Audience & customer insight
Analyse approved research, feedback and interaction data to surface themes and questions. Link findings to their evidence and the decisions they are intended to support.
Build / More relevant work. Less repetitive production.
AI marketing & personalisation.
Build AI into marketing operations, audience analysis and customer experiences. We connect approved data and content to workflows for research, personalisation, production and measurement.
Discuss this with usThe opportunity
Connect insight, content and the next action.
Marketing teams move between disconnected data, briefs, content tools and approval queues. More generated content is not automatically more useful; it needs to be relevant, accurate, on-brand and connected to a measurable purpose.
Choose a specific marketing workflow or decision. We define the data and brand guidance it can use, the review steps it needs and how its contribution will be measured. Integration makes the output usable in the tools where the team works.
What we can do.
Content & campaign workflows
Prepare drafts, catalogue enrichment and campaign variants using approved information. Route content through brand and factual review before publication.
Personalisation & recommendations
Develop recommendations or experience variations around appropriate first-party information and agreed rules. Evaluate relevance and business outcomes through controlled measurement.
Tangible outputs
What you receive.
The exact scope is agreed around your workflow. A typical engagement can include:
- A focused marketing workflow and measurement plan
- Data and content-source integrations
- Drafting, enrichment or recommendation capabilities
- Human approval and brand-guidance controls
- Experimentation and performance review guidance
Illustrative workflow
A product catalogue needs consistent descriptions
Retrieve approved specifications → draft product content → check required claims and tone → review → publish through the existing platform.
An example of how this capability can fit a business process.Define what better looks like.
We agree useful measures before implementation and compare them with the current workflow.
- ↗Review time and useful output acceptance
- ↗Content accuracy and consistency
- ↗Incremental outcomes from a defined experiment
Your questions, answered.
Is this an automated content factory?
The service focuses on a useful workflow with source material, standards and approval. Output volume alone is not a success measure.
Can we keep using our marketing platform?
We assess available integration options and build around the existing workflow where practical.
Can you guarantee better conversion?
No. Conversion depends on the audience, product, offer and experience. We define experiments that can test whether a change makes a useful contribution.
Useful before you start
Questions worth exploring.
How to choose your first AI project
Start with work you can observe, data you can access and an outcome you can measure.
From AI pilot to production: what changes?
A working demonstration is a starting point. A released service also needs integration, ownership and a dependable response to failure.
What does AI implementation really cost?
A useful budget covers the whole workflow: data, integrations, evaluation, people and the cost of keeping it running.
A useful next step
Bring us the work
that should work better.
One process, one product idea, or a question about where to start.