Data analytics
Exploratory analysis, metrics definitions, cohort and funnel analysis, forecasting and statistical evaluation of business data.
Answers to business questions, with the method shown.
5 deliverables, a 4-stage approach and 4 related technologies.
Overview
Teams often have more data than insight. Analytics starts with a decision someone needs to make, then works back to the data and methods that can inform it.
We define metrics precisely, analyse behaviour, funnels and cohorts, build forecasts where data supports them, and present results with their assumptions and limitations.
What we deliver
- Metric definitions document
- Analysis notebooks and findings
- Funnel and cohort analyses
- Forecasts with confidence ranges
- Recommendations tied to decisions
Use cases
Typical situations where this service is the right fit.
Conversion analysis
Find where customers drop off and why.
Operational analysis
Understand delays, utilisation and costs.
Programme evaluation
Assess whether an initiative achieved its goals.
How we work
The stages we follow. Each ends with something you can review.
- 01
Start from the decision
- 02
Agree definitions before computing numbers
- 03
Validate data quality first
- 04
Show uncertainty honestly
Things to consider
Questions worth answering before you commit budget.
- Correlation is not causation; experiments may be needed.
- Small samples produce unstable conclusions.
Technologies and engagement
Technologies we often use
We choose the stack with you; this is a starting point, not a requirement.
Ways to engage
- Fixed-scope project with milestones
- Dedicated team billed monthly
- Ongoing support and improvement retainer
Frequently asked questions
Solutions that use this service
Related services
Business intelligence
Self-service BI and operational dashboards with governed metrics, row-level access and scheduled reports.
Data engineering
Ingestion, transformation and orchestration pipelines, data warehouses and quality checks connecting operational systems to analytics.
AI and machine learning
Classical machine learning, forecasting, classification, recommendation and computer vision — from feasibility to monitored production models.
Ready to talk about data analytics?
Share a few details and we will reply with questions, options and an honest view of effort.