Blažek company is prominent Czech manufacturer of luxury clothing.
Objectives
Our task was to identify the members of the Blažek’s loyalty club who were sensitive to rewards so as to extend the profitable relationship. To save on the marketing budget, and increase efficiency of the mailing campaing, the Blažek loyalty club offerings should only reach the repeat and most loyal customers.
Solution
We used affinity model combining customer’s loyalty, past spending and his age as a Blažek’s customer. We came up with a predictive model built upon positive cases of back-coming customers. The model chooses customer with high probability of future purchase. Blažek offers advantages and discounts to these loyal and high-quality customers.
Results
As Blažek’s business is extremely stable the same applies also for the predictive model. It has been used already in twelve different communication waves without any drop in its effectivity. The model is used to assort customers in ten groups (deciles) according to their score of probability of future purchase. The top decile buys in 22 out of 100 cases whereas the average sixth decile only in 2 cases out of 100. Targeting at the tenth decile is therefore ten times more profitable than targeting at the average sixth decile. This implies that addressing the tenth decile is ten times more profitable than addressing the whole customer database.
Leaving out the deciles 1-5 from communication leads to significant cost cutting and increase in profitability.
References
Results of this case study were confirmed by Antonín Wierer, retail & marketing director, BLAŽEK PRAHA a.s.
