How to Calculate Pre-Arrival Contact Rate

Pre-arrival contact rate is the share of vessels due at your ports that you actually reach with a named person before the vessel berths. It is calculated as contacts reached divided by vessels in scope, counted in the same period and the same port set.

Most maritime suppliers cannot state that number. They know how many quotes they sent last month, but not how many arriving ships they never approached at all. That gap is where pre-arrival contact rate earns its place as a weekly operating metric.

Why pre-arrival timing drives the number

Arrival times move, and the supplier who reaches the right person first usually gets the enquiry. A 2022 study in the Flexible Services and Manufacturing Journal used machine learning, from linear regression to neural networks, to forecast vessel arrival times from AIS data and build dynamic time buffers into berth scheduling, because actual arrivals shift with cross wind and sea current (Springer).

For a chandler or bunker supplier, that variability is the reason to contact early rather than on the day of berthing. A 2021 paper in IEEE Transactions on Aerospace and Electronic Systems showed that encoder-decoder recurrent networks trained on historical AIS observations can predict vessel trajectories several hours ahead (IEEE). Better forward visibility of arrivals is exactly what a contact-rate target depends on.

Port calls themselves are routine events with commercial weight. Hellenic Shipping News describes a port call as a berth booking for a port authority and a service opportunity for a ship agent (Hellenic Shipping News). Every one of those opportunities either enters your contact-rate denominator or it does not.

The five stages of the calculation

Build the metric from five counted stages. Each stage is a whole number you can audit, so the final percentage always traces back to named vessels.

1. Vessels in scope. Every vessel with an ETA inside your target window at your selected ports, usually the next seven days. Include expected and scheduled arrivals, not only ships already at anchor.
2. Company resolved. The owner, manager, operator or charterer identified behind each vessel. Vessels with no company resolved stay in the denominator as a zero, which keeps the metric honest.
3. Decision-maker found. A named person in a buying role: technical superintendent, purchasing superintendent, port captain, fleet manager, operations manager or chartering desk.
4. Contact reached. A delivered, personalised message on email, WhatsApp or phone, addressed to that named person.
5. Reply received. Any human response, including a request for a quotation, a request to be contacted later or a decline.

Worked example: one week, two ports

Take a ship chandler covering two ports with 40 vessels expected in a week. The numbers below are illustrative, chosen to show how the stages compound.

StageCountShare of previous stage Vessels in scope (ETA next 7 days)40- Company resolved3690% Decision-maker found2775% Contact reached2178% Reply received943%

Pre-arrival contact rate is 21 divided by 40, or 52.5%. Reply rate on contacted vessels is 9 divided by 21, or 42.9%. The overall funnel from vessel to reply is 22.5%.

The compounding is the point. A team that resolves 90% of companies but finds a decision-maker for only 75% of those has already lost a quarter of the week before any message is sent. Fixing the decision-maker stage from 75% to 90% would have added four contacted vessels in this example, without a single extra arrival.

Reading the stages as diagnoses

Each stage failure has a different cause, so the fix differs.

• A low company-resolved rate usually means incomplete ownership or manager data for the vessel type, common with short-sea and specialist tonnage.
• A low decision-maker rate points to role mapping: contacting a general inbox instead of the technical superintendent who signs off stores.
• A low contact rate with a healthy decision-maker count points to channel and timing, not targeting.
• A low reply rate with a healthy contact rate points to message quality and relevance to that vessel's trade.

Vessel type changes the picture. A 230-guest expedition ship calling at Ipswich as the port's largest-ever cruise visitor brings a different buying pattern from a bulk carrier (Marine Insight). A naval visit such as the USS Theodore Roosevelt arriving at Yokosuka involves access and clearance steps a commercial chandler will not face (Marine Insight). Segment the metric by vessel type so one segment does not mask another.

Benchmark against your own history, not the market

No credible public benchmark for pre-arrival contact rate exists, because the denominator depends on your port set and window. Set your baseline from your own first four weeks, then track the direction of travel.

Dry-dock and repair demand is a useful stress test. Maersk Chattogram was scheduled to enter L&T's Kattupalli Shipyard on 20 October 2026, part of a partnership to strengthen India's ship repair capability (Marine Insight). A yard tracking pre-arrival contact rate should count that vessel in scope weeks before the docking date, because the purchasing decisions happen earlier than the arrival.

The same applies to offshore and project tonnage. DEME added turbine installation to its foundation scope on the 1GW Zeevonk offshore wind project in the Netherlands, covering 69 turbines in the first phase (Splash247). Project vessels attached to that work will arrive on schedules that shift, so the contact window matters as much as the contact itself.

Data quality upstream decides the number

Contact rate is only as good as the arrival and ownership data feeding it. Port communities are already automating the administrative layer: WiseTech Global integrated its CargoWise landside transport system with terminal appointment software provider Dray Dog to automate port bookings for US drayage operators (The Loadstar).

Container terminal operators face the same forecasting problem on the landside. A 2022 study in IEEE Transactions on Intelligent Transportation Systems combined a gated recurrent unit with a fully connected neural network to predict daily truck arrivals, incorporating vessel-related information among the input parameters (IEEE). The lesson for suppliers is structural: arrival data improves when it is modelled, not read off a single feed.

The one-page weekly port-call scorecard

Keep the scorecard to a single page, one row per port, one column per stage. Describe it in text so any team can rebuild it in a spreadsheet.

• Header: week number, port set, ETA window, owner of the number.
• Row per port: vessels in scope, companies resolved, decision-makers found, contacts reached, replies, quotes requested.
• Two calculated columns: pre-arrival contact rate and reply rate, each as a percentage of the stage before it.
• One notes line per port: the single biggest stage drop and the action for next week.
• Footer: four-week rolling average for the whole port set, so one bad week does not trigger a rewrite of the playbook.

Publish it every Monday for the week ahead, then reconcile on Friday with actual arrivals. That reconciliation is where the metric becomes credible with a sales team.

How VesselReach helps

VesselReach, built by CatalystIQ, produces the stage counts this scorecard needs from one workflow.

• Vessel intelligence for your ports: vessels near your selected ports plus scheduled and expected arrivals, which means your denominator is built from forward ETA data rather than yesterday's berth list.
• AI company targeting and decision-maker discovery: an LLM identifies the right company behind each vessel and surfaces roles from operations and technical superintendents to procurement and C-suite, which means the company-resolved and decision-maker stages stop leaking.
• Staged email, WhatsApp and phone outreach with automated follow-ups: personalised sequences avoid duplicate contacts, which means the contact-reached count reflects real people, not repeated sends.

Book a VesselReach demo to see the funnel for your own ports, and a 10-day free trial is offered after the demo meeting.