Summary

Improved commercial performance for a digital marketplace by converting large volumes of customer interaction data into actionable personalisation and recommendation capabilities.

Context

A digital marketplace wanted to improve customer engagement and commercial performance by better understanding customer behaviour. The organisation had large amounts of customer interaction data but needed stronger capabilities to convert insights into business value.

Challenges

• ◆Limited personalisation capabilities despite rich available data
• ◆Difficulty identifying meaningful customer purchasing patterns
• ◆Manual business analysis processes creating analytical bottlenecks
• ◆Need to improve conversion rates and customer retention
• ◆Limited use of predictive insights in commercial decision-making

Approach & Contribution

I analysed customer behaviour and purchasing patterns, supported development of recommendation and personalisation capabilities, and applied analytics approaches to identify optimisation opportunities. I worked with business teams to translate data insights into actionable commercial decisions and supported improvements in reporting and decision-making tooling.

Outcomes

• ◆Improved product discovery and recommendation relevance
• ◆Better understanding of purchasing behaviour patterns
• ◆Increased relevance of customer interactions
• ◆Improved commercial decision-making through data
• ◆Reduced reliance on manual analysis processes