Customer Intelligence Through Data
Turning customer behaviour into information teams could use to make better decisions.
The problem
The team needed a clearer understanding of purchasing patterns to identify opportunities for campaigns and offers, especially around lower-performing periods.
The reality
Useful answers required combining different datasets, cleaning information and translating business questions into robust analytical logic.
The approach
Daniel developed analytical models using SQL and Power BI, combining dimensions such as demographics, location, day of week, period and purchasing behaviour. The work supported KPI reporting and broader decision-making across the team.
The result
The resulting analysis gave teams a more structured view of customer behaviour and supported decisions around campaigns, benefits and other commercial opportunities.
What I learned
Data becomes valuable when it changes a decision. The dashboard is only the visible part; the real work is understanding the question, building the logic and making the result usable.