Summarizing and mapping it all out
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Including the introductory article of August 13th, this is the eighteenth and very last of this series of weekly articles on artificial intelligence in marketing. The idea is to give you a summary and a comprehensive map of the intersections between marketing activities and AI, knowing that this map will never be final! A little goody again at the end of this article.
A bit of history
The subject of artificial intelligence has fascinated me “since childhood,” and given my marketing background, it was inevitable that I would try to understand it from a marketing perspective, especially regarding its applications in strategic marketing.
Many years ago (I’m talking about the very early 1990s of the last century) there was timid talk about the applications of artificial intelligence with regard to so-called “expert systems”: they were basically rule-based systems, mostly based on tree architectures, that tried (and often succeeded!) to distill the experience and know-how of experts by making them accessible to anyone or almost anyone.
At that time, we had developed (myself together mainly with a friend who was also a marketer, but with a university background in physics, which didn’t hurt!), an expert system (“Strategic Marketing Exerciser”) intended to support teachers and marketing consultants in their work assisting small and medium-sized companies.
This product had also had a certain resonance at international conferences, and its development had been made possible thanks to European funding and the support of a major Italian training institute, which is still very active and present in the country, but which unfortunately (at least from my point of view) since the early 2000s has preferred to focus its mission on more prosaic topics but with more market: too bad, with them, and with those who at the time of the Strategic Marketing Exerciser were responsible for the marketing area, we would have seen and done some more good things!
In the meantime, expert systems have become much more sophisticated, thanks largely to machine learning, and, as everyone knows, AI developments are now exploding in an increasingly pervasive way.
I have let myself off the hook a bit, perhaps also with the intention of better contextualizing the goal of this final article, which is to propose, as food for thought on the topic, a sort of map that identifies, following the sequence of these articles, the areas of application of AI in strategic marketing of greatest potential interest.
Indeed, there are various sources in the literature on the intersection of AI and marketing (see an example below), but the best ones seem to me to be unwieldy and/or unfocused on the strategic aspects
I must say that in reflecting on the possible ways of classifying the areas of interest for strategic marketing (understood primarily as an orientation toward creating value for the market and for the company or entity that produces that value), I found the usual 4Ps (or even 6 or 7Ps, even less logically homogeneous) to be very meaningless for the umpteenth time.
Subject to possible contributions from readers, I would propose a classification according to the type of activities aimed at creating and making value available:
- knowledge (customer, expected value, context, channels, competition)
- creation/strategy (objectives, positioning, design, resources, pricing)
- execution/delivery, making value available (top management commitment and planning, organization, skills, information and control systems, KPIs)
- communication (target audience and content, platforms, sales force, tools, costs and benefits)
- relationship, involvement, and engagement (CRM, value analysis, value management, onboarding, community).
At this point, I would cross-reference the main functions performed by artificial intelligence, seen in the previous articles, with these activities. The result is proposed in the following graph (apologies for the quality of the photo, I’ll try to fix it).
As far as the academic literature on this topic is concerned, the following source is one of the most comprehensive ones that I found:
Ming-Hui Huang & Roland T. Rust, A strategic framework for artificial intelligence in marketing, Journal of the Academy of Marketing Science, 2020.
Stay in touch!
As a final reward for having been with me over the course of this series, I am offering you the usual classical music piece, played this time by Alice Sara Ott, my preferred pianist, followed closely by Olga Scheps and Hélène Grimaud, whom I highly recommend you listen to shortly: with Alice I usually listen to Beethoven, while Olga often plays Chopin and Hélène prefers Mozart and Rachmaninov.
But I would also be pleased to send you the ebook containing all the articles in this series, together with another ebook on “Marketing Models, Management Science & Decision Making”. Just email me here with the subject “ebooks”: firstname.lastname@example.org