Improving Marketing Interactions by Mining Sequences

摘要

The advent of digital marketing has revolutionized how a marketer reaches the organization's customers. Since each interaction with the customer is recorded today, the marketer can do a better job of measuring the effectiveness of marketing efforts. With multi-channel marketing data, comes a new set of challenges; those of measuring the effect of individual channels, understanding synergistic effects, and finally leveraging the information stored in the sequence of marketing activities. While there is some work addressing the first two challenges, we aim to shed light on the last question. The combinatorial explosion in the number of possible marketing sequences requires a systematic approach to address this problem. We propose an approach based on sequence mining to identify marketing touch sequences that are most likely to lead to a stated marketing goal. Our approach provides a rapid way of creating marketing campaigns with the highest chance of success. We test our proposed approach on a real world dataset of a retail chain (with web visits, digital marketing channels, email data, instore and online purchase data). We compare against baseline approaches, and observe interesting insights in the real data.