/ Data & Analytics
A clearer view of your business.
A stronger basis for action.
In good company.
[OUR PERSPECTIVE]
Start with the decision you need to make, then work back to the evidence.
We bring customer, campaign and sales information together to investigate what is changing and why. The aim is to give your team a clearer basis for planning, prioritising and investing.
That can mean examining a specific question or building a more connected measurement approach. We make the assumptions, gaps and limits visible, so you know how much confidence to place in a recommendation.
[DATA EXPERTISE]
Choose the analytical approach that fits the problem and the evidence available. We connect the work with a decision your business needs to make.
Marketing mix modelling
Examine how marketing activity and other factors relate to business performance over time. Use the findings to explore budget choices, with the model’s assumptions and uncertainty made clear.
Predictive analytics
Use historical patterns to explore likely outcomes and the factors that influence them. We assess whether the data supports a useful forecast and how it should inform decisions.
CRM analysis
Connect acquisition with what happens after the first enquiry or purchase. Explore lead quality, repeat behaviour and customer value to help marketing focus on the relationships that matter.
Regression analysis
Examine relationships between activity and outcomes, accounting for relevant factors where the data allows. We distinguish an observed association from evidence of a causal effect.
Offline tracking
Connect available offline signals with marketing activity, from qualified calls to recorded purchases. We assess coverage, matching and data handling so gaps stay visible.
Customer segmentation
Group customers by behaviour or value that can guide a real decision. We help turn those differences into more relevant messaging, audience choices and retention priorities.
A useful finding explains what the evidence suggests, where it is uncertain and what you can do with it. Reporting is the beginning of that conversation.
[OUR WORK]
Jimmy Brings: using historical evidence to inform channel planning.
Jimmy Brings / Modelling & media planning
For Jimmy Brings, Magic analysed granular client media data and used mathematical modelling to inform the media strategy. The work connected historical patterns with channel planning decisions.
3 years
of granular client
media data analysed
A modelling and planning case study. The figure describes the analysis period, not a performance uplift.
[WHY MAGIC]
We define the decision, the audience for the work and what would make the answer useful before choosing a method or building a report.
Missing information and modelling assumptions affect what you can conclude. We explain them alongside the findings, so decisions reflect the strength of the evidence.
Our data specialists work with media and marketing teams to translate findings into budget choices, audience priorities and tests that can inform the next decision.
[THE MAGIC APPROACH]
A clear analytical brief, a transparent method and an output your team can use.
01
Agree the business question, available data and measures of success. Identify access requirements and the gaps that could affect the work.
What you get
A scoped analysis plan
02
Review data quality, connect the relevant sources and apply the agreed analysis. Test the assumptions and document what the evidence supports.
What you get
Findings with clear context
03
Walk through the results, scenarios and limits with your team. Agree the decisions or tests that follow and how to assess their effect.
What you get
Practical recommendations
FAQs
Access, data quality, modelling and what you can expect from the work.
It depends on the question. Relevant inputs may include media activity, campaign results, sales, CRM records and business context such as pricing or promotions. We agree the minimum useful data and access arrangements during scoping.
We begin by assessing quality, coverage and consistency. Some questions can still be answered with limitations; others may require better collection first. We explain what is feasible before committing to a method.
Platform attribution assigns credit using the rules and signals available within that system. Modelling can examine broader patterns across channels and other influences. They answer different questions, and neither removes the need to understand assumptions and missing information.
Not necessarily. We start with your current systems and the decisions you need to support. Any recommendation for a new reporting setup should have a clear purpose and an agreed scope.
We agree access, handling and retention requirements before work starts and aim to use only the information needed for the analysis. Where practical, aggregated or de-identified data can reduce the need for customer-level information.
Timing depends on the question, data readiness, access and analytical approach. We set out stages and dependencies in the proposal, including time for your team to review findings and provide context.
Yes. A focused project can establish whether the available evidence supports a particular decision. We agree the question, the output and the limits of the work, then discuss any next steps based on what we find.
Our free marketing and digital audit checks for best practices and identifies any wastage or missed strategic opportunities across your entire ecosystem.
