Abstract

One main point distinguishing Marketing 4.0 from other marketing approaches is the “customer”. Marketing 4.0 focuses on “act” and “advocacy” within the 5A (aware, appeal, ask, act, and advocate) customer path. In Marketing 4.0, advocacy is as important as the purchase of customers. In order to have good competitive power in the digital world, and to follow and guide their digital customers, brands need to determine their marketing strategies by considering the 5A customer path, in which there may be touchpoints where brands can intervene. During the COVID-19 pandemic, there was a significant decrease in the incomes of consumers due to the closure of businesses and/or personnel dismissals. With this decrease in income, consumer purchasing habits have changed. For this reason, many companies have started studies to explore how to increase customer loyalty. This study aimed to understand how the marketing process and brand loyalty of a company operating in the cleaning products category were affected before and during the pandemic and to identify weak touchpoints in the customer path by developing a 5A customer path model based on fuzzy logic. The study also aimed to monitor customer purchasing and brand advocacy rates during the pandemic and detect the problematic touchpoints on the 5A customer path. The main contribution of this study to practitioners and brand strategy managers is that it brings a different dimension to the field of Marketing 4.0 applications with a fuzzy logic approach. In this study, a rule-based fuzzy logic application was used for the first time to identify the deficiencies in the 5A customer path. With the fuzzy logic approach, an artificial intelligence technology, failure points on the 5A customer path can be known in advance, and brand managers will be able to determine appropriate strategies to increase the advocacy of their brands and take precautions where necessary. Brand managers can periodically collect customer data and use fuzzy logic to identify and eliminate 5A customer path disruptions.

Full Text
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