Category: Case studies EN

Problem:

In connection with the COVID-19 epidemic and potential customer concerns about the safety of their visits to the stores, one of the retailers in Poland wanted to provide their customers with precise information about the expected traffic volume in its brick and mortar stores.

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Rozwiązanie:

Based on machine learning algorithms, predictive models were prepared which are capable of forecasting the number of transactions in hourly intervals 7 days in advance. A mechanism for regular automatic refreshing (teaching) was built to allow for quick adaptation of forecasts to new “post-epidemic” reality and new patterns of consumer behaviour.

Problem:

One of the leading retailers in Poland with an extensive network of outlets of various formats needed to create a communication strategy for its customers. One of the stages of the project was the segmentation of the consumer database.

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Solution:

Using machine learning methods, 7 segments were identified based on 88 variables describing different aspects of customer behaviour. These segments were characterised and described for marketing purposes.

Problem:

One of the largest NGOs wanted to conduct a comprehensive review of CRM activities in the context of increasing the effectiveness of fundraising campaigns.

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Solution:

An extensive analysis of the donor database, gathered by the organisation and the history of their interactions, was conducted. An extensive report was prepared, summarising the effectiveness of the organization’s current activities and indicating areas for optimisation. The donor database was segmented.

Problem:

In connection with the development of the Internet sales channel, one of the retailers wanted to enrich its website with product recommendations.

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Rozwiązanie:

Based on the basket analysis, a recommendation engine was built to power the website. The system fully integrates with the website, enabling its dynamic modification in accordance with recommended scenarios.