Case Study

Customer segmentation thanks to Dynamic Targeting

The company

Our customer is an Italian multinational manufacturer of FMCG.

The need

Leverage different data sources to identify clusters of buyers based on their purchasing behaviours and their preferences in selected categories.

The solution

Lyriko was able to create a profiled segmentation and determine micro/macro clusters and triggers for Next Best Actions at customer-level.

First it mixed several data sources and filled any gaps in the raw product data with external information. It then designed personalized campaign clusters, by segmenting the database in accordance to the store type and applying clusterisation using a cascade approach (first hierarchical clustering then based on identified categories).

After that, Lyriko found the best representatives of user personas, interpreting the clusters across different dimensions. Thanks to this profiled segmentation, Lyriko was then able to leverage each targets’ channel propensity and improve their content affinity.

The results

  • More than 86k of qualified shoppers
  • Over 24 months of data
  • 10M receipts analysed

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