Charter Pulse is a data intelligence platform. We collect booking signals from charter platforms, cross-reference them against historical archives, classify confidence, and produce structured reports with a source URL on every data point.
01
01
We pull availability calendars and weekly booking grids from charter platforms. Dates marked unavailable are logged as booking candidates. Each scrape cycle records the exact state of the calendar, giving us a time series of availability changes per vessel.
Availability entries are stored per listing with snapshot date, entry type (Booked / Unavailable), and duration. Each scrape run is logged with listings found, listings checked, new bookings detected, and error count.
02
02
Live scraping shows today's state. To reconstruct historical occupancy, we query the Wayback Machine CDX API — a free, publicly accessible index of archived web pages — retrieving calendar snapshots per vessel going back 24+ months. Each snapshot becomes a citable source URL included in the report.
CDX API returns snapshot timestamps. We fetch HTML for peak-month snapshots, parse calendar state, and record each booked or available day with the Wayback URL as the source. Multiple snapshots per year build a historical occupancy curve.
03
03
Not every detected booking has equal certainty. We classify each signal: Confirmed (detected 7+ days before charter, persistent across scrape cycles), Probable (3–7 days), or Ambiguous (<3 days, may be system cutoff). Each vessel's figures are then benchmarked against peer vessels — same type, same market, same season.
Benchmarks are calculated from current database records: RevPAW (Revenue per Available Week), avg occupancy %, avg lead days, and revenue concentration (Gini / Pareto). Stability is graded A–F by operator based on coefficient of variation across months.
04
04
Output is a 3-sheet Excel workbook and a structured PDF. Sheet 1 shows per-vessel tables with booked and unbooked dates colour-coded by period and revenue estimated per year. Sheet 2 provides a one-row-per-listing summary with occupancy % by year for cross-fleet comparison. Sheet 3 is every individual booking record with source URL, confidence level, and platform attribution.
PDF covers executive summary, occupancy analysis, revenue estimates, market benchmark comparison, seasonality, forward pipeline, and full source URL index. Every formula is visible. No black boxes.
Every module is available in the analyst dashboard. Each answers a specific question about charter asset performance.
Every detected booking is classified by confidence. The classification is disclosed in the report and drives how each signal is weighted in occupancy and revenue calculations.
Confirmed
Detected 7+ days before charter start. Signal persisted across multiple scrape cycles. Used in all primary metrics.
Probable
Detected 3–7 days before charter. Could be a genuine booking or an operator block. Included with a conservative discount applied to revenue estimates.
Ambiguous
Detected <3 days before charter. Could be a last-minute booking or a platform cutoff artefact. Flagged in the report but excluded from primary occupancy calculations.
Platform coverage is limited to tracked sources. Private bookings, direct operator deals, and listings on untracked platforms are not reflected.
Wayback Machine coverage varies per listing. Vessels with high crawl frequency yield richer historical data than newly-listed or low-traffic listings.
Revenue estimates are based on the last observed pricing before a detected booking. Actual pricing may differ if promotional or off-season rates applied.
Occupancy figures represent detected booking signals. Ambiguous signals are excluded from primary metrics. Reported occupancy may be marginally below true occupancy.
Charter Pulse is independent. We have no affiliation with any booking platform, charter company, or management program.
Every report ships with a full source URL index and methodology disclosure. No black boxes.
Order a Report