Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: How causal machine learning can leverage marketing strategies: Assessing
  and improving the performance of a coupon campaign   We apply causal machine learning algorithms to assess the causal effect of a
marketing intervention, namely a coupon campaign, on the sales of a retail
company. Besides assessing the average impacts of different types of coupons,
we also investigate the heterogeneity of causal effects across subgroups of
customers, e.g. across clients with relatively high vs. low previous purchases.
Finally, we use optimal policy learning to learn (in a data-driven way) which
customer groups should be targeted by the coupon campaign in order to maximize
the marketing intervention's effectiveness in terms of sales. Our study
provides a use case for the application of causal machine learning in business
analytics, in order to evaluate the causal impact of specific firm policies
(like marketing campaigns) for decision support.

14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
2
The categories of this paper are: math
9
The categories of this paper are: nlin