MadLab · staging · workflow branché

Un run public,
des sources réelles,
des outputs utiles.

Cette version staging exécute un vrai workflow: elle agrège des signaux publics, les score, choisit un angle, génère des livrables et persiste le dernier run pour lecture.

Voir le runVoir la chaîne
8
signaux captés
87
signal choisi
3
connecteurs
Run summary
Inputs
Marketing digital B2B
fondateur / growth manager / freelance
workflow IA de contenu marketing

Connecteurs actifs

Hacker News Algolia APIReddit public HTML fallbackarXiv public feed

Signaux détectés

01. arXiv cs.CLHarnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations
Large Language Models (LLMs) have revolutionized the process of customer engagement, campaign optimization, and content generation, in marketing management. In this paper, we explo
score 87
02. arXiv cs.CLComputational Studies in Influencer Marketing: A Systematic Literature Review
Influencer marketing has become a crucial feature of digital marketing strategies. Despite its rapid growth and algorithmic relevance, the field of computational studies in influen
score 75
03. Hacker NewsThe AI Marketing BS Index
score 70
04. Hacker NewsLessons Learned from 2 Years Marketing AI Bots
score 70
05. Hacker NewsLinus Torvalds: 90% of AI marketing is hype
score 70
06. Hacker NewsOn “Powered by AI / ML” Marketing
score 70
07. Hacker NewsAsk HN: Your thoughts on Linus Torvalds' view on AI: 90% marketing, 10% reality?
Linus Torvalds reportedly grimaced as labelled the current state of the AI market as “90% marketing and 10% reality.”

“I think AI is really interesting, and I think it is going t

score 65
08. arXiv cs.CLUncovering Relations for Marketing Knowledge Representation
Online behaviors of consumers and marketers generate massive marketing data, which ever more sophisticated models attempt to turn into insights and aid decisions by marketers. Yet,
score 65

Scoring & angle

Score: 87/100

Angle: Transformer "Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations" en campagne multi-format.

Le run choisit le meilleur signal public disponible, puis le transforme en message actionnable.

Assets générés

Hero
Transformez 1 signal en 1 campagne
Email
Votre prochain contenu peut venir de : Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations
Post
Le vrai avantage n’est pas de publier plus. C’est de transformer un signal comme “Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations” en campagne exploitable.

Carousel

  1. 1 Le problème: les idées sont éparpillées
  2. 2 Signal: Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations
  3. 3 Score: choisir ce qui vaut le coup
  4. 4 Factory: produire les assets
  5. 5 Queue + Loop: publier et apprendre

Publish queue

  • Slack (validation)
  • Notion (archive)
  • Sheets (tracking)
  • Email (draft)
  • Buffer-like (queue)

Metrics

CTRengagementrepliessaveswatchtime