Abstract
This chapter discusses the philosophy behind algorithmic marketing. This is an umbrella term for techniques that aspire to make marketing efforts more personalized and effective. The meaning of customer centricity and its implications for algorithmic marketing are discussed at length.
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Notes
- 1.
This software goes by many names, and acronyms that are hard to keep track of. Two popular ones are CRM (customer relationship management) and CPD (customer data platform)—only two of the many acronyms that are employed in an overly confusing landscape of similar tools. In essence these tools form a place to centralize customer information and act upon it by sending (automated) messages through various channels. Some of these systems also offer analytics capabilities to analyze results, but few truly do that well.
- 2.
A memorable wisecrack in this context is that the average customer has but a single testicle, the message being that the average customer as such does not exist and that one should be very weary of just working with averages across large groups of customers.
- 3.
This data was created using a very simple simulation where 10,000 random customers are generated. Each of these customers makes a number of purchases that are drawn from a Poisson distribution with a mean of 5. Each purchase then has an equal probability of 30% of being assigned to our fictitious company.
- 4.
This graph was created by running a similar simulation as described previously while varying the market share with 5% increments.
- 5.
If you want to know more the book Experimentation Works by Stefan Thomke [8] provides an easily digestible introduction.
References
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Thomke, S. H. (2020). Experimentation works: The surprising power of business experiments. Harvard Business Press.
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Kerkhove, LP. (2022). The Case for Algorithmic Marketing. In: Data-driven Retailing. Management for Professionals. Springer, Cham. https://doi.org/10.1007/978-3-031-12962-9_7
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DOI: https://doi.org/10.1007/978-3-031-12962-9_7
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