structure	The parent company changed to a different one.
`parent_company_added`	Structure	A parent company was set where there was none.
`parent_company_removed`	Structure	A parent company relationship was cleared.
`subsidiary_added`	Structure	A new subsidiary appeared in the company’s list.
`subsidiary_removed`	Structure	A subsidiary was removed from the company’s list.
`showcase_page_added`	Structure	A new Professional Network showcase page was linked.
`showcase_page_removed`	Structure	A Professional Network showcase page was unlinked.
`funding_round_announced`	Funding	A new funding round was announced.
`last_funding_round_change`	Funding	The company’s funding stage advanced.
`total_funding_increase`	Funding	The company’s total funding raised increased.
`page_reactivated`	Activity	The company resumed posting after a dormant stretch.
`post_topic_shift`	Activity	The dominant topic of recent posts changed.
`employee_joined`	People	A person’s current company changed to this company.
`employee_departed`	People	A person left this company for another.
`internal_promotion`	People	Someone was promoted to a more senior title at the same company.
`lateral_title_change`	People	Someone changed title at the same company without a seniority change.
`c_suite_hire`	People	A new C-level executive joined the company.
`c_suite_departure`	People	A C-level executive left the company.
`founder_departure`	People	A founder left the company.
`vp_hire`	People	A new VP-level leader joined the company.
`vp_departure`	People	A VP-level leader left the company.
`first_role_hire`	People	A company made its first-ever hire for a role function.
`leadership_churn_spike`	People	Multiple senior leaders departed in a short window.
`engineering_leader_hire`	People	A new engineering leader joined the company.
`sales_leader_hire`	People	A new sales leader joined the company.
`talent_outflow_to_competitor`	People	An employee left for a known competitor.
`talent_inflow_from_company`	People	A company hired multiple people from the same source company.
`notable_hire`	People	A high-profile or highly experienced person joined.
`ipo_signal`	Composite	A company went from private to public.
`acquired_signal`	Composite	A company was acquired.
`risk_score`	Composite	A nightly composite score ranking a company’s decline and risk.

Crawl-over-crawl baselines

These compare the current crawl against a short rolling baseline (the previous 4 or 6 crawls) to catch anomalies like spikes and surges. They fire only when current activity breaks sharply from the recent norm. 9 signals use this window:

Signal	Category	What it means
`followers_spike`	Growth	Follower growth ran sharply above the company’s recent baseline.
`jobs_open_spike`	Growth	Open job postings jumped sharply above the recent baseline.
`senior_hiring_increase`	Growth	The share of senior-level postings rose meaningfully.
`engineering_hiring_surge`	Growth	Engineering job postings doubled versus the prior crawl.
`sales_hiring_surge`	Growth	Sales job postings doubled versus the prior crawl.
`layoff_signal`	Decline	Employee count dropped sharply in a single interval.
`mass_layoff_signal`	Decline	Employee count dropped severely in a single interval.
`followers_growth_decelerating`	Decline	Follower growth slowed sharply while still positive.
`affiliated_pages_count_change`	Structure	The net count of affiliated pages shifted notably.

Week (7 days)

Short-fuse patterns evaluated over a rolling 7-day window. Fast-moving by design, so they are caught and acted on quickly. 1 signal use this window:

Signal	Category	What it means
`crisis_response_signal`	Activity	A cluster of statement or apology-style posts in a short window.

1 month (30 days)

Rolling 30-day windows, mostly social-activity rhythms compared against the preceding 30-day periods, plus the nightly momentum score that decays over 30-day steps. 4 signals use this window:

Signal	Category	What it means
`posting_activity_increase`	Activity	The company is posting noticeably more on social.
`posting_activity_decrease`	Activity	The company is posting noticeably less on social.
`avg_engagement_change`	Activity	Average post engagement shifted significantly.
`momentum_score`	Composite	A nightly composite score ranking a company’s upward trajectory.

3 months (60 to 90 days)

Quarter-scale patterns. A vacancy that stays open 60 days, three closures or departures inside 90 days, or a composite event whose parts must land within a 60-to-90-day window. Slower to fire, but high-confidence. 9 signals use this window:

Signal	Category	What it means
`page_dormant`	Activity	The company stopped posting for an extended period.
`key_role_vacancy`	People	A senior role stayed unfilled for 60 days.
`merger_signal`	Composite	Two companies merged under a common new parent.
`pivot_signal`	Composite	A company fundamentally changed what it does.
`rebrand_signal`	Composite	A company executed a coordinated rebrand.
`expansion_signal`	Composite	A company is expanding into new markets while growing.
`decline_signal`	Composite	A company shows a clear distress pattern.
`restructuring_signal`	Composite	A company is undergoing major restructuring.
`executive_team_buildout`	Composite	A company rapidly built out its leadership team.

6 months (180 days)

The longest patterns in the catalog. These need two quarters of evidence before they fire, which makes them rare and strong. 2 signals use this window:

Signal	Category	What it means
`headcount_recovery`	Growth	Employee growth returned after a recent decline.
`pre_ipo_signal`	Composite	A company shows the early pattern of an IPO track.

12-month lookback

These check whether something is happening for the first time in a year, a first job posting in a function or geography. The window is a backward lookback rather than a waiting period. 3 signals use this window:

Signal	Category	What it means
`first_job_in_function`	Growth	A company posted a role in a function it hadn’t hired for in 12 months.
`first_job_in_country`	Growth	A company posted its first role in a new country.
`first_job_in_city`	Growth	A company posted its first role in a new city.

Using timeframes in practice

Pair the window with magnitude. Act fastest on short-window, high-magnitude events (a funding round, a crisis cluster), and treat long-window composites as durable, high-trust signals worth a more considered approach. The longer the window a signal clears, the longer your outreach stays relevant.

See how detection works

The full pipeline behind snapshots, baselines, and windowed triggers.

Week (7 days)

1 month (30 days)

3 months (60 to 90 days)

6 months (180 days)

​Snapshot (instant)

​Crawl-over-crawl baselines

​Week (7 days)

​1 month (30 days)

​3 months (60 to 90 days)

​6 months (180 days)

​12-month lookback

​Using timeframes in practice

See how detection works

Snapshot (instant)

Crawl-over-crawl baselines

Week (7 days)

1 month (30 days)

3 months (60 to 90 days)

6 months (180 days)

12-month lookback

Using timeframes in practice