Overview
A maritime technology business had deep technical capability but presented it through internal product categories and organisational language.
Buyers approached the company from a different direction: vessel type, operational problem, regulation, application, lifecycle stage or commercial risk.
We reorganised the content model around those buyer contexts while preserving the technical detail experts and procurement teams needed.
Who This Is For
Maritime technology, marine equipment and specialist shipping-service firms selling complex solutions internationally.
The Situation
The website reflected how the supplier was organised.
Sales conversations reflected how customers operated.
The gap made it difficult for prospects to understand which capabilities belonged together or why a technical feature mattered operationally.
Where the Workflow Breaks
Our Approach
Map customer contexts
Structure discovery around:
- Vessel type
- Operational challenge
- Lifecycle stage
- Application
- Geography
- Regulation
- Technical requirement
Connect products to outcomes
Preserve specifications while linking them to the job the customer is trying to perform.
Structure proof
Connect claims to:
- Installations
- Use cases
- Technical evidence
- Certifications
- Relevant expertise
Create reusable solution views
Use the same underlying knowledge to create different paths for different buyer contexts.
Connect sales feedback
Capture questions and combinations that repeatedly arise in commercial conversations.
Before → After
Where AI Helps
AI can improve retrieval across a complex technical estate and help assemble relevant approved material for a particular vessel, application or problem.
The knowledge relationships must exist first.
What Changes
- Easier buyer navigation
- Stronger cross-sell between capabilities
- Less dependence on salespeople to explain the portfolio from scratch
- Better reuse of technical evidence
- Stronger foundations for international search and AI discovery
These are the operational changes the work aims for. Any measures are agreed against your own baseline during scoping.
What This Demonstrates
Complexity does not need to be removed.
It needs to be modelled around the customer's context.
Relevant experience
Named projects that show parts of this approach in practice. They evidence the underlying experience; none of them is the scenario above, and each case study says how it was delivered.
- Global Customer Services Portal
Replaced a site structured around business divisions with one built around customer journeys and solutions, for a global maritime services group.
- Intranet Migration & Information Architecture for a Maritime Services Group
Content migration and information architecture for a maritime group's move to Office 365.
- Demand Generation for a B2B Software Provider
Expert content and campaign paths for a software provider serving maritime and energy customers.
At a glance
Client type
Capabilities
- Information architecture
- Technical content
- Product and service modelling
- Sales enablement
Most relevant to
Maritime suppliersRelated patterns
Making Product Knowledge Machine-Readable
Export-oriented industrial manufacturer
Product truth was distributed across systems, documents and experts. We connected specifications, applications, buyer problems and evidence into a reusable knowledge model that could support web, sales, localisation and AI retrieval.
Creating One Knowledge Layer for Marketing, Sales and AI
Complex B2B organisation
The organisation had plenty of systems but no shared view of which information was authoritative. We created the model connecting content, product knowledge, customer questions and proof without requiring everything to move into one new platform.
Recognise this problem?
We can start by mapping the workflow, finding the bottleneck and defining a contained first improvement.
Discuss a first project