Multilevel marketing: optimizing marketing effectiveness for high-involvement goods in the automotive industry
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Multilevel marketing: optimizing marketing effectiveness for high-involvement goods in the automotive industry Thomas Niemand 1 & Sascha Kraus 2 Antonio C. Cuenca-Ballester 4
& Sophia
Mather 3 &
# The Author(s) 2020
Abstract With a surge in communication channels increasing the complexity of today’s media landscape, companies face new challenges concerning the allocation of their advertising budget. As consumers become increasingly more autonomous in gathering information from the channels they deem most suitable, they encounter several touchpoints on their customer journey. Marketers struggle with the assessment of channel effectiveness. Despite a rise in research on the topic of attribution, findings and methodology vary greatly regarding variables and outcomes. The question of how to determine suitable attribution modeling that optimizes advertising effectiveness thus remains unanswered. This article aims at assessing which factors influence channel effectiveness in the context of high-involvement goods. Based on a unique dataset from a multinational car manufacturer, a Structural Vector Autoregressive model has been formulated revealing channel interactions, lagged effects of advertising and conversion funnel stages as being highly influential factors concerning channel effectiveness. Keywords Attribution modeling . Multichannel advertising . Multi-channel attribution
modeling . Conversion funnel . Channel effectiveness . Automotive industry
* Thomas Niemand thomas.niemand@tu–clausthal.de Sascha Kraus [email protected] Sophia Mather [email protected] Antonio C. Cuenca-Ballester [email protected] Extended author information available on the last page of the article
International Entrepreneurship and Management Journal
Introduction When one thinks about a journey, it is usually a linear path. A journey from one point to another, from A to B. The same linearity is associated with the term “customer journey.” This journey occurs through several touchpoints and devices from the moment a consumer establishes his/her need until the moment he makes a transaction. Each touchpoint has a specific impact, either bringing the consumer closer to or driving him further away from the conversion to become a customer (Batra and Keller 2016). In the context of multichannel marketing, the number of channels and devices used by consumers to gather information has drastically increased in recent years. Especially online advertising has gained popularity in the last decade and witnessed a massive growth in investment, predicted to account for 335.48 billion U.S. dollars in 2020 (eMarketer 2019). Increasing diversity and complexity of today’s communication environment, this emergence of new communication formats challenges media attribution (Gupta and Steenburgh 2008). The challenge of identifying the most effective advertising medium has particularly increased as consumers are exposed to several advertising formats and have become more autonomous in terms of choosing advertising channels. While companies u
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