Author: Marta Wodzińska

Customer database segmentation

Posted on by Marta Wodzińska

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.

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.

Effects:

  • The report describing the segments was used to adjust the offer and language to each customer segment
  • Tracking customer migration between segments in time
  • Possibility to assess the increase in effectiveness of marketing activities addressed to a specific segment

Data base:

  • Sales data (over 3.4 billion items)
  • Consumer data (over 5 million customers)
  • Product data
  • Data on the use of discount codes

CRM performance analysis

Posted on by Marta Wodzińska

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.

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.

Effects:

  • The features of particularly valuable donors were identified, which made it possible to focus acquisition activities on people with an average donation value higher by about 60% than the rest
  • Reduction by about 10 percentage points of the percentage of people withdrawing from making the payments thanks to the recommendation that the retention activities should be accelerated

Data sources:

  • CRM Database
  • Data from the payment processing system
  • Fundraising activities calendar
  • Media data

Product recommendations on the website

Posted on by Marta Wodzińska

Problem:

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

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.

Effects:

  • Conversion increase by almost 14% (compared to the control group with disabled recommendations)
  • Increase in basket value by over 11%

Data sources:

  • Transaction data
  • Product data and business rules
  • Data on traffic on the website

Loyalty program dashboard

Posted on by Marta Wodzińska

Problem:

One of the retailers needed easy access to information about its loyalty program participant database. The information had to be legible, easily accessible and regularly updated.One of the retailers needed easy access to information about its loyalty program participant database. The information had to be legible, easily accessible and regularly updated.

Solution:

An interactive dashboard was built to present the most important information in a clear form. The dashboard is updated daily based on the loyalty program database and other data sources.

Effects:

  • Always up-to-date and legible information for managers responsible for the program
  • Good decisions translated into an almost twofold increase in the number of participants in the program in less than 2 years
  • EMAIL and SMS communication to program participants brought between PLN50 and 100 million of additional turnover per year

Data sources:

  • Data from the loyalty program
  • Sales data
  • Data from the mailing system