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Predictive Fleet Analytics vs. the competition: Four factors to inform your decision 

More Data Storytelling

When comparing predictive maritime analytics solutions in the market, the main factors to evaluate when deciding which one is right for you are its methodology, ease of use, contextual insights and customer focus. So, let’s compare our newest solution with two close competitors in the maritime industry to simplify your evaluation process.  

What they offer 

Lloyd's List Intelligence
Predictive Fleet Analytics

Maritime data
competitor A

Maritime data
competitor B

Vessel fleet coverage (All key commercial vessel types)

Vessel Operational Statuses

Predicted Estimated Time of Arrival (ETA)

Predicted Estimated Time to Berth (ETB)


Predicted Estimated time of Departure (ETD)


Predicted Destinations

Expected vessel arrivals

Trade Lane Analytics

Predicted waiting times and expected time at port (Port congestion levels)


Integrated news on Vessel, Port and Company Page

Detailed Port Hierarchy

Detailed Voyage History, Port Callings and Events Log timeline

Competitor A: Uses AIS data to provide real-time information on the movement and position of ships. It also gives some additional vessel details such as IMO numbers, gross tonnage, dimensions and place of build.

Competitor B: Uses AI-powered software to provide real-time information, insights and predictions about vessels at sea with the aim of aiding compliance.


Here are the four factors to inform your decision: 

1. Underlying Methodologies 

Whilst we are renowned for our maritime analytics solutions, an objective benchmark would be data quality. The quality of insights derived from any predictive maritime analytics solution will certainly depend on data quality and the data sources it relies on. 

In addition to strategic partnerships with terrestrial receivers, satellite providers and port agents, what sets one apart are exclusive data sources. We have hundreds of exclusive data sources and more than 500 Lloyd’s agents in over 170 countries.

Next, with all the quality data ingested, what’s vital is how it is being handled and used. Predictive Fleet Analytics combines quality data with machine learning to generate consistent accurate predictions for vessel movements - the models predict destinations with an accuracy of 70%, 35-percentage points higher than raw AIS destination.

The introduction of machine learning to the predictive model helps process huge volumes of complex data over time, with the learning algorithm uncovering patterns and correlations in data that may not be detected otherwise. Be sure to study the solution methodology to uncover the difference between machine learning and simple extrapolations or aggregations.  

Also consider the vessel fleet coverage. Some solutions can predict ETAs only for container ships while Predictive Fleet Analytics covers all key commercial vessel types which serves the need for shipping professionals in liner services and tramp markets, on fixed and non-fixed schedules. 

2. Ease of use

Ease of use can often be an unstated feature. Two things to consider are the comprehensiveness of the features as well as how useful and intuitive they are.

Predictive Fleet Analytics enables you to view a ship’s predictive route information, ETAs, ETBs and ETDs, port congestion levels, trade lane analytics alongside key vessel, characteristics, and ownership information in a single platform. Value added details such as the red, amber, green (RAG) status for port congestion levels, and quick research tool for common trade routes comes out of the box as well.

There is no need to stack requested data points or features into existing products, which translates into more time, effort and money to design a high level of customisation and configuration for each user role and workflow.

The result is a more straightforward and intuitive workflow, that makes the predictions more actionable. 

3. Contextual and actionable insights 

Context is key. Besides data points and features, it’s important to consider which of the three solutions  goes the extra mile to help users make an informed decision, with key information such as the vessel characteristics, distance traveled, time to go, current voyage, vessel operating and regional (eg. EEZ, time spent in high-risk areas) statuses.  

Furthermore, we offer a combination of data and insights solution suite where award-winning maritime reporters on the ground break unbiased and verified news to help you stay ahead of trends.

Predictive Fleet Analytics comes out on top, providing all of this information compared to competitors A and B, helping users to see the full picture. 

4. Customer focus 

Last but not the least, for a reliable maritime analytics solution, customer discovery, feedback, beta testing must be continuously gathered, analysed and actioned on to feed into the product.   

Additional features in Predictive Fleet Analytics are progressively rolled out to further enhance the user experience and meet the evolving needs of customers. Read more

Backed by influential customers and hundreds of interviews, Predictive Fleet Analytics was developed to respond to maritime professionals’ requirements to bridge maritime data gaps, enable proactivity in ship operations and planning, as well as opportunity creation via new trades and prospecting. 


The clear solution of choice 

Based on the four key factors above, Predictive Fleet Analytics offers maritime professionals the most comprehensive solution, providing a broad scope of accurate data and predictions on a single platform. In short, it stands out because it: 

  • Supplies a greater range and quality of data than any competitor 
  • Provides ETBs and ETDs in addition to ETAs, which is unique 
  • Delivers contextual and actional insights alongside data to assess the full situation 
  • Backed by real customer discovery, feedback and testing to meet the industry’s requirements 

Watch our new maritime analytics solution in action, specific to your workflows: 

Watch product overview videos