From data requests to decision products
One-off analysis rarely changes an operation. We identify the recurring decision, then engineer the data and interface required to support it consistently.
What we build
Analytics and Intelligence
Decision-ready intelligence that turns fragmented market, customer and operational data into a repeatable advantage.
As a business intelligence consultancy, we create trusted analytical products that make fragmented evidence usable in recurring commercial and operational decisions.
Evidence people can use
We combine data modelling, analytical methods and clear product experiences so leaders can explore drivers, compare options and understand limitations.
Power BI and the tools you already use
We build on the business intelligence tools your teams already know, including Power BI, Tableau and Looker, and engineer the data model and pipelines beneath them. Where a standard report cannot support the decision, we build a custom analytical product instead.
A repeatable intelligence asset
Pipelines, definitions and quality controls make the evidence maintainable, while ownership and documentation let client teams operate it with confidence.
Related expertise
Connect the problem to delivery
Related work
Selected case studies from delivery
Media & Entertainment
Giving commercial teams a clearer view of streaming audiences
- Period
- Since 2022
- Scale / geography
- Global streaming audience and distributed commercial teams
- Work type
- Client work
- Status
- Ongoing
Challenges
Commercial teams needed audience intelligence that could support specific buyer conversations rather than relying on generic viewership data.
Outcome
- North American and UK teams use the intelligence in commercial workflows
- Pitch teams can explore buyer-relevant audience patterns
- Decision-makers share a consistent evidence base across markets
Delivery areas
Capabilities
Ecommerce and Gifting
Understanding customers through occasions, not just transactions
- Period
- Since 2024
- Scale / geography
- Scaled UK ecommerce customer and order data
- Work type
- Client work
- Status
- Ongoing
Challenges
A gifting business needed to understand the people, relationships and occasions behind purchases so that merchandising and communication could become more relevant.
Outcome
- Teams gained a shared view of customer and occasion behaviour
- Segments support more relevant merchandising and communication
- Repeatable analysis replaced one-off data requests
Delivery areas
Education Publishing
Turning global education surveys into usable intelligence
- Period
- Since 2025
- Scale / geography
- Global multi-market survey programme
- Work type
- Client work
- Status
- Ongoing
Challenges
A global publisher needed to make large volumes of survey data easier for research and commercial teams to explore across markets, roles and topics.
Outcome
- Global survey evidence can be explored through a consistent model
- Teams spend less time preparing repeated cuts of the data
- Market and audience comparisons are easier to communicate
Delivery areas
Capabilities
Further reading
Related insights
Field Notes
What Building Quantsole Taught Us About Production Analytics
Lessons from building Quantsole, Rodan’s BI and AutoML platform, and how they now shape our production analytics engineering.
Read More
Perspectives
How to move from data reports to AI-driven decisions
AI-driven decisions require more than better dashboards. Learn what the shift from data reports actually demands — and how to sequence it.
Read More
Perspectives
The difference between analytics, business intelligence and AI — and why it matters
Analytics, BI and AI are not interchangeable. Senior leaders who conflate them misallocate budget. Here is how to tell the difference and invest in the right layer.
Read More
Perspectives
Why specialist markets need intelligence infrastructure
Why specialist markets need connected, evidence-backed intelligence infrastructure rather than another static database or research report.
Read More
Frequently asked questions
How is an intelligence product different from a dashboard?
A dashboard reports what happened. An intelligence product supports a recurring decision: it brings together the right sources, applies consistent definitions and shows the options and their limits. It is built to be used every week or month, not viewed once.
What data sources can you work with?
We work with internal systems such as CRM, finance and operational databases, as well as market, public and third-party data. Much of the value comes from joining sources that were never designed to work together and making those joins reliable.
Do you work with Power BI?
Yes. Our analytics engineers work with Power BI, Tableau, Looker, SQL and Excel. Most reporting problems start beneath the report: inconsistent definitions, manual data preparation and missing quality checks. We fix the data model and pipelines first, then build reports people trust.
How do you make sure people trust the numbers?
We agree definitions with the people who use the numbers, add quality checks to the data pipelines and show where each figure comes from. When data is incomplete or uncertain, the product says so.
Do we need a data team to run it?
Not necessarily. Pipelines and quality checks run automatically and we document how the product works. If you have a data team, we hand over to them. If you do not, we can keep it running for you.
Can you add forecasting or AI?
Yes, where it improves the decision. We add forecasts, anomaly detection or AI summaries once the core data is reliable, and we show the confidence behind each output.
Explore the problem
Related solutions
Discuss the operational problem
Start with the constraint, the decision and the outcome that matters. We will help determine whether a focused build is the right response.
