Overview
A B2B company was producing content and running campaigns but could not reliably explain which activity created useful commercial conversations.
We connected content planning, landing journeys, qualification, CRM hand-off and sales feedback into one operating loop.
Who This Is For
B2B technology companies with:
- Regular content production
- Paid and organic acquisition
- A CRM
- Sales development or direct sales
- Weak visibility between engagement and opportunity
- Marketing and sales using different definitions of a good lead
The Situation
Marketing measured traffic, downloads and campaign engagement.
Sales measured conversations and opportunities.
Between them sat an attribution gap and, more importantly, an operating gap.
Marketing could not see which questions signalled genuine buying intent. Sales repeatedly encountered objections and information needs that never made it back into content planning.
Where the Workflow Breaks
Our Approach
Start with buying questions
Map content to:
- Problem recognition
- Evaluation
- Risk
- Implementation
- Proof
- Commercial readiness
Design conversion paths
Give useful content a logical next action:
- Assessment
- Calculator
- Diagnostic
- Comparison
- Workshop
- Conversation
Improve qualification
Capture enough context to distinguish curiosity from a problem worth discussing.
Connect the CRM hand-off
Make source, topic, content journey, expressed problem and qualification signals visible to sales.
Return sales learning
Capture these and feed them into the content backlog:
- Objections
- Recurring questions
- Lost reasons
- New use cases
- Proof requirements
Before → After
Where AI Helps
AI can:
- Classify inbound questions
- Summarise engagement context
- Suggest relevant existing content
- Identify recurring objections
- Cluster CRM feedback
- Propose backlog priorities
Humans decide:
- Account value
- Sales approach
- Commercial qualification
- Positioning
- What deserves investment
What Changes
- Clearer relationship between content and commercial activity
- Stronger marketing-to-sales hand-off
- Better-informed sales conversations
- Content planning based on real buyer friction
- Fewer vanity metrics
- A repeatable learning loop
These are the operational changes the work aims for. Any measures are agreed against your own baseline during scoping.
What This Demonstrates
Content operations should not end at Publish.
For B2B organisations, the operating model should continue through buyer response, CRM, sales learning and the next content decision.
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.
- Digital Demand Generation for a Global Technology Manufacturer
Search, content and conversion journeys connected into one measurable model, with lead scoring and attribution across marketing automation, analytics and CRM.
- Demand Generation for a B2B Software Provider
An inbound model connecting expert content and campaign paths to qualified sales leads.
- Sales Funnel & Digital Strategy for a Norwegian Energy Retailer
Sales-funnel design for a business moving from a service portal to a sales-driven site.
- Advertising Sales Platform
A CRM-connected sales platform linking audience data, formats, pricing and sales contacts.
At a glance
Client type
Capabilities
- Demand generation
- CRM workflow
- Lead qualification
- Measurement
- Content operations
Most relevant to
SaaS and industrial techRelated patterns
Turning Customer Questions Into a GTM System
Specialist professional-services firm
Instead of inventing another editorial calendar, we used the questions prospects were already asking to build a structured knowledge backlog connecting expert answers, content, services and sales conversations.
Redesigning the Content Supply Chain Around Human + AI Work
Resource-constrained B2B marketing team
People were already using AI, but every workflow was different. We defined the inputs, outputs, owners, AI tasks, human decisions and quality gates needed to turn individual experimentation into a repeatable operation.
Recognise this problem?
We can start by mapping the workflow, finding the bottleneck and defining a contained first improvement.
Discuss a first project