Talk:Artificial intelligence marketing

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Wiki Education Foundation-supported course assignment[edit]

This article was the subject of a Wiki Education Foundation-supported course assignment, between 25 August 2020 and 10 December 2020. Further details are available on the course page. Student editor(s): Alr5845. Peer reviewers: Rwf5256, Lionwolf53.

Above undated message substituted from Template:Dashboard.wikiedu.org assignment by PrimeBOT (talk) 17:34, 17 January 2022 (UTC)[reply]

Wiki Education Foundation-supported course assignment[edit]

This article was the subject of a Wiki Education Foundation-supported course assignment, between 6 September 2020 and 6 December 2020. Further details are available on the course page. Student editor(s): Nectaros.

Above undated message substituted from Template:Dashboard.wikiedu.org assignment by PrimeBOT (talk) 17:34, 17 January 2022 (UTC)[reply]

New Edits[edit]

Hello everyone,

I am working on fixing this article for one of my classes. I am researching into each section of the article and plan to add a new section about how this marking technique is used in the real life. Here are some of the sources I am planning to use and investigate farther. - https://www.loc.gov/law/help/artificial-intelligence/americas.php - https://www.forbes.com/sites/forbesagencycouncil/2019/08/21/how-artificial-intelligence-is-transforming-digital-marketing/#23d7659421e1 - https://www.mentionlytics.com/blog/7-real-world-examples-of-how-brands-use-artificial-intelligence-in-marketing/ — Preceding unsigned comment added by Alr5845 (talkcontribs) 20:51, 30 September 2020 (UTC)[reply]

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Scope, intent, structure[edit]

I'm not certain what the intent of this article would be. I would propose first expanding Artificial intelligence#Applications with a subsection on Marketing. Has the term "Artificial intelligence marketing" been established as its own concept yet, rather than an application of AI and machine learning methods?

The "Collect, reason, act" section currently amounts to original research as well as most of what's written as far as I can tell.

The current sections might need to be restructured.

I'd first look into whether there are distinct methods used when big data, statistical methods, and machine learning are applied to marketing. (The paper "Bayesian Neural Network Learning for Repeat Purchase Modelling in Direct Marketing" in the further reading section is a good example.) How is data about marketing targets aggregated? What data points, typically? Do these methods differ when targeting customers vs. other businesses? There are certainly sources about companies, like Amazon for example, using some of these methods for product suggestions, tracking interest across the web, etc. Plenty of companies exist doing things like customer analytics, automated messaging, automated targeting on platforms like Facebook for example or even for business-to-business interactions. Things like sentiment analysis on text for customer satisfaction.

A lot could be done to salvage this article, assuming it doesn't overlap with too much elsewhere. Looking at Marketing automation and linked-to articles, it seems like there are a large number of articles on specific subtypes of marketing and methods with varying amounts of fine-grainedness with respect to the subject matter. Perhaps all of this should be compiled into a handful of very fleshed out, monolothic articles.

Anyone have any ideas? Ceci N'Est Pas Un Contributeur (talk) 19:03, 3 December 2019 (UTC)[reply]

Methods/papers[edit]

I went scavenging for some related papers on arXiv and found some inspiration.

  • Liu, Yiheng; Zhou, Wengang; Liu, Jianzhuang; Qi, Guojun; Tian, Qi; Li, Houqiang (2019). "An End-to-End Foreground-Aware Network for Person Re-Identification". arXiv:1910.11547 [cs.CV].
  • Zhao, Xilei; Zhou, Zhengze; Yan, Xiang; Pascal Van Hentenryck (2019). "Distilling Black-Box Travel Mode Choice Model for Behavioral Interpretation". arXiv:1910.13930 [stat.ML].
  • Lieder, Itay; Segal, Meirav; Avidan, Eran; Cohen, Asaf; Hope, Tom (2019). "Learning a faceted customer segmentation for discovering new business opportunities at Intel". arXiv:1912.00778 [cs.IR].
  • Lhéritier, Alix (2019). "PCMC-Net: Feature-based Pairwise Choice Markov Chains". arXiv:1909.11553 [cs.LG].
  • Dev, Soumyabrata; Hossari, Murhaf; Nicholson, Matthew; McCabe, Killian; Nautiyal, Atul; Conran, Clare; Tang, Jian; Xu, Wei; Pitié, François (2019). "Localizing Adverts in Outdoor Scenes". arXiv:1905.02106 [cs.CV].

Ceci N'Est Pas Un Contributeur (talk) 20:20, 3 December 2019 (UTC)[reply]

Wiki Education assignment: Social Informatics - ITI 200 Section 91[edit]

This article was the subject of a Wiki Education Foundation-supported course assignment, between 18 January 2024 and 29 April 2024. Further details are available on the course page. Student editor(s): Akshita.j, Hafiza Mubashra Fiaz, Ksg55032, Jfk156, Mm3179 (article contribs).

— Assignment last updated by Dhara447 (talk) 14:37, 23 April 2024 (UTC)[reply]